Responding to membership in a disadvantaged group: From acceptance to collective protest.

The question addressed is, when do disadvantaged-group members accept their situation, take individual action, or attempt to instigate collective action? Ss attempted to move from a low-status group into an advantaged, high-status group and were asked to respond to their subsequent rejection. Ss who believed that the high-status group was open to members of their group endorsed acceptance and individual actions. When access to the high-status group was restricted, even to the point of being almost closed (tokenism), Ss still preferred individual action. Disruptive forms of collective action were only favored by Ss who were told that the high-status group was completely closed to members of their group. Ss who believed they were near to gaining entry into the high-status group favored individual protest, while Ss distant from entry were more likely to accept their position. The theoretical and societal implications of these findings are discussed. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Glutamatergic regulation of basal and stimulus-activated dopamine release in the prefrontal cortex

The present study was undertaken to determine whether basal and stimulus-activated dopamine release in the prefrontal cortex (PFC) is regulated by glutamatergic afferents to the PFC or the ventral tegmental area (VTA), the primary source of dopamine neurons that innervate the rodent PFC. In awake rats, blockade of NMDA or alpha-amino-3-hydroxy-5-methylisoxazole-4-propionate (AMPA) receptors in the VTA, or blockade of AMPA receptors in the PFC, profoundly reduced dopamine release in the PFC, suggesting that the basal output of dopamine neurons projecting to the PFC is under a tonic excitatory control of NMDA and AMPA receptors in the VTA, and AMPA receptors in the PFC. Consistent with previous reports, blockade of cortical NMDA receptors increased dopamine release, suggesting that NMDA receptors in the PFC exert a tonic inhibitory control on dopamine release. Blockade of NMDA or AMPA receptors in the VTA as well as blockade of AMPA receptors in the PFC reduced the dopaminergic response to mild handling, suggesting that activation of glutamate neurotransmission also regulates stimulus-induced increase of dopamine release in the PFC. In the context of brain disorders that may involve cortical dopamine dysfunction, the present findings suggest that abnormal basal or stimulus-activated dopamine neurotransmission in the PFC may be secondary to glutamatergic dysregulation.     

Effects of lesions of the associative parietal cortex on the acquisition and use of spatial memory in egocentric and allocentric navigation tasks in the rat.

It has been hypothesized that the rat associative parietal cortex (APC) is involved in the association between visuospatial and locomotion-generated (kinesthetic) information. To study the kinesthetic component, APC-lesioned and control rats were trained in total darkness to reach a submerged platform in the Morris water maze. In the egocentric task, the relative position of the starting point and the platform was constant all over training. Parietal rats have been found impaired in acquisition and to a less extent in retention of this task. In the allocentric task, rats were then trained in the standard version of the navigation task. A mild deficit was observed in acquisition of this task because the APC-lesioned rats displayed longer escape latencies but control-like search patterns. These results suggest that the APC is involved in the coding of kinesthetic information that plays an important role in place navigation. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Glutamate receptors in the rat medial prefrontal cortex regulate set-shifting ability.

The authors examined set-shifting abilities in rats injected with antagonists of N-methyl-D-aspartate (NMDA) receptors (MK801) or alpha-amino-3-hydroxy-5-methylisoxazole-4-propionic acid (AMPA) receptors (LY293558) into the medial prefrontal cortex (mPFC). Set-shifting was assessed with a maze-based task requiring a switch between brightness and texture discrimination strategies. Intra-mPFC injection of MK801 prior to training on the 2nd discrimination impaired discrimination strategy acquisition. The MK801-induced deficit was due to increased perseverative responding. AMPA receptor blockade also impaired acquisition of the 2nd discrimination, these impairments were due to more general cognitive deficits. Results suggest that, within the mPFC, both AMPA and NMDA receptors are necessary for set-shifting, and that NNMA receptor hypofunction impairs the capacity to modify existing knowledge or to inhibit responses that are no longer appropriate. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

An efficient hybrid genetic algorithm to solve assembly line balancing problem with sequence-dependent setup times

In this paper the setup assembly line balancing and scheduling problem (SUALBSP) is considered. Since this problem is NP-hard, a hybrid genetic algorithm (GA) is proposed to solve the problem. This problem involves assigning the tasks to the stations and scheduling them inside each station. A simple permutation is used to determine the sequence of tasks. To determine the assignment of tasks to stations, the algorithm is hybridized using a dynamic programming procedure. Using dynamic programming, at any time a chromosome can be converted to an optimal solution (subject to the chromosome sequence).     

