Secondary Microseisms Characterization and Green’s Function Extraction at the Larderello-Travale Geothermal Field (Italy)

Over the past ten years, the cross-correlation of long-time series of ambient seismic noise (ASN) has been widely adopted to extract the surface-wave part of the Green’s Functions (GF). This stochastic procedure relies on the assumption that ASN wave-field is diffuse and stationary. At frequencies <1Hz, the ASN is mainly composed by surface-waves, whose origin is attributed to the sea-wave climate. Consequently, marked directional properties may be observed, which call for accurate investigation about location and temporal evolution of the ASN-sources before attempting any GF retrieval. Within this general context, this thesis is aimed at a thorough investigation about feasibility and robustness of the noise-based methods toward the imaging of complex geological structures at the local (∼10-50km) scale. The study focused on the analysis of an extended (11 months) seismological data set collected at the Larderello-Travale geothermal field (Italy), an area for which the underground geological structures are well-constrained thanks to decades of geothermal exploration. Focusing on the secondary microseism band (SM;f>0.1Hz), I first investigate the spectral features and the kinematic properties of the noise wavefield using beamforming analysis, highlighting a marked variability with time and frequency. For the 0.1-0.3Hz frequency band and during Spring- Summer-time, the SMs waves propagate with high apparent velocities and from well-defined directions, likely associated with ocean-storms in the south- ern hemisphere. Conversely, at frequencies >0.3Hz the distribution of back- azimuths is more scattered, thus indicating that this frequency-band is the most appropriate for the application of stochastic techniques. For this latter frequency interval, I tested two correlation-based methods, acting in the time (NCF) and frequency (modified-SPAC) domains, respectively yielding esti- mates of the group- and phase-velocity dispersions. Velocity data provided by the two methods are markedly discordant; comparison with independent geological and geophysical constraints suggests that NCF results are more robust and reliable.

Uncovering the dynamics of cardiac systems using stochastic pacing and frequency domain analyses

Alternans of cardiac action potential duration (APD) is a well-known arrhythmogenic mechanism which results from dynamical instabilities. The propensity to alternans is classically investigated by examining APD restitution and by deriving APD restitution slopes as predictive markers. However, experiments have shown that such markers are not always accurate for the prediction of alternans. Using a mathematical ventricular cell model known to exhibit unstable dynamics of both membrane potential and Ca2+ cycling, we demonstrate that an accurate marker can be obtained by pacing at cycle lengths (CLs) varying randomly around a basic CL (BCL) and by evaluating the transfer function between the time series of CLs and APDs using an autoregressive-moving-average (ARMA) model. The first pole of this transfer function corresponds to the eigenvalue (λalt) of the dominant eigenmode of the cardiac system, which predicts that alternans occurs when λalt≤−1. For different BCLs, control values of λalt were obtained using eigenmode analysis and compared to the first pole of the transfer function estimated using ARMA model fitting in simulations of random pacing protocols. In all versions of the cell model, this pole provided an accurate estimation of λalt. Furthermore, during slow ramp decreases of BCL or simulated drug application, this approach predicted the onset of alternans by extrapolating the time course of the estimated λalt. In conclusion, stochastic pacing and ARMA model identification represents a novel approach to predict alternans without making any assumptions about its ionic mechanisms. It should therefore be applicable experimentally for any type of myocardial cell.

A comparison of ground cover and frequency estimation methods for post-harvest soil monitoring

The amount and type of ground cover is an important characteristic to measure when collecting soil disturbance monitoring data after a timber harvest. Estimates of ground cover and bare soil can be used for tracking changes in invasive species, plant growth and regeneration, woody debris loadings, and the risk of surface water runoff and soil erosion. A new method of assessing ground cover and soil disturbance was recently published by the U.S. Forest Service, the Forest Soil Disturbance Monitoring Protocol (FSDMP). This protocol uses the frequency of cover types in small circular (15cm) plots to compare ground surface in pre- and post-harvest condition. While both frequency and percent cover are common methods of describing vegetation, frequency has rarely been used to measure ground surface cover. In this study, three methods for assessing ground cover percent (step-point, 15cm dia. circular and 1x5m visual plot estimates) were compared to the FSDMP frequency method. Results show that the FSDMP method provides significantly higher estimates of ground surface condition for most soil cover types, except coarse wood. The three cover methods had similar estimates for most cover values. The FSDMP method also produced the highest value when bare soil estimates were used to model erosion risk. In a person-hour analysis, estimating ground cover percent in 15cm dia. plots required the least sampling time, and provided standard errors similar to the other cover estimates even at low sampling intensities (n=18). If ground cover estimates are desired in soil monitoring, then a small plot size (15cm dia. circle), or a step-point method can provide a more accurate estimate in less time than the current FSDMP method.

Four-window technique for measuring optical-phase-space-time-frequency tomography

A new approach, the four-window technique, was developed to measure optical phase-space-time-frequency tomography (OPSTFT). The four-window technique is based on balanced heterodyne detection with two local oscillator (LO) fields. This technique can provide independent control of position, momentum, time and frequency resolution. The OPSTFT is a Wigner distribution function of two independent Fourier transform pairs, phase-space and time-frequency. The OPSTFT can be applied for early disease detection.

