Serotonergic neurons in the median raphe nucleus regulate inhibitory avoidance but not escape behavior in the rat elevated T-maze test of anxiety

Rationale: A wealth of evidence supports the involvement of the serotonergic neurons of the median raphe nucleus (MRN) in anxiety. However, it is presently unclear whether serotonergic pathways arising from this nucleus play distinguishing regulatory roles in defensive behaviors that have been associated with specific subtypes of anxiety disorders. Objectives: To evaluate the role of the MRN serotonergic neurons in the regulation of two defensive behaviors, inhibitory avoidance and escape, which have been related, respectively, to generalized anxiety and panic disorders. Methods: Male Wistar rats were submitted to the elevated T-maze test of anxiety after intra-MRN administration of drugs that either non-selectively or selectively change the activity of the serotonergic neurons. Results: Intra-MRN injection of FG 7142 (0.04 and 0.08 nmol) and kainic acid (0.03 and 0.06 nmol), drugs that non-selectively stimulate the MRN serotonergic neurons, facilitated inhibitory avoidance acquisition, but impaired escape performance. Microinjection of muscimol (0.11 and 0.22 nmol), a compound that non-selectively inhibits the activity of the MRN serotonergic neurons, impaired inhibitory avoidance and facilitated escape performance. Both kainic acid and muscimol also changed rat locomotion in the open-field test. Intra-MRN injection of 8-OH-DPAT (0.6-15 nmol) and WAY-100635 (0.18-0.74 nmol), respectively an agonist and an antagonist of somatodendritic 5-HT1A receptors located on serotonergic neurons of the MRN, only affected inhibitory avoidance-while the former inhibited the acquisition of this behavior, the latter facilitated it. Conclusion: MRN serotonergic neurons seem to be selectively involved in the regulation of inhibitory avoidance in the elevated T-maze. This result supports the proposal that 5-HT pathways departing from this nucleus play an important role in anxiety processing, with implications for pathologies such as generalized anxiety disorder.

Power flow for primary distribution networks considering uncertainty in demand and user connection

This paper presents a method for calculating the power flow in distribution networks considering uncertainties in the distribution system. Active and reactive power are used as uncertain variables and probabilistically modeled through probability distribution functions. Uncertainty about the connection of the users with the different feeders is also considered. A Monte Carlo simulation is used to generate the possible load scenarios of the users. The results of the power flow considering uncertainty are the mean values and standard deviations of the variables of interest (voltages in all nodes, active and reactive power flows, etc.), giving the user valuable information about how the network will behave under uncertainty rather than the traditional fixed values at one point in time. The method is tested using real data from a primary feeder system, and results are presented considering uncertainty in demand and also in the connection. To demonstrate the usefulness of the approach, the results are then used in a probabilistic risk analysis to identify potential problems of undervoltage in distribution systems. (C) 2012 Elsevier Ltd. All rights reserved.

Optic Flow Contribution to Locomotion Adjustments in Obstacle Avoidance

Locomotion generates a visual movement pattern characterized as optic flow. To explore how the locomotor adjustments are affected by this pattern, an experimental paradigm was developed to eliminate optic flow during obstacle avoidance. The aim was to investigate the contribution of optic flow in obstacle avoidance by using a stroboscopic lamp. Ten young adults walked on an 8m pathway and stepped over obstacles at two heights. Visual sampling was determined by a stroboscopic lamp (static and dynamic visual sampling). Three-dimensional kinematics data showed that the visual information about self-motion provided by the optic flow was crucial for estimating the distance from and the height of the obstacle. Participants presented conservative behavior for obstacle avoidance under experimental visual sampling conditions, which suggests that optic flow favors the coupling of vision to adaptive behavior for obstacle avoidance.

Mapping an uncertainty zone between interpolated types of a categorical variable

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

DERIVATION OF THE ENERGY-TIME UNCERTAINTY RELATION

A derivation from first principles is given of the energy-time uncertainty relation in quantum mechanics. A canonical transformation is made in classical mechanics to a new canonical momentum, which is energy E, and a new canonical coordinate T, which is called tempus, conjugate to the energy. Tempus T, the canonical coordinate conjugate to the energy, is conceptually different from the time t in which the system evolves. The Poisson bracket is a canonical invariant, so that energy and tempus satisfy the same Poisson bracket as do p and q. When the system is quantized, we find the energy-time uncertainty relation DELTAEDELTAT greater-than-or-equal-to HBAR/2. For a conservative system the average of the tempus operator T is the time t plus a constant. For a free particle and a particle acted on by a constant force, the tempus operators are constructed explicitly, and the energy-time uncertainty relation is explicitly verified.

Transmission network expansion planning considering uncertainty in demand

This paper presents two mathematical models and one methodology to solve a transmission network expansion planning problem considering uncertainty in demand. The first model analyzed the uncertainty in the system as a whole; then, this model considers the uncertainty in the total demand of the power system. The second one analyzed the uncertainty in each load bus individually. The methodology used to solve the problem, finds the optimal transmission network expansion plan that allows the power system to operate adequately in an environment with uncertainty. The models presented are solved using a specialized genetic algorithm. The results obtained for several known systems from literature show that cheaper plans can be found satisfying the uncertainty in demand.