A hybrid fuzzy regression-fuzzy cognitive map algorithm for forecasting and optimization of housing market fluctuations

This paper presents a hybrid algorithm based on fuzzy linear regression (FLR) and fuzzy cognitive map (FCM) to deal with the problem of forecasting and optimization of housing market fluctuations. Due to the uncertainty and severe noise associated with the housing market, the application of crisp data for forecasting and optimization purposes is insufficient. Hence, in order to enable the decision-makers to make decisions with respect to imprecise/fuzzy data, FLR is used in the proposed hybrid algorithm. The best-fitted FLR model is then selected with respect to two indicators including Index of Confidence (IC) and Mean Absolute Percentage Error (MAPE). To achieve this objective, analysis of variance (ANOVA) for a randomized complete block design (RCBD) is employed. The primary objective of this study is to utilize imprecise/fuzzy data in order to improve the analysis of housing price fluctuations, in accordance with the factors obtained through the best-fitted FLR model. The secondary objective of this study is the exhibition of the resulted values in a schematic way via FCM. Hybridization of FLR and FCM provides a decision support system (DSS) for utilization of historical data to predict housing market fluctuation in the future and identify the influence of the other parameters. The proposed hybrid FLR-FCM algorithm enables the decision-makers to utilize imprecise and ambiguous data and represent the resulted values of the model more clearly. This is the first study that utilizes a hybrid intelligent approach for housing price and market forecasting and optimization.     

An integrated Data Envelopment Analysis–Artificial Neural Network–Rough Set Algorithm for assessment of personnel efficiency

Personnel specifications have greatest impact on total efficiency. They can help us to design work environment and enhance total efficiency. Determination of critical personnel attributes is a useful procedure to overcome complication associated with multiple inputs and outputs. The proposed algorithm assesses the impact of personnel efficiency attributes on total efficiency through Data Envelopment Analysis (DEA), Artificial Neural Network (ANN) and Rough Set Theory (RST). DEA has two roles in the proposed integrated algorithm of this study. It provides data ANN and finally it selects the best reduct through ANN result. Reduct is described as a minimum subset of attributes, completely discriminating all objects in a data set. The reduct selection is achieved by RST. ANN has two roles in the integrated algorithm. ANN results are basis for selecting the best reduct and it is also used for forecasting total efficiency. The proposed integrated approach is applied to an actual banking system and its superiorities and advantages are discussed.     

Multimodal information fusion application to human emotion recognition from face and speech

A multimedia content is composed of several streams that carry information in audio, video or textual channels. Classification and clustering multimedia contents require extraction and combination of information from these streams. The streams constituting a multimedia content are naturally different in terms of scale, dynamics and temporal patterns. These differences make combining the information sources using classic combination techniques difficult. We propose an asynchronous feature level fusion approach that creates a unified hybrid feature space out of the individual signal measurements. The target space can be used for clustering or classification of the multimedia content. As a representative application, we used the proposed approach to recognize basic affective states from speech prosody and facial expressions. Experimental results over two audiovisual emotion databases with 42 and 12 subjects revealed that the performance of the proposed system is significantly higher than the unimodal face based and speech based systems, as well as synchronous feature level and decision level fusion approaches.     

Mechanistic study of electrochemical oxidation of o-dihydroxybenzenes in the presence of 4-hydroxy-1-methyl-2(1H)-quinolone: Application to the electrochemical synthesis

Electrochemical oxidation of o-dihydroxybenzenes (1a and 1b) has been studied in the presence of 4-hydroxy-1-methyl-2(1H)-quinolone (3) as a nucleophile in aqueous solution using cyclic voltammetry and controlled-potential coulometry. The results indicate that the o-quinones derived from o-dihydroxybenzenes (1a and 1b) participate in 1,4-(michael) addition reactions with 3 to form the corresponding new o-dihydroxybenzene derivatives (6a and 6b). We propose a mechanism for the electrode process. The efficient electrochemical synthesis of 6a and 6b has been successfully performed at carbon rod electrodes in an undivided cell in good yield and purity. The products have been characterized after purification by IR, ¹H NMR, ¹³C NMR and MS.     

Planning Robot Navigation among Movable Obstacles (NAMO) through a Recursive Approach

This paper addresses the NP-complete problem of Navigation Among Movable Obstacles (NAMO) in which a robot is required to find a collision-free path toward a goal through manipulating and transferring some movable objects on its way. The robot’s main goal is to optimize a performance criterion such as runtime, length of transit or transfer paths, number of manipulated obstacles, total number of displacements of all objects, etc. We have designed a recursive algorithm capable of solving various NAMO problems, ranging from linear monotone to nonlinear non-monotone, and with convex or concave polygonal obstacles. Through the adopted approach, the original problem is decomposed into recursively-solved subproblems, in each of which only one movable object is manipulated. In each call of the algorithm, first a Visibility Graph determines a path from the robot’s current configuration to an intermediate goal configuration, and then a tentative final configuration for the last object intercepting the path is calculated using the Penetration Depth concept. It is assumed that the objects can be pulled or pushed, but not rotated, in a continuous space, and under such assumptions the method is complete and locally optimal for convex objects, with a worst-case time complexity of O(n⁴3^m) in which m is the number of movable objects and n is the number of all vertices on them. Several computational experiments showed that compared to the existing methods in the literature, the proposed recursive method achieved equal or smaller number of transferred obstacles or the total number of displacements of all objects in majority of the test problems.