Topographic time-frequency decomposition of the EEG

Frequency-transformed EEG resting data has been widely used to describe normal and abnormal brain functional states as function of the spectral power in different frequency bands. This has yielded a series of clinically relevant findings. However, by transforming the EEG into the frequency domain, the initially excellent time resolution of time-domain EEG is lost. The topographic time-frequency decomposition is a novel computerized EEG analysis method that combines previously available techniques from time-domain spatial EEG analysis and time-frequency decomposition of single-channel time series. It yields a new, physiologically and statistically plausible topographic time-frequency representation of human multichannel EEG. The original EEG is accounted by the coefficients of a large set of user defined EEG like time-series, which are optimized for maximal spatial smoothness and minimal norm. These coefficients are then reduced to a small number of model scalp field configurations, which vary in intensity as a function of time and frequency. The result is thus a small number of EEG field configurations, each with a corresponding time-frequency (Wigner) plot. The method has several advantages: It does not assume that the data is composed of orthogonal elements, it does not assume stationarity, it produces topographical maps and it allows to include user-defined, specific EEG elements, such as spike and wave patterns. After a formal introduction of the method, several examples are given, which include artificial data and multichannel EEG during different physiological and pathological conditions.

Indications and Frequency for the Use of Cone Beam Computed Tomography for Implant Treatment Planning in a Specialty Clinic

PURPOSE To analyze the indications and frequency for three-dimensional (3D) imaging for implant treatment planning in a pool of patients referred to a specialty clinic over a 3-year period. MATERIALS AND METHODS All patients who received dental implants between 2008 and 2010 at the Department of Oral Surgery and Stomatology at the University of Bern were included in the study. The influence of age, gender, and time of treatment (2008 to 2010) on the frequency of use of two-dimensional (2D) radiographic imaging modalities alone or in combination with 3D cone beam computed tomography (CBCT) scans was analyzed. Furthermore, the influence of the indication, location, and need for bone augmentation on the frequency of use of 2D imaging modalities alone or in combination with CBCT was evaluated. RESULTS In all, 1,568 patients (792 women and 776 men) received 2,279 implants. Overall, 633 patients (40.4%) were analyzed with 2D imaging procedures alone. CBCT was performed in 935 patients (59.6%). There was a statistically significant increase in CBCT between 2008 and 2010. Patients older than 55 years received a CBCT scan in addition to 2D radiographic imaging statistically significantly more often. Additional 3D imaging was most frequently performed in the posterior maxilla, whereas 2D radiographs alone exhibited the highest frequency in the anterior mandible. The combination of 2D with CBCT was used predominantly for implant placement with simultaneous or staged guided bone regeneration or sinus elevation. CONCLUSION Based on these findings from a specialty clinic, the use of additional CBCT imaging for implant treatment planning is influenced by the indication, location, local anatomy (including the need for bone augmentation), and the age of the patient.

Spicule dimensions of Siphonodictyon spp., raw data, biometry and frequency distributions

Early descriptions for species of Aka were poor in detail, and the only spicule type that occurs in this genus does not vary much between species, which led to taxonomic confusion. Moreover, the type specimens of 5 species of Aka are lost, causing considerable problems. Mediterranean specimens of Aka were identified as Aka labyrinthica (Hancock, 1849) by Topsent (1900), even though this species was originally described from the Indo-Pacific. All following publications on Mediterranean Aka accepted Topsent's decision. We assessed this problem with new samples from the Ionian Sea. Our material consisted of only one specimen of Aka, and we had to rely mainly on spicule characters for comparison to other species. We developed a system for species recognition solely based on spicular characters and biometry, involving a combination of the parameters oxea length, width, tip form and angle of curvature. This approach was surprisingly accurate. Forming ratios of the above parameters was less helpful, but can sometimes provide additional information. We identified our sample as Aka infesta (Johnson, 1899), and describe it as a minute-fistulate species with large, multicamerate erosion traces and stout, smooth oxeas. Our data further imply that A. labyrinthica sensu Hancock has not yet been found in the Mediterranean. A. labyrinthica sensu Topsent is a collection of different species not including A. labyrinthica sensu Hancock.

Time-frequency characterization of a sound propagation channel as an educational tool

This paper discusses the use of sound waves to illustrate multipath radio propagation concepts. Specifically, a procedure is presented to measure the time-varying frequency response of the channel. This helps demonstrate how a propagation channel can be characterized in time and frequency, and provides visualizations of the concepts of coherence time and coherence bandwidth. The measurements are very simple to carry out, and the required equipment is easily available. The proposed method can be useful for wireless or mobile communication courses.

Time and space partition platform for safe and secure flight software.

