The association between auditory memory span and speech rate in children from kindergarten to sixth grade

This study reexamined the association between speech rate and memory span in children from kindergarten to sixth grade (N = 152) in order to potentially account for the inconsistencies within the published literature on this topic. Some of the inconsistencies in past research may reflect the different methods adopted in assessing speech rate. In particular, repeating word triples may itself involve memory demands, contaminating the correlation between speech rate and memory span in younger children. Analyses using composite speech rate and memory span measures showed that speech rate for word triples shared variance with memory span that was independent of speech rate for single words. Moreover, speech rate for word triples was largely redundant with age in explaining additional variation in memory span once the effects of speech rate for single words were controlled. (C) 2002 Elsevier Science.

Working memory correlates of three symptom clusters in schizophrenia

This study was designed to examine whether discrete working memory deficits underlie positive, negative and disorganised symptoms of schizophrenia. Symptom dimension ratings were assigned to 52 outpatients with schizophrenia (ICD-10 criteria), using items drawn from the Positive and Negative Syndrome Scale (PANSS). Linear regression and correlational analyses were conducted to examine whether symptom dimension scores were related to performance on several tests of working memory function. Severity of negative symptoms correlated with reduced production of words during a verbal fluency task, impaired ability to hold letter and number sequences on-line and manipulate them Simultaneously, reduced performance during a dual task, and compromised visuospatial working memory under distraction-free conditions. Severity of disorganisation symptoms correlated with impaired visuospatial working memory under conditions of distraction, failure of inhibition during a verbal fluency task, perseverative responding on a test of set-shifting ability, and impaired ability to judge the veracity of simple declarative statements. Severity of positive symptoms was uncorrelated with performance on any of the measures examined. The present study provides evidence that the positive, negative and disorganised symptom dimensions of the PANSS constitute independent clusters, associated with unique patterns of working memory impairment. (C) 2002 Elsevier Science Ireland Ltd. All rights reserved.

An augmented Lanczos algorithm for the efficient computation of a dot-product of a function of a large sparse symmetric matrix

The Lanczos algorithm is appreciated in many situations due to its speed. and economy of storage. However, the advantage that the Lanczos basis vectors need not be kept is lost when the algorithm is used to compute the action of a matrix function on a vector. Either the basis vectors need to be kept, or the Lanczos process needs to be applied twice. In this study we describe an augmented Lanczos algorithm to compute a dot product relative to a function of a large sparse symmetric matrix, without keeping the basis vectors.

Provision of 4-1BB ligand enhances effector and memory CTL responses generated by immunization with dendritic cells expressing a human tumor-associated antigen

Up-regulation of receptor-ligand pairs during interaction of an MHC-presented epitope on dendritic cells (DCs) with cognate TCR may amplify, sustain, and drive diversity in the ensuing T cell immune response. Members of the TNF ligand superfamily and the TNFR superfamily contribute to this costimulatory molecule signaling. In this study, we used replication deficient adenoviruses to introduce a model tumor-associated Ag (the E7 oncoprotein of human papillomavirus 16) and the T cell costimulatory molecule 4-IBBL into murine DCs, and monitored the ability of these recombinant DO to elicit E7-directed T cell responses following immunization. Splenocytes from mice immunized with DCs expressing E7 alone elicited E7-directed effector and memory CTL responses. Coexpression of 4-1BBL in these E7-expressing DO increased effector and memory CTL responses when they were used for immunization. 4-1BBL expression up-regulated CD80 and CD86 second signaling molecules in DO. We also report an additive effect of 4-IBBL and receptor activator of NF-kappaB/receptor activator of NF-kappaB ligand coexpression in E7-transduced DC inummogens on E7-directed effector and memory CTL responses and on MHC class II and CD80/86 expression in DCs. Additionally, expression of 4-1BBL in E7-transduced DCs reduced nonspecific T cell activation characteristic of adenovirus vector-associated immunization. The results have generic implications for improved or tumor Ag-expressing DC vaccines by incorporation of exogenous 4-1BBL. There are also specific implications for an improved DC-based vaccine for human papillomavirus 16-associated cervical carcinoma.

