Consistent off-shell πNN\pi N N vertex and nucleon self-energy

We present a consistent calculation of half-off-shell form factors in the pion-nucleon vertex and the nucleon self-energy. Numerical results are presented. Near the on-shell point the pion-nucleon vertex is dominated by the pseudovector coupling, while at large nucleon invariant masses we find a sizable pseudoscalar admixture.Comment: 23 pages, 7 figures, REVTeX, submitted to Phys. Rev. C, replaced with corrected versio

Quasi-Elastic Scattering in the Inclusive (3^3He, t) Reaction

The triton energy spectra of the charge-exchange $^{12}$C($^3$He,t) reaction at 2 GeV beam energy are analyzed in the quasi-elastic nucleon knock-out region. Considering that this region is mainly populated by the charge-exchange of a proton in $^3$He with a neutron in the target nucleus and the final proton going in the continuum, the cross-sections are written in the distorted-wave impulse approximation. The t-matrix for the elementary exchange process is constructed in the DWBA, using one pion- plus rho-exchange potential for the spin-isospin nucleon- nucleon potential. This t-matrix reproduces the experimental data on the elementary pn $\rightarrow$np process. The calculated cross-sections for the $^{12}$C($^3$He,t) reaction at $2^o$ to $7^o$ triton emission angle are compared with the corresponding experimental data, and are found in reasonable overall accord.Comment: 19 pages, latex, 11 postscript figures available at [email protected], submitted to Phy.Rev.

The future of hybrid imaging—part 1: hybrid imaging technologies and SPECT/CT

Since the 1990s, hybrid imaging by means of software and hardware image fusion alike allows the intrinsic combination of functional and anatomical image information. This review summarises in three parts the state-of-the-art of dual-technique imaging, with a focus on clinical applications. We will attempt to highlight selected areas of potential improvement of combined imaging technologies and new applications. In this first part, we briefly review the origins of hybrid imaging and comment on the status and future development of single photon emission tomography (SPECT)/computed tomography (CT). In short, we could predict that, within 10 years, we may see all existing dual-technique imaging systems, including SPECT/CT, in clinical routine use worldwide. SPECT/CT, in particular, may evolve into a whole-body imaging technique with supplementary use in dosimetry applications

Cognitive loading affects motor awareness and movement kinematics but not locomotor trajectories during goal-directed walking in a virtual reality environment.

The primary purpose of this study was to investigate the effects of cognitive loading on movement kinematics and trajectory formation during goal-directed walking in a virtual reality (VR) environment. The secondary objective was to measure how participants corrected their trajectories for perturbed feedback and how participants' awareness of such perturbations changed under cognitive loading. We asked 14 healthy young adults to walk towards four different target locations in a VR environment while their movements were tracked and played back in real-time on a large projection screen. In 75% of all trials we introduced angular deviations of ±5° to ±30° between the veridical walking trajectory and the visual feedback. Participants performed a second experimental block under cognitive load (serial-7 subtraction, counter-balanced across participants). We measured walking kinematics (joint-angles, velocity profiles) and motor performance (end-point-compensation, trajectory-deviations). Motor awareness was determined by asking participants to rate the veracity of the feedback after every trial. In-line with previous findings in natural settings, participants displayed stereotypical walking trajectories in a VR environment. Our results extend these findings as they demonstrate that taxing cognitive resources did not affect trajectory formation and deviations although it interfered with the participants' movement kinematics, in particular walking velocity. Additionally, we report that motor awareness was selectively impaired by the secondary task in trials with high perceptual uncertainty. Compared with data on eye and arm movements our findings lend support to the hypothesis that the central nervous system (CNS) uses common mechanisms to govern goal-directed movements, including locomotion. We discuss our results with respect to the use of VR methods in gait control and rehabilitation

Integration of decision support systems to improve decision support performance

Decision support system (DSS) is a well-established research and development area. Traditional isolated, stand-alone DSS has been recently facing new challenges. In order to improve the performance of DSS to meet the challenges, research has been actively carried out to develop integrated decision support systems (IDSS). This paper reviews the current research efforts with regard to the development of IDSS. The focus of the paper is on the integration aspect for IDSS through multiple perspectives, and the technologies that support this integration. More than 100 papers and software systems are discussed. Current research efforts and the development status of IDSS are explained, compared and classified. In addition, future trends and challenges in integration are outlined. The paper concludes that by addressing integration, better support will be provided to decision makers, with the expectation of both better decisions and improved decision making processes

Mesenchymal stromal-cell transplants induce oligodendrocyte progenitor migration and remyelination in a chronic demyelination model.