EFFECT OF FENCAMFAMINE ON AVOIDANCE PERFORMANCES OF RATS

The effects of fencamfamine (1.0 and 5.0 mg/kg, ip, single dose) on an inhibitory task were studied in rats (N = 15 per group). Post-training treatment with fencamfamine (1.0 mg/kg) significantly increased avoidance latency from 23 +/- 3 to 146 +/- 28 and 170 +/- 33 s for training day 1 and day 7, respectively, indicating an enhancement of retention. However, retention was significantly reduced with a high dose of fencamfamine (5.0 mg/kg). These results demonstrate that fencamfamine caused a reproducible dose-related increase and reduction in avoidance latency.

Contrasting effects of acute and chronic treatment with imipramine and fluoxetine on inhibitory avoidance and escape responses in mice exposed to the elevated T-maze

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Transmission network expansion planning considering uncertainty in generation and demand

This paper presents a mathematical model and a methodology to solve a transmission network expansion planning problem considering uncertainty in demand and generation. The methodology used to solve the problem, finds the optimal transmission network expansion plan that allows the power system to operate adequately in an environment with uncertainty. The model presented results in an optimization problem that is solved using a specialized genetic algorithm. The results obtained for known systems from the literature show that cheaper plans can be found satisfying the uncertainty in demand and generation. ©2008 IEEE.

Calibration uncertainty estimation for internal aerodynamic balance

Aerodynamic balances are employed in wind tunnels to estimate the forces and moments acting on the model under test. This paper proposes a methodology for the assessment of uncertainty in the calibration of an internal multi-component aerodynamic balance. In order to obtain a suitable model to provide aerodynamic loads from the balance sensor responses, a calibration is performed prior to the tests by applying known weights to the balance. A multivariate polynomial fitting by the least squares method is used to interpolate the calibration data points. The uncertainties of both the applied loads and the readings of the sensors are considered in the regression. The data reduction includes the estimation of the calibration coefficients, the predicted values of the load components and their corresponding uncertainties, as well as the goodness of fit.

Reactive power support pricing of distributed generators with primary energy source uncertainty

In this paper, a novel methodology to price the reactive power support ancillary service of Distributed Generators (DGs) with primary energy source uncertainty is shown. The proposed methodology provides the service pricing based on the Loss of Opportunity Costs (LOC) calculation. An algorithm is proposed to reduce the uncertainty present in these generators using Multiobjective Power Flows (MOPFs) implemented in multiple probabilistic scenarios through Monte Carlo Simulations (MCS), and modeling the time series associated with the generation of active power from DGs through Markov Chains (MC). © 2011 IEEE.

A multi-objective programming approach for the optimal operation of distributed generation considering uncertainty

Due to the renewed interest in distributed generation (DG), the number of DG units incorporated in distribution systems has been rapidly increasing in the past few years. This situation requires new analysis tools for understanding system performance, and taking advantage of the potential benefits of DG. This paper presents an evolutionary multi-objective programming approach to determine the optimal operation of DG in distribution systems. The objectives are the minimization of the system power losses and operation cost of the DG units. The proposed approach also considers the inherent stochasticity of DG technologies powered by renewable resources. Some tests were carried out on the IEEE 34 bus distribution test system showing the robustness and applicability of the proposed methodology. © 2011 IEEE.

Students' foregrounds: Hope, despair, uncertainty

A foreground is formed through the possibilities, tendencies, propensities, obstructions, barriers, hindrances, et cetera, which his or her context provides for a person. Simultaneously, a foreground is formed through the person's interpretations of these possibilities, tendencies, propensities, obstructions, barriers, hindrances. A foreground is a fragmented, partial, and inconsistent constellation of bits and pieces of aspirations, hopes, and frustrations. It might be both promising and frightening; it is always being rebuilt and restructured. Foregrounds are multiple as one person might see very different possibilities; at the same time they are collective and established through processes of communication. In this article educational meaning is discussed in terms of relationships between the students' foregrounds and activities in the classroom. I illustrate how students' dreams might be kept in cages, and how this has implications for how they engage or do not engage in learning processes. I investigate how a foreground might be ruined, and in what sense a ruined foreground might turn into a learning obstacle. Finally, I discuss processes of inclusion and exclusion with reference to the notion of foreground. © 2012. The Authors.

Transaction scheduling using dynamic conflict avoidance

Software transaction memory (STM) systems have been used as an approach to improve performance, by allowing the concurrent execution of atomic blocks. However, under high-contention workloads, STM-based systems can considerably degrade performance, as transaction conflict rate increases. Contention management policies have been used as a way to select which transaction to abort when a conflict occurs. In general, contention managers are not capable of avoiding conflicts, as they can only select which transaction to abort and the moment it should restart. Since contention managers act only after a conflict is detected, it becomes harder to effectively increase transaction throughput. More proactive approaches have emerged, aiming at predicting when a transaction is likely to abort, postponing its execution. Nevertheless, most of the proposed proactive techniques are limited, as they do not replace the doomed transaction by another or, when they do, they rely on the operating system for that, having little or no control on which transaction to run. This article proposes LUTS, a lightweight user-level transaction scheduler. Unlike other techniques, LUTS provides the means for selecting another transaction to run in parallel, thus improving system throughput. We discuss LUTS design and propose a dynamic conflict-avoidance heuristic built around its scheduling capabilities. Experimental results, conducted with the STAMP and STMBench7 benchmark suites, running on TinySTM and SwissTM, show how our conflict-avoidance heuristic can effectively improve STM performance on high contention applications. © 2012 Springer Science+Business Media, LLC.