Automatic motion compensation of free breathing acquired myocardial perfusion data by using independent component analysis

Images acquired during free breathing using first-pass gadolinium-enhanced myocardial perfusion magnetic resonance imaging (MRI) exhibit a quasiperiodic motion pattern that needs to be compensated for if a further automatic analysis of the perfusion is to be executed. In this work, we present a method to compensate this movement by combining independent component analysis (ICA) and image registration: First, we use ICA and a time?frequency analysis to identify the motion and separate it from the intensity change induced by the contrast agent. Then, synthetic reference images are created by recombining all the independent components but the one related to the motion. Therefore, the resulting image series does not exhibit motion and its images have intensities similar to those of their original counterparts. Motion compensation is then achieved by using a multi-pass image registration procedure. We tested our method on 39 image series acquired from 13 patients, covering the basal, mid and apical areas of the left heart ventricle and consisting of 58 perfusion images each. We validated our method by comparing manually tracked intensity profiles of the myocardial sections to automatically generated ones before and after registration of 13 patient data sets (39 distinct slices). We compared linear, non-linear, and combined ICA based registration approaches and previously published motion compensation schemes. Considering run-time and accuracy, a two-step ICA based motion compensation scheme that first optimizes a translation and then for non-linear transformation performed best and achieves registration of the whole series in 32 ± 12 s on a recent workstation. The proposed scheme improves the Pearsons correlation coefficient between manually and automatically obtained time?intensity curves from .84 ± .19 before registration to .96 ± .06 after registration

Bandlimited Airy Pulses for Invariant Propagation in Single-Mode Fibers

By spectral analysis, and using joint time-frequency representations, we present the theoretical basis to design invariant bandlimited Airy pulses with an arbitrary degree of robustness and an arbitrary range of single-mode fiber chromatic dispersion. The numerically simulated examples confirm the theoretically predicted pulse partial invariance in the propagation of the pulse in the fiber.

Optical digital chaos cryptography

In this work we present a new way to mask the data in a one-user communication system when direct sequence - code division multiple access (DS-CDMA) techniques are used. The code is generated by a digital chaotic generator, originally proposed by us and previously reported for a chaos cryptographic system. It is demonstrated that if the user's data signal is encoded with a bipolar phase-shift keying (BPSK) technique, usual in DS-CDMA, it can be easily recovered from a time-frequency domain representation. To avoid this situation, a new system is presented in which a previous dispersive stage is applied to the data signal. A time-frequency domain analysis is performed, and the devices required at the transmitter and receiver end, both user-independent, are presented for the optical domain.

Electricity price forecasting accounting for renewable energies: optimal combined forecasts

Electricity price forecasting is an interesting problem for all the agents involved in electricity market operation. For instance, every profit maximisation strategy is based on the computation of accurate one-day-ahead forecasts, which is why electricity price forecasting has been a growing field of research in recent years. In addition, the increasing concern about environmental issues has led to a high penetration of renewable energies, particularly wind. In some European countries such as Spain, Germany and Denmark, renewable energy is having a deep impact on the local power markets. In this paper, we propose an optimal model from the perspective of forecasting accuracy, and it consists of a combination of several univariate and multivariate time series methods that account for the amount of energy produced with clean energies, particularly wind and hydro, which are the most relevant renewable energy sources in the Iberian Market. This market is used to illustrate the proposed methodology, as it is one of those markets in which wind power production is more relevant in terms of its percentage of the total demand, but of course our method can be applied to any other liberalised power market. As far as our contribution is concerned, first, the methodology proposed by García-Martos et al(2007 and 2012) is generalised twofold: we allow the incorporation of wind power production and hydro reservoirs, and we do not impose the restriction of using the same model for 24h. A computational experiment and a Design of Experiments (DOE) are performed for this purpose. Then, for those hours in which there are two or more models without statistically significant differences in terms of their forecasting accuracy, a combination of forecasts is proposed by weighting the best models(according to the DOE) and minimising the Mean Absolute Percentage Error (MAPE). The MAPE is the most popular accuracy metric for comparing electricity price forecasting models. We construct the combi nation of forecasts by solving several nonlinear optimisation problems that allow computation of the optimal weights for building the combination of forecasts. The results are obtained by a large computational experiment that entails calculating out-of-sample forecasts for every hour in every day in the period from January 2007 to Decem ber 2009. In addition, to reinforce the value of our methodology, we compare our results with those that appear in recent published works in the field. This comparison shows the superiority of our methodology in terms of forecasting accuracy.

A temperature-based thermodynamically consistent integration scheme for discrete thermo-elastodynamics

The formulation of thermodynamically consistent (TC) time integration methods was introduced by a general procedure based on the GENERIC form of the evolution equations for thermo-mechanical problems. The use of the entropy was reported to be the best choice for the thermodynamical variable to easily provide TC integrators. Also the employment of the internal energy was proved to not involve excessive complications. However, attempts towards the use of the temperature in the design of GENERIC-based TC schemes have so far been unfruitful. This paper complements the said procedure to attain TC integrators by presenting a TC scheme based on the temperature as thermodynamical state variable. As a result, the problems which arise due to the use of the entropy are overcome, mainly the definition of boundary conditions. What is more, the newly proposed method exhibits the general enhanced numerical stability and robustness properties of the entropy formulation.

