Microscopic calculations of the excitation spectrum of one 3He impurity in liquid 4He

We calculate the chemical potential ¿0 and the effective mass m*/m3 of one 3He impurity in liquid 4He. First a variational wave function including two- and three-particle dynamical correlations is adopted. Triplet correlations bring the computed values of ¿0 very close to the experimental results. The variational estimate of m*/m3 includes also backflow correlations between the 3He atom and the particles in the medium. Different approximations for the three-particle distribution function give almost the same values for m*/m3. The variational approach underestimates m*/m3 by ~10% at all of the considered densities. Correlated-basis perturbation theory is then used to improve the wave function to include backflow around the particles of the medium. The perturbative series built up with one-phonon states only is summed up to infinite order and gives results very close to the variational ones. All the perturbative diagrams with two independent phonons have then been summed to compute m*/m3. Their contribution depends to some extent on the form used for the three-particle distribution function. When the scaling approximation is adopted, a reasonable agreement with the experimental results is achieved.

On-axis joint transform correlation based on a four-level power spectrum

We propose a method to obtain a single centered correlation with use of a joint transform correlator. We analyze the required setup to carry out the whole process optically, and we also present experimental results.

Photon spectrum produced by the late decay of a cosmic neutrino background

We obtain the photon spectrum induced by a cosmic background of unstable neutrinos. We study the spectrum in a variety of cosmological scenarios and also we allow for the neutrinos having a momentum distribution (only a critical matter-dominated universe and neutrinos at rest have been considered until now). Our results can be helpful when extracting bounds on neutrino electric and magnetic moments from cosmic photon background observations.

Spectrum of gluten sensitive enteropathy in first degree relatives of patients with coeliac disease: clinical relevance of lymphocytic enteritis.

Background: Limited data on a short series of patients suggest that lymphocytic enteritis (classically considered as latent coeliac disease) may produce symptoms of malabsorption, although the true prevalence of this situation is unknown. Serological markers of coeliac disease are of little diagnostic value in identifying these patients. Aims: To evaluate the usefulness of human leucocyte antigen-DQ2 genotyping followed by duodenal biopsy for the detection of gluten-sensitive enteropathy in first-degree relatives of patients with coeliac disease and to assess the clinical relevance of lymphocytic enteritis diagnosed with this screening strategy. Patients and methods: 221 first-degree relatives of 82 DQ2+ patients with coeliac disease were consecutively included. Duodenal biopsy (for histological examination and tissue transglutaminase antibody assay in culture supernatant) was carried out on all DQ2+ relatives. Clinical features, biochemical parameters and bone mineral density were recorded. Results: 130 relatives (58.8%) were DQ2+, showing the following histological stages: 64 (49.2%) Marsh 0; 32 (24.6%) Marsh I; 1 (0.8%) Marsh II; 13 (10.0%) Marsh III; 15.4% refused the biopsy. 49 relatives showed gluten sensitive enteropathy, 46 with histological abnormalities and 3 with Marsh 0 but positive tissue transglutaminase antibody in culture supernatant. Only 17 of 221 relatives had positive serological markers. Differences in the diagnostic yield between the proposed strategy and serology were significant (22.2% v 7.2%, p<0.001). Relatives with Marsh I and Marsh II¿III were more often symptomatic (56.3% and 53.8%, respectively) than relatives with normal mucosa (21.1%; p=0.002). Marsh I relatives had more severe abdominal pain (p=0.006), severe distension (p=0.047) and anaemia (p=0.038) than those with Marsh 0. The prevalence of abnormal bone mineral density was similar in relatives with Marsh I (37%) and Marsh III (44.4%). Conclusions: The high number of symptomatic patients with lymphocytic enteritis (Marsh I) supports the need for a strategy based on human leucocyte antigen-DQ2 genotyping followed by duodenal biopsy in relatives of patients with coeliac disease and modifies the current concept that villous atrophy is required to prescribe a gluten-free diet.

