A Neural Theory of Attentive Visual Search: Interactions of Boundary, Surface, Spatial, and Object Representations

Visual search data are given a unified quantitative explanation by a model of how spatial maps in the parietal cortex and object recognition categories in the inferotemporal cortex deploy attentional resources as they reciprocally interact with visual representations in the prestriate cortex. The model visual representations arc organized into multiple boundary and surface representations. Visual search in the model is initiated by organizing multiple items that lie within a given boundary or surface representation into a candidate search grouping. These items arc compared with object recognition categories to test for matches or mismatches. Mismatches can trigger deeper searches and recursive selection of new groupings until a target object io identified. This search model is algorithmically specified to quantitatively simulate search data using a single set of parameters, as well as to qualitatively explain a still larger data base, including data of Aks and Enns (1992), Bravo and Blake (1990), Chellazzi, Miller, Duncan, and Desimone (1993), Egeth, Viri, and Garbart (1984), Cohen and Ivry (1991), Enno and Rensink (1990), He and Nakayarna (1992), Humphreys, Quinlan, and Riddoch (1989), Mordkoff, Yantis, and Egeth (1990), Nakayama and Silverman (1986), Treisman and Gelade (1980), Treisman and Sato (1990), Wolfe, Cave, and Franzel (1989), and Wolfe and Friedman-Hill (1992). The model hereby provides an alternative to recent variations on the Feature Integration and Guided Search models, and grounds the analysis of visual search in neural models of preattentive vision, attentive object learning and categorization, and attentive spatial localization and orientation.

Normal and Amnesis Learning, Recognition, and Memory by a Neural Model of Cortico-Hippocampal Interactions

The processes by which humans and other primates learn to recognize objects have been the subject of many models. Processes such as learning, categorization, attention, memory search, expectation, and novelty detection work together at different stages to realize object recognition. In this article, Gail Carpenter and Stephen Grossberg describe one such model class (Adaptive Resonance Theory, ART) and discuss how its structure and function might relate to known neurological learning and memory processes, such as how inferotemporal cortex can recognize both specialized and abstract information, and how medial temporal amnesia may be caused by lesions in the hippocampal formation. The model also suggests how hippocampal and inferotemporal processing may be linked during recognition learning.

Novel ingredients from brewers' spent grain - bioactivity in cell culture model systems and bioactivity retention in fortified food products

