Thermal resonance in signal transmission

We use temperature tuning to control signal propagation in simple one-dimensional arrays of masses connected by hard anharmonic springs and with no local potentials. In our numerical model a sustained signal is applied at one site of a chain immersed in a thermal environment and the signal-to-noise ratio is measured at each oscillator. We show that raising the temperature can lead to enhanced signal propagation along the chain, resulting in thermal resonance effects akin to the resonance observed in arrays of bistable systems.

Effects of anomalous propagation conditions on weather radar observations

In this chapter our objective is to provide an overview of the effects of anomalous propagation conditions on weather radar observations, based mostly on studies performed by the authors during the last decade, summarizing results from recent publications, presentations, or unpublished material. We believe this chapter may be useful as an introductory text for graduate students, or researchers and practitioners dealing with this topic. Throughout the text a spherical symmetric atmosphere is assumed and the focus is on the occurrence of ground and sea clutter and subsequent problems for weather radar applications. Other related topics such as long-path, over-the-horizon propagation and detection of radar targets (either clutter or weather systems) at long ranges is not considered here; however readers should be aware of the potential problems these phenomena may have as range aliasing may cause these echoes appear nearer than they are ¿ for more details see the discussion about second trip echoes by Zrnic, this volume.

Nuclear magnetic resonance

This article reviews the principles and methods of nuclear magnetic resonance spectroscopy, and gives examples of applications carried out at ourFacility, which illustrate the capabilities of the technique.

Anomalous crystallization of hydrogenated amorphous silicon during fast heating ramps

Thermal crystallization experiments carried out using calorimetry on several a-Si:H materials with different microstructures are reported. The samples were crystallized during heating ramps at constant heating rates up to 100 K/min. Under these conditions, crystallization takes place above 700 C and progressively deviates from the standard kinetics. In particular, two crystallization processes were detected in conventional a-Si:H, which reveal an enhancement of the crystallization rate. At100 K/min, such enhancement is consistent with a diminution of the crystallization time by a factor of 7. In contrast, no systematic variation of the resulting grain size was observed. Similar behavior was also detected in polymorphous silicon and silicon nanoparticles, thus showing that it is characteristic of a variety of hydrogenated amorphous silicon materials

Stochastic resonance in a dipole

We show that the dipole, a system usually proposed to model relaxation phenomena, exhibits a maximum in the signal-to-noise ratio at a nonzero noise level, thus indicating the appearance of stochastic resonance. The phenomenon occurs in two different situations, i.e., when the minimum of the potential of the dipole remains fixed in time and when it switches periodically between two equilibrium points. We have also found that the signal-to-noise ratio has a maximum for a certain value of the amplitude of the oscillating field.

Controlling anomalous stresses in soft field-responsive systems

We report a phenomenon occurring in field-responsive suspensions: shear-induced anomalous stresses. Competition between a rotating field and a shear flow originates a multiplicity of anomalous stress behaviors in suspensions of bound dimers constituted by induced dipoles. The great variety of stress regimes includes nonmonotonic behaviors, multiresonances, negative viscosity effect, and blockades. The reversibility of the transitions between the different regimes and the self-similarity of the stresses make this phenomenon controllable and therefore applicable to modify macroscopic properties of soft condensed matter phases.

Entropic stochastic resonance

We present a novel scheme for the appearance of stochastic resonance when the dynamics of a Brownian particle takes place in a confined medium. The presence of uneven boundaries, giving rise to an entropic contribution to the potential, may upon application of a periodic driving force result in an increase of the spectral amplification at an optimum value of the ambient noise level. The entropic stochastic resonance, characteristic of small-scale systems, may constitute a useful mechanism for the manipulation and control of single molecules and nanodevices.

Endorectal Magnetic Resonance Imaging and Spectroscopy Are Useful for Selecting Candidates for Biopsy among Patients with Persistently Elevated Prostate Specific Antigen

To evaluate the efficacy of endorectal Magnetic Resonance Imaging (MRI) and Magnetic Resonance Spetroscopic Imaging (MRSI) combined with total prostate-specific antigen (tPSA) and free prostate-specific antigen (fPSA) in selecting candidates for biopsy. Subjects and Methods: 246 patients with elevated tPSA (median: 7.81 ng/ml) underwent endorectal MRI and MRSI before Transrectal Ultrasound (TRUS) biopsy (10 peripheral + 2 central cores); patients with positive biopsies were treated with radical intention; those with negative biopsies were followed up and underwent MRSI before each additional biopsy if tPSA rose persistently. Mean follow-up: 27.6 months. We compared MRI, MRSI, tPSA, and fPSA with histopathology by sextant and determined the association between the Gleason score and MRI and MRSI. We determined the most accurate combination to detect prostate cancer (PCa) using receiver operating curves; we estimated the odds ratios (OR) and calculated sensitivity, specificity, and positive and negative predictive values. Results: No difference in tPSA was found between patients with and without PCa (p = 0.551). In the peripheral zone, the risk of PCa increased with MRSI grade; patients with high-grade MRSI had the greatest risk of PCa over time (OR = 328.6); the model including MRI, MRSI, tPSA, and fPSA was more accurate (Area under Curve: AUC = 95.7%) than MRI alone (AUC = 85.1%) or fPSA alone (AUC = 78.1%), but not than MRSI alone (94.5%). In the transitional zone, the model was less accurate (AUC = 84.4%). The association (p = 0.005) between MRSI and Gleason score was significant in both zones. Conclusions: MRSI is useful in patients with elevated tPSA. High-grade MRSI lesions call for repeated biopsies. Men with negative MRSI may forgo further biopsies because a significantly high Gleason lesion is very unlikely

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.