There are a number of research and development activities that are exploring Time and Space Partition (TSP) to implement safe and secure flight software. This approach allows to execute different real-time applications with different levels of criticality in the same computer board. In order to do that, flight applications must be isolated from each other in the temporal and spatial domains. This paper presents the first results of a partitioning platform based on the Open Ravenscar Kernel (ORK+) and the XtratuM hypervisor. ORK+ is a small, reliable real-time kernel supporting the Ada Ravenscar Computational model that is central to the ASSERT development process. XtratuM supports multiple virtual machines, i.e. partitions, on a single computer and is being used in the Integrated Modular Avionics for Space study. ORK+ executes in an XtratuM partition enabling Ada applications to share the computer board with other applications.

Independent mobility of catalytic and regulatory domains of myosin heads

The recent determination of the myosin head atomic structure has led to a new model of muscle contraction, according to which mechanical torque is generated in the catalytic domain and amplified by the lever arm made of the regulatory domain [Fisher, A. J., Smith, C. A., Thoden, J., Smith, R., Sutoh, K., Holden, H. M. & Rayment, I. (1995) Biochemistry 34, 8960–8972]. A crucial aspect of this model is the ability of the regulatory domain to move independently of the catalytic domain. Saturation transfer–EPR measurements of mobility of these two domains in myosin filaments give strong support for this notion. The catalytic domain of the myosin head was labeled at Cys-707 with indane dione spin label; the regulatory domain was labeled at the single cysteine residue of the essential light chain and exchanged into myosin. The mobility of the regulatory domain in myosin filaments was characterized by an effective rotational correlation time (τR) between 24 and 48 μs. In contrast, the mobility of the catalytic domain was found to be τR = 5–9 μs. This difference in mobility between the two domains existed only in the filament form of myosin. In the monomeric form, or when bound to actin, the mobility of the two domains in myosin was indistinguishable, with τR = 1–4 μs and >1,000 μs, respectively. Therefore, the observed difference in filaments cannot be ascribed to differences in local conformations of the spin-labeled sites. The most straightforward interpretation suggests a flexible hinge between the two domains, which would have to stiffen before force could be generated.

Voltage dependence of the pattern and frequency of discrete Ca2+ release events after brief repriming in frog skeletal muscle

Applying a brief repolarizing pre-pulse to a depolarized frog skeletal muscle fiber restores a small fraction of the transverse tubule membrane voltage sensors from the inactivated state. During a subsequent depolarizing test pulse we detected brief, highly localized elevations of myoplasmic Ca2+ concentration (Ca2+ “sparks”) initiated by restored voltage sensors in individual triads at all test pulse voltages. The latency histogram of these events gives the gating pattern of the sarcoplasmic reticulum (SR) calcium release channels controlled by the restored voltage sensors. Both event frequency and clustering of events near the start of the test pulse increase with test pulse depolarization. The macroscopic SR calcium release waveform, obtained from the spark latency histogram and the estimated open time of the channel or channels underlying a spark, exhibits an early peak and rapid marked decline during large depolarizations. For smaller depolarizations, the release waveform exhibits a smaller peak and a slower decline. However, the mean use time and mean amplitude of the individual sparks are quite similar at all test depolarizations and at all times during a given depolarization, indicating that the channel open times and conductances underlying sparks are essentially independent of voltage. Thus, the voltage dependence of SR Ca2+ release is due to changes in the frequency and pattern of occurrence of individual, voltage-independent, discrete release events.

Investigation of neural correlates of faces and emotional expressions using magnetoencephalography

The recognition of faces and of facial expressions in an important evolutionary skill, and an integral part of social communication. It has been argued that the processing of faces is distinct from the processing of non-face stimuli and functional neuroimaging investigations have even found evidence of a distinction between the perception of faces and of emotional expressions. Structural and temporal correlates of face perception and facial affect have only been separately identified. Investigation neural dynamics of face perception per se as well as facial affect would allow the mapping of these in space, time and frequency specific domains. Participants were asked to perform face categorisation and emotional discrimination tasks and Magnetoencephalography (MEG) was used to measure the neurophysiology of face and facial emotion processing. SAM analysis techniques enable the investigation of spectral changes within specific time-windows and frequency bands, thus allowing the identification of stimulus specific regions of cortical power changes. Furthermore, MEG’s excellent temporal resolution allows for the detection of subtle changes associated with the processing of face and non-face stimuli and different emotional expressions. The data presented reveal that face perception is associated with spectral power changes within a distributed cortical network comprising occipito-temporal as well as parietal and frontal areas. For the perception of facial affect, spectral power changes were also observed within frontal and limbic areas including the parahippocampal gyrus and the amygdala. Analyses of temporal correlates also reveal a distinction between the processing of faces and facial affect. Face perception per se occurred at earlier latencies whereas the discrimination of facial expression occurred within a longer time-window. In addition, the processing of faces and facial affect was differentially associated with changes in cortical oscillatory power for alpha, beta and gamma frequencies. The perception of faces and facial affect is associated with distinct changes in cortical oscillatory activity that can be mapped to specific neural structures, specific time-windows and latencies as well as specific frequency bands. Therefore, the work presented in this thesis provides further insight into the sequential processing of faces and facial affect.