Reciprocal changes in forebrain contents of glycogen and of glutamate/glutamine during early memory consolidation in the day-old chick

Passive avoidance learning is with advantage studied in day-old chicks trained to distinguish between beads of two different colors, of which one at training was associated with aversive taste. During the first 30-min post-training, two periods of glutamate release occur in the forebrain. One period is immediately after the aversive experience, when glutamate release is confined to the left hemisphere. A second release, 30 min later, may be bilateral, perhaps with preponderance of the right hemisphere. The present study showed increased pool sizes of glutamate and glutamine, specifically in the left hemisphere, at the time when the first glutamate release occurs, indicating de novo synthesis of glutamate/glutamine from glucose or glycogen, which are the only possible substrates. Behavioral evidence that memory is extinguished by intracranial administration at this time of iodoacetate, an inhibitor of glycolysis and glycogenolysis, and that the extinction of memory is counteracted by injection of glutamine, supports this concept. A decrease in forebrain glycogen of similar magnitude and coinciding with the increase in glutamate and glutamine suggests that glycogen rather than glucose is the main source of newly synthesized glutamate/glutamine. The second activation of glutamatergic activity 30 min after training, when memory is consolidated into stable, long-term memory, is associated with a bilateral increase in pool size of glutamate/glutamine. No glycogenolysis was observed at this time, but again there is a temporal correlation with sensitivity to inhibition by iodoacetate and rescue by glutamine, indicating the importance of de novo synthesis of glutamate/glutamine from glucose or glycogen. (C) 2003 Elsevier B.V All rights reserved.

Enhanced effector and memory CTL responses generated by incorporation of receptor activator of NF-kappa B(RANK)/RANK ligand costimulatory molecules into dendritic cell immunogens expressing a human tumor-specific antigen

The outcome of dendritic cell (DC) presentation of Ag to T cells via the TCR/MHC synapse is determined by second signaling through CD80/86 and, importantly, by ligation of costimulatory ligands and receptors located at the DC and T cell surfaces. Downstream signaling triggered by costimulatory molecule ligation results in reciprocal DC and T cell activation and survival, which predisposes to enhanced T cell-mediated immune responses. In this study, we used adenoviral vectors to express a model tumor Ag (the E7 oncoprotein of human papillomavirus 16) with or without coexpression of receptor activator of NF-kappaB (RANK)/RANK ligand (RANKL) or CD40/CD40L costimulatory molecules, and used these transgenic DCs to immunize mice for the generation of E7-directed CD8(+) T cell responses. We show that coexpression of RANK/RANKL, but not CD40/CD40L, in E7-expressing DCs augmented E7-specific IFN-gamma-secreting effector and memory T cells and E7-specific CTLs. These responses were also augmented by coexpression of T cell costimulatory molecules (RANKL and CD40L) or DC costimulatory molecules (RANK and CD40) in the E7-expressing DC immunogens. Augmentation of CTL responses correlated with up-regulation of CD80 and CD86 expression in DCs transduced with costimulatory molecules, suggesting a mechanism for enhanced T cell activation/survival. These results have generic implications for improved tumor Ag-expressing DC vaccines, and specific implications for a DC-based vaccine approach for human papillomavirus 16-associated cervical carcinoma.

Cognitive intervention protocol for age-related memory impairments

With the number of elderly people increasing tremendously worldwide, comes the need for effective methods to maintain or improve older adults' cognitive performance. Using continuous neurofeedback, through the use of EEG techniques, people can learn how to train and alter their brain electrical activity. A software platform that puts together the proposed rehabilitation methodology has been developed: a digital game protocol that supports neurofeedback training of alpha and theta rhythms, by reading the EEG activity and presenting it back to the subject, interleaved with neurocognitive tasks such as n-Back and Corsi Block-Tapping. This tool will be used as a potential rehabilitative platform for age-related memory impairments.

Error bounds for low-rank approximations of the first exponential integral kernel

A hierarchical matrix is an efficient data-sparse representation of a matrix, especially useful for large dimensional problems. It consists of low-rank subblocks leading to low memory requirements as well as inexpensive computational costs. In this work, we discuss the use of the hierarchical matrix technique in the numerical solution of a large scale eigenvalue problem arising from a finite rank discretization of an integral operator. The operator is of convolution type, it is defined through the first exponential-integral function and, hence, it is weakly singular. We develop analytical expressions for the approximate degenerate kernels and deduce error upper bounds for these approximations. Some computational results illustrating the efficiency and robustness of the approach are presented.

