Enthalpy as internal energy in plug flow reactor models: A long-lasting assumption defeated and its effects on models predictions in dynamic regime

In this paper, a general dynamic model of a pseudo-homogeneous catalytic plug flow reactor (PFR) is developed, which does not apply the traditional assumption of negligible difference between enthalpy and internal energy inside its energy balance. Such a model is then compared to a second dynamic PFR model, whose energy conservation equation identifies internal energy with enthalpy. The aim is that of quantitatively investigating the real suitability of the identification of these two thermodynamic quantities (internal energy and enthalpy) in PFR modeling problems. The Claus process is selected as a meaningful case study for the aforementioned purposes

Investigation of hippocampal synaptic transmission and plasticity in mice deficient in the actin-binding protein Drebrin

The dynamic regulation of the actin cytoskeleton plays a key role in controlling the structure and function of synapses. It is vital for activity-dependent modulation of synaptic transmission and long-term changes in synaptic morphology associated with memory consolidation. Several regulators of actin dynamics at the synapse have been identified, of which a salient one is the postsynaptic actin stabilising protein Drebrin (DBN). It has been suggested that DBN modulates neurotransmission and changes in dendritic spine morphology associated with synaptic plasticity. Given that a decrease in DBN levels is correlated with cognitive deficits associated with ageing and dementia, it was hypothesised that DBN protein abundance instructs the integrity and function of synapses. We created a novel DBN deficient mouse line. Analysis of gross brain and neuronal morphology revealed no phenotype in the absence of DBN. Electrophysiological recordings in acute hippocampal slices and primary hippocampal neuronal cultures showed that basal synaptic transmission, and both long-term and homeostatic synaptic plasticity were unchanged, suggesting that loss of DBN is not sufficient in inducing synapse dysfunction. We propose that the overall lack of changes in synaptic function and plasticity in DBN deficient mice may indicate robust compensatory mechanisms that safeguard cytoskeleton dynamics at the synapse

Production of n-propyl acetate by reactive distillation : experimental and theoretical study

First steps of the development of a catalytic reactive distillation process for the production of n-propyl acetate based on experiments and simulations are proposed. The kinetics for homogeneously (sulphuric acid) and heterogeneously (Amberlyst 15) catalysed reaction were investigated and the constants for a pseudo-homogeneous model are presented. Pilot plant experiments were performed using a homogeneous strong acid catalyst in a packed column. A top-column decanter is used to withdraw the aqueous phase and to reflux the organic phase. Simulation results are in good agreement with experimental data. Thermodynamics nonidealities are taken into account using VLE and LLE NRTL interaction parameters. Alcohol conversion and n-propyl acetate purity may be dramatically increased just by adding to the pilot plant a stripping section in an additional column: six different configurations are identified to achieve such a production. The startup is studied in order to determine the best strategy to achieve steady-state conditions. The strong influence of the composition of the initial charging in the decanter can be seen and an initial charging of the two-phase top product leads to the fastest startup

Role of amyloid-β glycine 33 in oligomerization, toxicity, and neuronal plasticity

The aggregation of the amyloid-{beta} (Abeta) peptide plays a pivotal role in the pathogenesis of Alzheimer's disease, as soluble oligomers are intimately linked to neuronal toxicity and inhibition of hippocampal long-term potentiation (LTP). In the C-terminal region of Abeta there are three consecutive GxxxG dimerization motifs, which we could previously demonstrate to play a critical role in the generation of Abeta. Here, we show that glycine 33 (G33) of the central GxxxG interaction motif within the hydrophobic Abeta sequence is important for the aggregation dynamics of the peptide. Abeta peptides with alanine or isoleucine substitutions of G33 displayed an increased propensity to form higher oligomers, which we could attribute to conformational changes. Importantly, the oligomers of G33 variants were much less toxic than Abeta(42) wild type (WT), in vitro and in vivo. Also, whereas Abeta(42) WT is known to inhibit LTP, Abeta(42) G33 variants had lost the potential to inhibit LTP. Our findings reveal that conformational changes induced by G33 substitutions unlink toxicity and oligomerization of Abeta on the molecular level and suggest that G33 is the key amino acid in the toxic activity of Abeta. Thus, a specific toxic conformation of Abeta exists, which represents a promising target for therapeutic interventions

Acceleration of generalized hypergeometric functions through precise remainder asymptotics

We express the asymptotics of the remainders of the partial sums {s_n} of the generalized hypergeometric function q+1_F_q through an inverse power series z^n n^l \sum_k c_k/n^k, where the exponent l and the asymptotic coefficients {c_k} may be recursively computed to any desired order from the hypergeometric parameters and argument. From this we derive a new series acceleration technique that can be applied to any such function, even with complex parameters and at the branch point z=1. For moderate parameters (up to approximately ten) a C implementation at fixed precision is very effective at computing these functions; for larger parameters an implementation in higher than machine precision would be needed. Even for larger parameters, however, our C implementation is able to correctly determine whether or not it has converged; and when it converges, its estimate of its error is accurate.Comment: 36 pages, 6 figures, LaTeX2e. Fixed sign error in Eq. (2.28), added several references, added comparison to other methods, and added discussion of recursion stabilit