Training referential communicative skills to individuals with autism spectrum disorder: a pilot study

Summary. The present study reports the effects of referential communication training in individuals formally diagnosed with autism spectrum disorder (ASD). Participants were 20 children with ASD (M age = 14.3 yr., SD = 4.2; 6 girls, 14 boys) in the role of speakers and 20 control children, who acted as listeners. They were all enrolled in mainstream compulsory education. Inclusion/exclusion criteria were defined according to the clinical diagnosis of ASD, the presence or absence of additional or associated disability, previous training in referential communication, and any drug treatment. Speakers were randomly assigned to one of two groups (trained vs untrained). Linguistic age, cognitive level, and autistic symptoms were analyzed, respectively, with the Peabody Picture Vocabulary Test (PPVT), the Wechsler Intelligence Scale (WISCR or WAISIII), and the Autistic Behavior Checklist (ABC). Communicative abilities were analyzed through two indexes related to message complexity and self-regulation. The trained group was trained in referential communication tasks (task analysis, role taking, and task evaluation), while the untrained group took part in a communicative game but without any specific communicative training. The results showed that the complexity of emitted messages had improved statistically significantly in the trained group as an effect of training. Ecological referential communication is shown to be an appropriate paradigm for studying the communicative process and its products and could be used to develop and implement a training program focused on those skills in which individuals with ASD are most deficient.

Identification of neuronal network properties from the spectral analysis of calcium imaging signals in neuronal cultures

Neuronal networks in vitro are prominent systems to study the development of connections in living neuronal networks and the interplay between connectivity, activity and function. These cultured networks show a rich spontaneous activity that evolves concurrently with the connectivity of the underlying network. In this work we monitor the development of neuronal cultures, and record their activity using calcium fluorescence imaging. We use spectral analysis to characterize global dynamical and structural traits of the neuronal cultures. We first observe that the power spectrum can be used as a signature of the state of the network, for instance when inhibition is active or silent, as well as a measure of the network's connectivity strength. Second, the power spectrum identifies prominent developmental changes in the network such as GABAA switch. And third, the analysis of the spatial distribution of the spectral density, in experiments with a controlled disintegration of the network through CNQX, an AMPA-glutamate receptor antagonist in excitatory neurons, reveals the existence of communities of strongly connected, highly active neurons that display synchronous oscillations. Our work illustrates the interest of spectral analysis for the study of in vitro networks, and its potential use as a network-state indicator, for instance to compare healthy and diseased neuronal networks.

Fully Distributed Cooperative Spectrum Sensing for Cognitive Radio Networks

Cognitive radio networks (CRN) sense spectrum occupancy and manage themselves to operate in unused bands without disturbing licensed users. The detection capability of a radio system can be enhanced if the sensing process is performed jointly by a group of nodes so that the effects of wireless fading and shadowing can be minimized. However, taking a collaborative approach poses new security threats to the system as nodes can report false sensing data to force a wrong decision. Providing security to the sensing process is also complex, as it usually involves introducing limitations to the CRN applications. The most common limitation is the need for a static trusted node that is able to authenticate and merge the reports of all CRN nodes. This paper overcomes this limitation by presenting a protocol that is suitable for fully distributed scenarios, where there is no static trusted node.

Spectrum Sharing Models in Cognitive Radio

Spectrum scarcity demands thinking new ways tomanage the distribution of radio frequency bands so that its use is more effective. The emerging technology that can enable this paradigm shift is the cognitive radio. Different models fororganizing and managing cognitive radios have emerged, all with specific strategic purposes. In this article we review the allocation spectrum patterns of cognitive radio networks andanalyse which are the common basis of each model.We expose the vulnerabilities and open challenges that still threaten the adoptionand exploitation of cognitive radios for open civil networks.

Self-Organising Maps and Correlation Analysis as a Tool to Explore Patterns in Excitation-Emission Matrix Data Sets and to Discriminate Dissolved Organic Matter Fluorescence Components