Functional food ingredients, with scientifically proven and validated bioactive effects, present an effective means of inferring physiological health benefits to consumers to reduce the risk of certain diseases. The search for novel bioactive compounds for incorporation into functional foods is particularly active, with brewers’ spent grain (BSG, a brewing industry co-product) representing a unique source of potentially bioactive compounds. The DNA protective, antioxidant and immunomodulatory effects of phenolic extracts from both pale (P1 - P4) and black (B1 – B4) BSG were examined. Black BSG extracts significantly (P < 0.05) protected against DNA damage induced by hydrogen peroxide (H2O2) and extracts with the highest total phenolic content (TPC) protected against 3-morpholinosydnonimine hydrochloride (SIN-1)-induced oxidative DNA damage, measured by the comet assay. Cellular antioxidant activity assays were used to measured antioxidant potential in the U937 cell line. Extracts P1 – P3 and B2 - B4 demonstrated significant (P < 0.05) antioxidant activity, measured by the superoxide dismutase (SOD) activity, catalase (CAT) activity and gluatathione (GSH) content assays. Phenolic extracts P2 and P3 from pale BSG possess anti-inflammatory activity measured in concanavalin-A (conA) stimulated Jurkat T cells by an enzyme-linked immunosorbent assay (ELISA); significantly (P < 0.05) reducing production of interleukin-2 (IL-2), interleukin-4 (IL-4, P2 only), interleukin-10 (IL-10) and interferon-γ (IFN-γ). Black BSG phenolic extracts did not exhibit anti-inflammatory effects in vitro. Hydroxycinnamic acids (HA) have previously been shown to be the phenolic acids present at highest concentration in BSG; therefore the HA profile of the phenolic extracts used in this research, the original barley (before brewing) and whole BSG was characterised and quantified using high performance liquid chromatography (HPLC). The concentration of HA present in the samples was in the order of ferulic acid (FA) > p-coumaric acid (p-CA) derivatives > FA derivatives > p-CA > caffeic acid (CA) > CA derivatives. Results suggested that brewing and roasting decreased the HA content. Protein hydrolysates from BSG were also screened for their antioxidant and anti-inflammatory potential. A total of 34 BSG protein samples were tested. Initial analyses of samples A – J found the protein samples did not exert DNA protective effects (except hydrolysate H) or antioxidant effects by the comet and SOD assays, respectively. Samples D, E, F and J selectively reduced IFN-γ production (P < 0.05) in Jurkat T cells, measured using enzyme linked immunosorbent assay (ELISA). Further testing of hydrolysates K – W, including fractionated hydrolysates with molecular weight < 3, < 5 and > 5 kDa, found that higher molecular weight (> 5 kDa) and unfractionated hydrolysates demonstrate greatest anti-inflammatory effects, while fractionated hydrolysates were also shown to have antioxidant activity, by the SOD activity assay. A commercially available yogurt drink (Actimel) and snack-bar and chocolate-drink formulations were fortified with the most bioactive phenolic and protein samples – P2, B2, W, W < 3 kDa, W < 5 kDa, W > 5 kDa. All fortified foods were subjected to a simulated gastrointestinal in vitro digestion procedure and bioactivity retention in the digestates was determined using the comet and ELISA assays. Yogurt fortified with B2 digestate significantly (P < 0.05) protected against H2O2-induced DNA damage in Caco-2 cells. Greatest immunomodulatory activity was demonstrated by the snack-bar formulation, significantly (P < 0.05) reducing IFN-γ production in con-A stimulated Jurkat T cells. Hydrolysate W significantly (P < 0.05) increased the IFN-γ reducing capacity of the snack-bar. Addition of fractionated hydrolysate W < 3 kDa and W < 5 kDa to yogurt also reduced IL-2 production to a greater extent than the unfortified yogurt (P < 0.05).

Application description and policy model in collaborative environment for sharing of information on epidemiological and clinical research data sets.

BACKGROUND: Sharing of epidemiological and clinical data sets among researchers is poor at best, in detriment of science and community at large. The purpose of this paper is therefore to (1) describe a novel Web application designed to share information on study data sets focusing on epidemiological clinical research in a collaborative environment and (2) create a policy model placing this collaborative environment into the current scientific social context. METHODOLOGY: The Database of Databases application was developed based on feedback from epidemiologists and clinical researchers requiring a Web-based platform that would allow for sharing of information about epidemiological and clinical study data sets in a collaborative environment. This platform should ensure that researchers can modify the information. A Model-based predictions of number of publications and funding resulting from combinations of different policy implementation strategies (for metadata and data sharing) were generated using System Dynamics modeling. PRINCIPAL FINDINGS: The application allows researchers to easily upload information about clinical study data sets, which is searchable and modifiable by other users in a wiki environment. All modifications are filtered by the database principal investigator in order to maintain quality control. The application has been extensively tested and currently contains 130 clinical study data sets from the United States, Australia, China and Singapore. Model results indicated that any policy implementation would be better than the current strategy, that metadata sharing is better than data-sharing, and that combined policies achieve the best results in terms of publications. CONCLUSIONS: Based on our empirical observations and resulting model, the social network environment surrounding the application can assist epidemiologists and clinical researchers contribute and search for metadata in a collaborative environment, thus potentially facilitating collaboration efforts among research communities distributed around the globe.

The Basic-Systems Model of Episodic Memory.

Behavior, neuropsychology, and neuroimaging suggest that episodic memories are constructed from interactions among the following basic systems: vision, audition, olfaction, other senses, spatial imagery, language, emotion, narrative, motor output, explicit memory, and search and retrieval. Each system has its own well-documented functions, neural substrates, processes, structures, and kinds of schemata. However, the systems have not been considered as interacting components of episodic memory, as is proposed here. Autobiographical memory and oral traditions are used to demonstrate the usefulness of the basic-systems model in accounting for existing data and predicting novel findings, and to argue that the model, or one similar to it, is the only way to understand episodic memory for complex stimuli routinely encountered outside the laboratory.