Multisensory causal inference in the brain

At any given moment, our brain processes multiple inputs from its different sensory modalities (vision, hearing, touch, etc.). In deciphering this array of sensory information, the brain has to solve two problems: (1) which of the inputs originate from the same object and should be integrated and (2) for the sensations originating from the same object, how best to integrate them. Recent behavioural studies suggest that the human brain solves these problems using optimal probabilistic inference, known as Bayesian causal inference. However, how and where the underlying computations are carried out in the brain have remained unknown. By combining neuroimaging-based decoding techniques and computational modelling of behavioural data, a new study now sheds light on how multisensory causal inference maps onto specific brain areas. The results suggest that the complexity of neural computations increases along the visual hierarchy and link specific components of the causal inference process with specific visual and parietal regions

Collective Animal Behavior from Bayesian Estimation and Probability Matching

Animals living in groups make movement decisions that depend, among other factors, on social interactions with other group members. Our present understanding of social rules in animal collectives is based on empirical fits to observations and we lack first-principles approaches that allow their derivation. Here we show that patterns of collective decisions can be derived from the basic ability of animals to make probabilistic estimations in the presence of uncertainty. We build a decision-making model with two stages: Bayesian estimation and probabilistic matching.
In the first stage, each animal makes a Bayesian estimation of which behavior is best to perform taking into account personal information about the environment and social information collected by observing the behaviors of other animals. In the probability matching stage, each animal chooses a behavior with a probability given by the Bayesian estimation that this behavior is the most appropriate one. This model derives very simple rules of interaction in animal collectives that depend only on two types of reliability parameters, one that each animal assigns to the other animals and another given by the quality of the non-social information. We test our model by obtaining theoretically a rich set of observed collective patterns of decisions in three-spined sticklebacks, Gasterosteus aculeatus, a shoaling fish species. The quantitative link shown between probabilistic estimation and collective rules of behavior allows a better contact with other fields such as foraging, mate selection, neurobiology and psychology, and gives predictions for experiments directly testing the relationship between estimation and collective behavior

Gender roles and couple conflicts: gender stereotypes in couples therapy in Mendoza City

Introducción: las concepciones sobre los roles de género se han modificado profundamente en las últimas décadas. Conllevan asignaciones diferenciales de poder y estatus, foco de los cuestionamientos feministas que en la actualidad impactan en la construcción de la subjetividad y en las expectativas de rol. En el ámbito de la vida privada confluyen los estereotipos de género tradicionales junto a nuevas concepciones de los mismos, lo cual podría generar conflictos al interior de las parejas y la vida familiar afectando también el sano desarrollo de niños, niñas y adolescentes cuando estas dificultades no son resueltas y llegan a tener manifestaciones violentas. El efecto de estas modificaciones en la vida íntima y su influencia en las consultas psicológicas de pareja ha sido escasamente estudiado

A Simple Artificial Life Model Explains Irrational Behavior in Human Decision-Making

Although praised for their rationality, humans often make poor decisions, even in simple situations. In the repeated binary choice experiment, an individual has to choose repeatedly between the same two alternatives, where a reward is assigned to one of them with fixed probability. The optimal strategy is to perseverate with choosing the alternative with the best expected return. Whereas many species perseverate, humans tend to match the frequencies of their choices to the frequencies of the alternatives, a sub-optimal strategy known as probability matching. Our goal was to find the primary cognitive constraints under which a set of simple evolutionary rules can lead to such contrasting behaviors. We simulated the evolution of artificial populations, wherein the fitness of each animat (artificial animal) depended on its ability to predict the next element of a sequence made up of a repeating binary string of varying size. When the string was short relative to the animats’ neural capacity, they could learn it and correctly predict the next element of the sequence. When it was long, they could not learn it, turning to the next best option: to perseverate. Animats from the last generation then performed the task of predicting the next element of a non-periodical binary sequence. We found that, whereas animats with smaller neural capacity kept perseverating with the best alternative as before, animats with larger neural capacity, which had previously been able to learn the pattern of repeating strings, adopted probability matching, being outperformed by the perseverating animats. Our results demonstrate how the ability to make predictions in an environment endowed with regular patterns may lead to probability matching under less structured conditions. They point to probability matching as a likely by-product of adaptive cognitive strategies that were crucial in human evolution, but may lead to sub-optimal performances in other environments

Grouping by feature of cross-modal flankers in temporal ventriloquism

Signals in one sensory modality can influence perception of another, for example the bias of visual timing by audition: temporal ventriloquism. Strong accounts of temporal ventriloquism hold that the sensory representation of visual signal timing changes to that of the nearby sound. Alternatively, underlying sensory representations do not change. Rather, perceptual grouping processes based on spatial, temporal, and featural information produce best-estimates of global event properties. In support of this interpretation, when feature-based perceptual grouping conflicts with temporal information-based in scenarios that reveal temporal ventriloquism, the effect is abolished. However, previous demonstrations of this disruption used long-range visual apparent-motion stimuli. We investigated whether similar manipulations of feature grouping could also disrupt the classical temporal ventriloquism demonstration, which occurs over a short temporal range. We estimated the precision of participants’ reports of which of two visual bars occurred first. The bars were accompanied by different cross-modal signals that onset synchronously or asynchronously with each bar. Participants’ performance improved with asynchronous presentation relative to synchronous - temporal ventriloquism - however, unlike the long-range apparent motion paradigm, this was unaffected by different combinations of cross-modal feature, suggesting that featural similarity of cross-modal signals may not modulate cross-modal temporal influences in short time scales