Dissolved organic matter (DOM) is a complex mixture of organic compounds, ubiquitous in marine and freshwater systems. Fluorescence spectroscopy, by means of Excitation-Emission Matrices (EEM), has become an indispensable tool to study DOM sources, transport and fate in aquatic ecosystems. However the statistical treatment of large and heterogeneous EEM data sets still represents an important challenge for biogeochemists. Recently, Self-Organising Maps (SOM) has been proposed as a tool to explore patterns in large EEM data sets. SOM is a pattern recognition method which clusterizes and reduces the dimensionality of input EEMs without relying on any assumption about the data structure. In this paper, we show how SOM, coupled with a correlation analysis of the component planes, can be used both to explore patterns among samples, as well as to identify individual fluorescence components. We analysed a large and heterogeneous EEM data set, including samples from a river catchment collected under a range of hydrological conditions, along a 60-km downstream gradient, and under the influence of different degrees of anthropogenic impact. According to our results, chemical industry effluents appeared to have unique and distinctive spectral characteristics. On the other hand, river samples collected under flash flood conditions showed homogeneous EEM shapes. The correlation analysis of the component planes suggested the presence of four fluorescence components, consistent with DOM components previously described in the literature. A remarkable strength of this methodology was that outlier samples appeared naturally integrated in the analysis. We conclude that SOM coupled with a correlation analysis procedure is a promising tool for studying large and heterogeneous EEM data sets.

Conditional equilibrium constants in multicomponent heterogeneous adsorption: The conditional affinity spectrum

The concept of conditional stability constant is extended to the competitive binding of small molecules to heterogeneous surfaces or macromolecules via the introduction of the conditional affinity spectrum (CAS). The CAS describes the distribution of effective binding energies experienced by one complexing agent at a fixed concentration of the rest. We show that, when the multicomponent system can be described in terms of an underlying affinity spectrum [integral equation (IE) approach], the system can always be characterized by means of a CAS. The thermodynamic properties of the CAS and its dependence on the concentration of the rest of components are discussed. In the context of metal/proton competition, analytical expressions for the mean (conditional average affinity) and the variance (conditional heterogeneity) of the CAS as functions of pH are reported and their physical interpretation discussed. Furthermore, we show that the dependence of the CAS variance on pH allows for the analytical determination of the correlation coefficient between the binding energies of the metal and the proton. Nonideal competitive adsorption isotherm and Frumkin isotherms are used to illustrate the results of this work. Finally, the possibility of using CAS when the IE approach does not apply (for instance, when multidentate binding is present) is explored. © 2006 American Institute of Physics.

Technical Note: Dissolved organic matter fluorescence a finite mixture approach to deconvolve excitation-emission matrices

The analysis of the shape of excitation-emission matrices (EEMs) is a relevant tool for exploring the origin, transport and fate of dissolved organic matter (DOM) in aquatic ecosystems. Within this context, the decomposition of EEMs is acquiring a notable relevance. A simple mathematical algorithm that automatically deconvolves individual EEMs is described, creating new possibilities for the comparison of DOM fluorescence properties and EEMs that are very different from each other. A mixture model approach is adopted to decompose complex surfaces into sub-peaks. The laplacian operator and the Nelder-Mead optimisation algorithm are implemented to individuate and automatically locate potential peaks in the EEM landscape. The EEMs of a simple artificial mixture of fluorophores and DOM samples collected in a Mediterranean river are used to describe the model application and to illustrate a strategy that optimises the search for the optimal output.

Identification of neuronal network properties from the spectral analysis of calcium imaging signals in neuronal cultures

Neuronal networks in vitro are prominent systems to study the development of connections in living neuronal networks and the interplay between connectivity, activity and function. These cultured networks show a rich spontaneous activity that evolves concurrently with the connectivity of the underlying network. In this work we monitor the development of neuronal cultures, and record their activity using calcium fluorescence imaging. We use spectral analysis to characterize global dynamical and structural traits of the neuronal cultures. We first observe that the power spectrum can be used as a signature of the state of the network, for instance when inhibition is active or silent, as well as a measure of the network's connectivity strength. Second, the power spectrum identifies prominent developmental changes in the network such as GABAA switch. And third, the analysis of the spatial distribution of the spectral density, in experiments with a controlled disintegration of the network through CNQX, an AMPA-glutamate receptor antagonist in excitatory neurons, reveals the existence of communities of strongly connected, highly active neurons that display synchronous oscillations. Our work illustrates the interest of spectral analysis for the study of in vitro networks, and its potential use as a network-state indicator, for instance to compare healthy and diseased neuronal networks.