The librarian is in: a consultation model for information literacy formative assessment

Formative assessment was introduced in Rehabilitation Therapy students’ information literacy programs in Fall Term 2006 in the course OT/PT 892: Evidence-Based Practice. It was subsequently employed in the Winter Term 2008 and again in the Spring Term 2008. Formative assessment during student/librarian face-to-face consultations was one of a variety of teaching techniques used in the program. Other techniques included: a required reading; an interactive hands-on searching session; and a summative assessment of the final revised search strategy assignment (these techniques varied somewhat over the 3 classes). With the 2008 entrance class, this course content moved to OT/PT 898: Critical Enquiry, largely in Module 3: Reviewing the Literature. One of the Critical Enquiry’s learning objectives is: “recognize and reflect on the complexity of gathering evidence to inform decision-making.”

CARBON MONOXIDE AND PREGNANCY: A SEARCH FOR A POSSIBLE THERAPEUTIC IN THE TREATMENT OF PRE-ECLAMPSIA

Pre-eclampsia (PE) is a pregnancy disorder that affects roughly 5-7% of all pregnancies and is a leading cause of both maternal and fetal/neonatal morbidity and mortality. With no present cure for the disease, researchers are interested in the lower incidence of PE observed among the cigarette smoking pregnant population. However, women who use smokeless tobacco do not experience the same decreased incidence of PE, leading to hypothesis of protection against PE from the largest combustible product of cigarette smoke, carbon monoxide (CO). Studies evaluated levels of CO in PE women and found that they were statistically lower than those of healthy pregnancy. Researchers have found CO to possess many cytoprotective and regulatory properties and specifically within the placenta, it has been found to increase perfusion pressure, decrease oxidative stress, decreases ischemia/reperfusion induced apoptosis and maintain endothelial functioning. The idea for use of CO as a possible therapeutic for PE has thus become a real possibility. This study determined CO levels in pregnant women ± smoking as well as in PE women±smoking, as to discover a possible therapeutic range for future treatments. The best correlated automated CO measurement device with blood CO levels was determined, for use in future clinical studies. This thesis also sought a possible CO delivery concentration, in order to achieve the CO levels observed in the human correlation study. A threshold level of maternal CO exposure in a murine animal model was found, for which fetal and maternal negative toxicities were not observed. The results of this thesis lend a few more pieces to the complicated puzzle involving CO and PE and offer another step toward the possibility of a therapeutic treatment/prevention using this gaseous molecule.

Cooperativism, entrepreneurship and economic development: a linking theoretical model

Cooperatives, as a kind of firms, are considered by many scholars as an remarkable alternative for overcoming the economic crisis started in 2008. Besides, there are other scholars which pointed out the important role that these firms play in the regional economic development. Nevertheless, when one examines the economic literature on cooperatives, it is detected that this kind of firms is mainly studied starting from the point of view of their own characteristics and particularities of participation and solidarity. In this sense, following a different analysis framework, this article proposes a theoretical model in order to explain the behavior of cooperatives based on the entrepreneurship theory with the aim of increasing the knowledge about this kind of firms and, more specifically, their contribution to regional economic development.

Stochastic protein folding simulation in the three-dimensional HP-model

We present results from three-dimensional protein folding simulations in the HP-model on ten benchmark problems. The simulations are executed by a simulated annealing-based algorithm with a time-dependent cooling schedule. The neighbourhood relation is determined by the pull-move set. The results provide experimental evidence that the maximum depth D of local minima of the underlying energy landscape can be upper bounded by D < n(2/3). The local search procedure employs the stopping criterion (In/delta)(D/gamma) where m is an estimation of the average number of neighbouring conformations, gamma relates to the mean of non-zero differences of the objective function for neighbouring conformations, and 1-delta is the confidence that a minimum conformation has been found. The bound complies with the results obtained for the ten benchmark problems. (c) 2008 Elsevier Ltd. All rights reserved.

Strasheela: Design and usage of a music composition environment based on the Oz programming model

Strasheela provides a means for the composer to create a symbolic score by formally describing it in a rule-based way. The environment defines a rich music representation for complex polyphonic scores. Strasheela enables the user to define expressive compositional rules and then to apply them to the score. Compositional rules can restrict many aspects of the music - including the rhythmic structure, the melodic structure and the harmonic structure - by constraining the parameters (e.g. duration or pitch) of musical events according to some numerical or logical relation. Strasheela combines this expressivity with efficient search strategies.