Dynamic model of the left ventricle for use in simulation of myocardial perfusion SPECT and gated SPECT

Simulation is a useful tool in cardiac SPECT to assess quantification algorithms. However, simple equation-based models are limited in their ability to simulate realistic heart motion and perfusion. We present a numerical dynamic model of the left ventricle, which allows us to simulate normal and anomalous cardiac cycles, as well as perfusion defects. Bicubic splines were fitted to a number of control points to represent endocardial and epicardial surfaces of the left ventricle. A transformation from each point on the surface to a template of activity was made to represent the myocardial perfusion. Geometry-based and patient-based simulations were performed to illustrate this model. Geometry-based simulations modeled ~1! a normal patient, ~2! a well-perfused patient with abnormal regional function, ~3! an ischaemic patient with abnormal regional function, and ~4! a patient study including tracer kinetics. Patient-based simulation consisted of a left ventricle including a realistic shape and motion obtained from a magnetic resonance study. We conclude that this model has the potential to study the influence of several physical parameters and the left ventricle contraction in myocardial perfusion SPECT and gated-SPECT studies.

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.

Anomalous optical and electrical recovery process of photoquenched EL2 defect produced by oxygen and boron ion implantation in gallium arsenide

The optical and electrical recovery processes of the metastable state of the EL2 defect artificially created in n‐type GaAs by boron or oxygen implantation are analyzed at 80 K using optical isothermal transient spectroscopy. In both cases, we have found an inhibition of the electrical recovery and the existence of an optical recovery in the range 1.1-1.4 eV, competing with the photoquenching effect. The similar results obtained with both elements and the different behavior observed in comparison with the native EL2 defect has been related to the network damage produced by the implantation process. From the different behavior with the technological process, it can be deduced that the electrical and optical anomalies have a different origin. The electrical inhibition is due to the existence of an interaction between the EL2 defect and other implantation‐created defects. However, the optical recovery seems to be related to a change in the microscopic metastable state configuration involving the presence of vacancies

Combination of diffusion tensor and functional magnetic resonance imaging during recovery from the vegetative state

Background: The rate of recovery from the vegetative state (VS) is low. Currently, little is known of the mechanisms and cerebral changes that accompany those relatively rare cases of good recovery. Here, we combined functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) to study the evolution of one VS patient at one month post-ictus and again twelve months later when he had recovered consciousness. Methods fMRI was used to investigate cortical responses to passive language stimulation as well as task-induced deactivations related to the default-mode network. DTI was used to assess the integrity of the global white matter and the arcuate fasciculus. We also performed a neuropsychological assessment at the time of the second MRI examination in order to characterize the profile of cognitive deficits. Results: fMRI analysis revealed anatomically appropriate activation to speech in both the first and the second scans but a reduced pattern of task-induced deactivations in the first scan. In the second scan, following the recovery of consciousness, this pattern became more similar to that classically described for the default-mode network. DTI analysis revealed relative preservation of the arcuate fasciculus and of the global normal-appearing white matter at both time points. The neuropsychological assessment revealed recovery of receptive linguistic functioning by 12-months post-ictus. Conclusions: These results suggest that the combination of different structural and functional imaging modalities may provide a powerful means for assessing the mechanisms involved in the recovery from the VS.

Combination of diffusion tensor and functional magnetic resonance imaging during recovery from the vegetative state

Background: The rate of recovery from the vegetative state (VS) is low. Currently, little is known of the mechanisms and cerebral changes that accompany those relatively rare cases of good recovery. Here, we combined functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) to study the evolution of one VS patient at one month post-ictus and again twelve months later when he had recovered consciousness. Methods fMRI was used to investigate cortical responses to passive language stimulation as well as task-induced deactivations related to the default-mode network. DTI was used to assess the integrity of the global white matter and the arcuate fasciculus. We also performed a neuropsychological assessment at the time of the second MRI examination in order to characterize the profile of cognitive deficits. Results: fMRI analysis revealed anatomically appropriate activation to speech in both the first and the second scans but a reduced pattern of task-induced deactivations in the first scan. In the second scan, following the recovery of consciousness, this pattern became more similar to that classically described for the default-mode network. DTI analysis revealed relative preservation of the arcuate fasciculus and of the global normal-appearing white matter at both time points. The neuropsychological assessment revealed recovery of receptive linguistic functioning by 12-months post-ictus. Conclusions: These results suggest that the combination of different structural and functional imaging modalities may provide a powerful means for assessing the mechanisms involved in the recovery from the VS.

Combination of diffusion tensor and functional magnetic resonance imaging during recovery from the vegetative state

Background: The rate of recovery from the vegetative state (VS) is low. Currently, little is known of the mechanisms and cerebral changes that accompany those relatively rare cases of good recovery. Here, we combined functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) to study the evolution of one VS patient at one month post-ictus and again twelve months later when he had recovered consciousness. Methods fMRI was used to investigate cortical responses to passive language stimulation as well as task-induced deactivations related to the default-mode network. DTI was used to assess the integrity of the global white matter and the arcuate fasciculus. We also performed a neuropsychological assessment at the time of the second MRI examination in order to characterize the profile of cognitive deficits. Results: fMRI analysis revealed anatomically appropriate activation to speech in both the first and the second scans but a reduced pattern of task-induced deactivations in the first scan. In the second scan, following the recovery of consciousness, this pattern became more similar to that classically described for the default-mode network. DTI analysis revealed relative preservation of the arcuate fasciculus and of the global normal-appearing white matter at both time points. The neuropsychological assessment revealed recovery of receptive linguistic functioning by 12-months post-ictus. Conclusions: These results suggest that the combination of different structural and functional imaging modalities may provide a powerful means for assessing the mechanisms involved in the recovery from the VS.