Self-Organising Maps and Correlation Analysis as a Tool to Explore Patterns in Excitation-Emission Matrix Data Sets and to Discriminate Dissolved Organic Matter Fluorescence Components

Dissolved organic matter (DOM) is a complex mixture of organic compounds, ubiquitous in marine and freshwater systems. Fluorescence spectroscopy, by means of Excitation-Emission Matrices (EEM), has become an indispensable tool to study DOM sources, transport and fate in aquatic ecosystems. However the statistical treatment of large and heterogeneous EEM data sets still represents an important challenge for biogeochemists. Recently, Self-Organising Maps (SOM) has been proposed as a tool to explore patterns in large EEM data sets. SOM is a pattern recognition method which clusterizes and reduces the dimensionality of input EEMs without relying on any assumption about the data structure. In this paper, we show how SOM, coupled with a correlation analysis of the component planes, can be used both to explore patterns among samples, as well as to identify individual fluorescence components. We analysed a large and heterogeneous EEM data set, including samples from a river catchment collected under a range of hydrological conditions, along a 60-km downstream gradient, and under the influence of different degrees of anthropogenic impact. According to our results, chemical industry effluents appeared to have unique and distinctive spectral characteristics. On the other hand, river samples collected under flash flood conditions showed homogeneous EEM shapes. The correlation analysis of the component planes suggested the presence of four fluorescence components, consistent with DOM components previously described in the literature. A remarkable strength of this methodology was that outlier samples appeared naturally integrated in the analysis. We conclude that SOM coupled with a correlation analysis procedure is a promising tool for studying large and heterogeneous EEM data sets.

On the multiwavelength spectrum of the microquasar 1E1740.7-2942

The microquasar 1E 1740.7-2942 is a source located in the direction of the Galactic Center. It has been detected at X-rays, soft gamma-rays, and in the radio band, showing an extended radio component in the form of a double-sided jet. Although no optical counterpart has been found so far for 1E 1740.7-2942, its X-ray activity strongly points to a galactic nature. Aims.We aim to improve our understanding of the hard X-ray and gamma-ray production in the system, exploring whether the jet can emit significantly at high energies under the light of the present knowledge. Methods.We have modeled the source emission, from radio to gamma-rays, with a cold-matter dominated jet model. INTEGRAL data combined with radio and RXTE data, as well as EGRET and HESS upper-limits, are used to compare the computed and the observed spectra. Results.From our modeling, we find out that jet emission cannot explain the high fluxes observed at hard X-rays without violating at the same time the constraints from the radio data, favoring the corona origin of the hard X-rays. Also, 1E 1740.7-2942 might be detected by GLAST or AGILE at GeV energies, and by HESS and HESS-II beyond 100 GeV, with the spectral shape likely affected by photon-photon absorption in the disk and corona photon fields.

Two-year follow-op of cognitive functions in Schizophrenia spectrum disorders of adolescent patients treated with electroconvulsive therapy

Objective: The aim of the current study was to investigate the long-term cognitive effects of electroconvulsive therapy (ECT) in a sample of adolescent patients in whom schizophrenia spectrum disorders were diagnosed. Methods: The sample was composed of nine adolescent subjects in whom schizophrenia or schizoaffective disorder was diagnosed according to DSM-IV-TR criteria on whom ECT was conducted (ECT group) and nine adolescent subjects matched by age, socioeconomic status, and diagnostic and Positive and Negative Syndrome Scale (PANSS) total score at baseline on whom ECT was not conducted (NECT group). Clinical and neuropsychological assessments were carried out at baseline before ECT treatment and at 2-year follow-up. Results: Significant differences were found between groups in the number of unsuccessful medication trials. No statistically significant differences were found between the ECT group and theNECT group in either severity as assessed by the PANSS, or in any cognitive variables at baseline.At follow-up, both groups showed significant improvement in clinical variables (subscales of positive, general, and total scores of PANSS and Clinical Global Impressions-Improvement). In the cognitive assessment at follow-up, significant improvement was found in both groups in the semantic category of verbal fluency task and digits forward. However, no significant differences were found between groups in any clinical or cognitive variable at follow-up. Repeated measures analysis found no significant interaction of time · group in any clinical or neuropsychological measures. Conclusions: The current study showed no significant differences in change over time in clinical or neuropsychological variables between the ECT group and the NECT group at 2-year follow-up. Thus, ECT did not show any negative influence on long-term neuropsychological variables in our sample.