A SuperWASP search for additional transiting planets in 24 known systems

We present results from a search for additional transiting planets in 24 systems already known to contain a transiting planet. We model the transits due to the known planet in each system and subtract these models from light curves obtained with the SuperWASP (Wide Angle Search for Planets) survey instruments. These residual light curves are then searched for evidence of additional periodic transit events. Although we do not find any evidence for additional planets in any of the planetary systems studied, we are able to characterize our ability to find such planets by means of Monte Carlo simulations. Artificially generated transit signals corresponding to planets with a range of sizes and orbital periods were injected into the SuperWASP photometry and the resulting light curves searched for planets. As a result, the detection efficiency as a function of both the radius and orbital period of any second planet is calculated. We determine that there is a good (>50 per cent) chance of detecting additional, Saturn-sized planets in P ~ 10 d orbits around planet-hosting stars that have several seasons of SuperWASP photometry. Additionally, we confirm previous evidence of the rotational stellar variability of WASP-10, and refine the period of rotation. We find that the period of the rotation is 11.91 +/- 0.05 d, and the false alarm probability for this period is extremely low (~10-13).

Unemployment Benefits and Reservation Wages: Key Elasticities from a Stripped-Down Job Search Approach

This paper exploits survey information on reservation wages and data on actual wages from the European Community Household Panel to deduce, in the manner of Lancaster and Chesher, additional parameters of a stylized structural search model; specifically, reservation wage and transition/duration elasticities. The informational requirements of this approach are minimal, thereby facilitating comparisons between countries. Further, its policy content is immediate in so far as the impact of unemployment benefit rules and measures increasing the arrival rate of job offers are concerned. These key elasticities are computed for the United Kingdom and 11 other European nations.

Fast automatic two-stage nonlinear model identification based on the extreme learning machine

It is convenient and effective to solve nonlinear problems with a model that has a linear-in-the-parameters (LITP) structure. However, the nonlinear parameters (e.g. the width of Gaussian function) of each model term needs to be pre-determined either from expert experience or through exhaustive search. An alternative approach is to optimize them by a gradient-based technique (e.g. Newton’s method). Unfortunately, all of these methods still need a lot of computations. Recently, the extreme learning machine (ELM) has shown its advantages in terms of fast learning from data, but the sparsity of the constructed model cannot be guaranteed. This paper proposes a novel algorithm for automatic construction of a nonlinear system model based on the extreme learning machine. This is achieved by effectively integrating the ELM and leave-one-out (LOO) cross validation with our two-stage stepwise construction procedure [1]. The main objective is to improve the compactness and generalization capability of the model constructed by the ELM method. Numerical analysis shows that the proposed algorithm only involves about half of the computation of orthogonal least squares (OLS) based method. Simulation examples are included to confirm the efficacy and superiority of the proposed technique.

Model Selection in SVMs Using Differential Evolution

To improve the performance of classification using Support Vector Machines (SVMs) while reducing the model selection time, this paper introduces Differential Evolution, a heuristic method for model selection in two-class SVMs with a RBF kernel. The model selection method and related tuning algorithm are both presented. Experimental results from application to a selection of benchmark datasets for SVMs show that this method can produce an optimized classification in less time and with higher accuracy than a classical grid search. Comparison with a Particle Swarm Optimization (PSO) based alternative is also included.

Determining the parametric effectiveness of a CAD model

The motivation for this paper is to present an approach for rating the quality of the parameters in a computer-aided design model for use as optimization variables. Parametric Effectiveness is computed as the ratio of change in performance achieved by perturbing the parameters in the optimum way, to the change in performance that would be achieved by allowing the boundary of the model to move without the constraint on shape change enforced by the CAD parameterization. The approach is applied in this paper to optimization based on adjoint shape sensitivity analyses. The derivation of parametric effectiveness is presented for optimization both with and without the constraint of constant volume. In both cases, the movement of the boundary is normalized with respect to a small root mean squared movement of the boundary. The approach can be used to select an initial search direction in parameter space, or to select sets of model parameters which have the greatest ability to improve model performance. The approach is applied to a number of example 2D and 3D FEA and CFD problems.