Grid structure impact in sparse point representation of derivatives

In the Sparse Point Representation (SPR) method the principle is to retain the function data indicated by significant interpolatory wavelet coefficients, which are defined as interpolation errors by means of an interpolating subdivision scheme. Typically, a SPR grid is coarse in smooth regions, and refined close to irregularities. Furthermore, the computation of partial derivatives of a function from the information of its SPR content is performed in two steps. The first one is a refinement procedure to extend the SPR by the inclusion of new interpolated point values in a security zone. Then, for points in the refined grid, such derivatives are approximated by uniform finite differences, using a step size proportional to each point local scale. If required neighboring stencils are not present in the grid, the corresponding missing point values are approximated from coarser scales using the interpolating subdivision scheme. Using the cubic interpolation subdivision scheme, we demonstrate that such adaptive finite differences can be formulated in terms of a collocation scheme based on the wavelet expansion associated to the SPR. For this purpose, we prove some results concerning the local behavior of such wavelet reconstruction operators, which stand for SPR grids having appropriate structures. This statement implies that the adaptive finite difference scheme and the one using the step size of the finest level produce the same result at SPR grid points. Consequently, in addition to the refinement strategy, our analysis indicates that some care must be taken concerning the grid structure, in order to keep the truncation error under a certain accuracy limit. Illustrating results are presented for 2D Maxwell's equation numerical solutions.

A flexible side information generation framework for distributed video coding

One of the most efficient approaches to generate the side information (SI) in distributed video codecs is through motion compensated frame interpolation where the current frame is estimated based on past and future reference frames. However, this approach leads to significant spatial and temporal variations in the correlation noise between the source at the encoder and the SI at the decoder. In such scenario, it would be useful to design an architecture where the SI can be more robustly generated at the block level, avoiding the creation of SI frame regions with lower correlation, largely responsible for some coding efficiency losses. In this paper, a flexible framework to generate SI at the block level in two modes is presented: while the first mode corresponds to a motion compensated interpolation (MCI) technique, the second mode corresponds to a motion compensated quality enhancement (MCQE) technique where a low quality Intra block sent by the encoder is used to generate the SI by doing motion estimation with the help of the reference frames. The novel MCQE mode can be overall advantageous from the rate-distortion point of view, even if some rate has to be invested in the low quality Intra coding blocks, for blocks where the MCI produces SI with lower correlation. The overall solution is evaluated in terms of RD performance with improvements up to 2 dB, especially for high motion video sequences and long Group of Pictures (GOP) sizes.

Low Complexity Intra Mode Selection for Efficient Distributed Video Coding

Motion compensated frame interpolation (MCFI) is one of the most efficient solutions to generate side information (SI) in the context of distributed video coding. However, it creates SI with rather significant motion compensated errors for some frame regions while rather small for some other regions depending on the video content. In this paper, a low complexity Infra mode selection algorithm is proposed to select the most 'critical' blocks in the WZ frame and help the decoder with some reliable data for those blocks. For each block, the novel coding mode selection algorithm estimates the encoding rate for the Intra based and WZ coding modes and determines the best coding mode while maintaining a low encoder complexity. The proposed solution is evaluated in terms of rate-distortion performance with improvements up to 1.2 dB regarding a WZ coding mode only solution.

Augmented LDPC Graph for Distributed Video Coding with Multiple Side Information

The advances made in channel-capacity codes, such as turbo codes and low-density parity-check (LDPC) codes, have played a major role in the emerging distributed source coding paradigm. LDPC codes can be easily adapted to new source coding strategies due to their natural representation as bipartite graphs and the use of quasi-optimal decoding algorithms, such as belief propagation. This paper tackles a relevant scenario in distributedvideo coding: lossy source coding when multiple side information (SI) hypotheses are available at the decoder, each one correlated with the source according to different correlation noise channels. Thus, it is proposed to exploit multiple SI hypotheses through an efficient joint decoding technique withmultiple LDPC syndrome decoders that exchange information to obtain coding efficiency improvements. At the decoder side, the multiple SI hypotheses are created with motion compensated frame interpolation and fused together in a novel iterative LDPC based Slepian-Wolf decoding algorithm. With the creation of multiple SI hypotheses and the proposed decoding algorithm, bitrate savings up to 8.0% are obtained for similar decoded quality.

A hybrid intelligent system for distributed dynamic scheduling

This chapter addresses the resolution of dynamic scheduling by means of meta-heuristic and multi-agent systems. Scheduling is an important aspect of automation in manufacturing systems. Several contributions have been proposed, but the problem is far from being solved satisfactorily, especially if scheduling concerns real world applications. The proposed multi-agent scheduling system assumes the existence of several resource agents (which are decision-making entities based on meta-heuristics) distributed inside the manufacturing system that interact with other agents in order to obtain optimal or near-optimal global performances.