Demyelinating disorders such as leukodystrophies and multiple sclerosis are neurodegenerative diseases characterized by the progressive loss of myelin that may lead toward a chronic demyelination of the brain¿s white matter, impairing normal axonal conduction velocity and ultimately causing neurodegeneration. Current treatments modifying the pathological mechanisms are capable of ameliorating the disease; however, frequently, these therapies are not sufficient to repress the progressive demyelination into a chronic condition and permanent loss of function. To this end, we analyzed the effect that bone marrowderived mesenchymal stromal cell (BM-MSC) grafts exert in a chronically demyelinated mouse brain. As a result, oligodendrocyte progenitors were recruited surrounding the graft due to the expression of various trophic signals by the grafted MSCs. Although there was no significant reaction in the non-grafted side, in the grafted regions oligodendrocyte progenitors were detected. These progenitors were derived from the nearby tissue as well as from the neurogenic niches, including the subependymal zone and dentate gyrus. Once near the graft site, the cells matured to myelinating oligodendrocytes. Finally, electrophysiological studies demonstrated that axonal conduction velocity was significantly increased in the grafted side of the fimbria. In conclusion, we demonstrate here that in chronic demyelinated white matter, BM-MSC transplantation activates oligodendrocyte progenitors and induces remyelination in the tissue surrounding the stem cell graft

Estimation of Relevant Variables on High-Dimensional Biological Patterns Using Iterated Weighted Kernel Functions

BACKGROUND The analysis of complex proteomic and genomic profiles involves the identification of significant markers within a set of hundreds or even thousands of variables that represent a high-dimensional problem space. The occurrence of noise, redundancy or combinatorial interactions in the profile makes the selection of relevant variables harder. METHODOLOGY/PRINCIPAL FINDINGS Here we propose a method to select variables based on estimated relevance to hidden patterns. Our method combines a weighted-kernel discriminant with an iterative stochastic probability estimation algorithm to discover the relevance distribution over the set of variables. We verified the ability of our method to select predefined relevant variables in synthetic proteome-like data and then assessed its performance on biological high-dimensional problems. Experiments were run on serum proteomic datasets of infectious diseases. The resulting variable subsets achieved classification accuracies of 99% on Human African Trypanosomiasis, 91% on Tuberculosis, and 91% on Malaria serum proteomic profiles with fewer than 20% of variables selected. Our method scaled-up to dimensionalities of much higher orders of magnitude as shown with gene expression microarray datasets in which we obtained classification accuracies close to 90% with fewer than 1% of the total number of variables. CONCLUSIONS Our method consistently found relevant variables attaining high classification accuracies across synthetic and biological datasets. Notably, it yielded very compact subsets compared to the original number of variables, which should simplify downstream biological experimentation

Intuition: Myth or a Decision-making Tool?

Faced with today’s ill-structured business environment of fast-paced change and rising uncertainty, organizations have been searching for management tools that will perform satisfactorily under such ambiguous conditions. In the arena of managerial decision making, one of the approaches being assessed is the use of intuition. Based on our definition of intuition as a non-sequential information-processing mode, which comprises both cognitive and affective elements and results in direct knowing without any use of conscious reasoning, we develop a testable model of integrated analytical and intuitive decision making and propose ways to measure the use of intuition

Disrupted habenula function in major depression.

The habenula is a small, evolutionarily conserved brain structure that plays a central role in aversive processing and is hypothesised to be hyperactive in depression, contributing to the generation of symptoms such as anhedonia. However, habenula responses during aversive processing have yet to be reported in individuals with major depressive disorder (MDD). Unmedicated and currently depressed MDD patients (N=25, aged 18-52 years) and healthy volunteers (N=25, aged 19-52 years) completed a passive (Pavlovian) conditioning task with appetitive (monetary gain) and aversive (monetary loss and electric shock) outcomes during high-resolution functional magnetic resonance imaging; data were analysed using computational modelling. Arterial spin labelling was used to index resting-state perfusion and high-resolution anatomical images were used to assess habenula volume. In healthy volunteers, habenula activation increased as conditioned stimuli (CSs) became more strongly associated with electric shocks. This pattern was significantly different in MDD subjects, for whom habenula activation decreased significantly with increasing association between CSs and electric shocks. Individual differences in habenula volume were negatively associated with symptoms of anhedonia across both groups. MDD subjects exhibited abnormal negative task-related (phasic) habenula responses during primary aversive conditioning. The direction of this effect is opposite to that predicted by contemporary theoretical accounts of depression based on findings in animal models. We speculate that the negative habenula responses we observed may result in the loss of the capacity to actively avoid negative cues in MDD, which could lead to excessive negative focus