Proton transport by a bacteriorhodopsin mutant, aspartic acid-85-->asparagine, initiated in the unprotonated Schiff base state.

At alkaline pH the bacteriorhodopsin mutant D85N, with aspartic acid-85 replaced by asparagine, is in a yellow form (lambda max approximately 405 nm) with a deprotonated Schiff base. This state resembles the M intermediate of the wild-type photocycle. We used time-resolved methods to show that this yellow form of D85N, which has an initially unprotonated Schiff base and which lacks the proton acceptor Asp-85, transports protons in the same direction as wild type when excited by 400-nm flashes. Photoexcitation leads in several milliseconds to the formation of blue (630 nm) and purple (580 nm) intermediates with a protonated Schiff base, which decay in tens of seconds to the initial state (400 nm). Experiments with pH indicator dyes show that at pH 7, 8, and 9, proton uptake occurs in about 5-10 ms and precedes the slow release (seconds). Photovoltage measurements reveal that the direction of proton movement is from the cytoplasmic to the extracellular side with major components on the millisecond and second time scales. The slowest electrical component could be observed in the presence of azide, which accelerates the return of the blue intermediate to the initial yellow state. Transport thus occurs in two steps. In the first step (milliseconds), the Schiff base is protonated by proton uptake from the cytoplasmic side, thereby forming the blue state. From the pH dependence of the amplitudes of the electrical and photocycle signals, we conclude that this reaction proceeds in a similar way as in wild type--i.e., via the internal proton donor Asp-96. In the second step (seconds) the Schiff base deprotonates, releasing the proton to the extracellular side.

Human Motion Analysis Based on Sequential Modeling of Radar Signal and Stereo Image Features

Falls are one of the greatest threats to elderly health in their daily living routines and activities. Therefore, it is very important to detect falls of an elderly in a timely and accurate manner, so that immediate response and proper care can be provided, by sending fall alarms to caregivers. Radar is an effective non-intrusive sensing modality which is well suited for this purpose, which can detect human motions in all types of environments, penetrate walls and fabrics, preserve privacy, and is insensitive to lighting conditions. Micro-Doppler features are utilized in radar signal corresponding to human body motions and gait to detect falls using a narrowband pulse-Doppler radar. Human motions cause time-varying Doppler signatures, which are analyzed using time-frequency representations and matching pursuit decomposition (MPD) for feature extraction and fall detection. The extracted features include MPD features and the principal components of the time-frequency signal representations. To analyze the sequential characteristics of typical falls, the extracted features are used for training and testing hidden Markov models (HMM) in different falling scenarios. Experimental results demonstrate that the proposed algorithm and method achieve fast and accurate fall detections. The risk of falls increases sharply when the elderly or patients try to exit beds. Thus, if a bed exit can be detected at an early stage of this motion, the related injuries can be prevented with a high probability. To detect bed exit for fall prevention, the trajectory of head movements is used for recognize such human motion. A head detector is trained using the histogram of oriented gradient (HOG) features of the head and shoulder areas from recorded bed exit images. A data association algorithm is applied on the head detection results to eliminate head detection false alarms. Then the three dimensional (3D) head trajectories are constructed by matching scale-invariant feature transform (SIFT) keypoints in the detected head areas from both the left and right stereo images. The extracted 3D head trajectories are used for training and testing an HMM based classifier for recognizing bed exit activities. The results of the classifier are presented and discussed in the thesis, which demonstrates the effectiveness of the proposed stereo vision based bed exit detection approach.

Towards Closed-loop Deep Brain Stimulation: Behavior Recognition from Human STN

Deep brain stimulation (DBS) provides significant therapeutic benefit for movement disorders such as Parkinson’s disease (PD). Current DBS devices lack real-time feedback (thus are open loop) and stimulation parameters are adjusted during scheduled visits with a clinician. A closed-loop DBS system may reduce power consumption and side effects by adjusting stimulation parameters based on patient’s behavior. Thus behavior detection is a major step in designing such systems. Various physiological signals can be used to recognize the behaviors. Subthalamic Nucleus (STN) Local field Potential (LFP) is a great candidate signal for the neural feedback, because it can be recorded from the stimulation lead and does not require additional sensors. This thesis proposes novel detection and classification techniques for behavior recognition based on deep brain LFP. Behavior detection from such signals is the vital step in developing the next generation of closed-loop DBS devices. LFP recordings from 13 subjects are utilized in this study to design and evaluate our method. Recordings were performed during the surgery and the subjects were asked to perform various behavioral tasks. Various techniques are used understand how the behaviors modulate the STN. One method studies the time-frequency patterns in the STN LFP during the tasks. Another method measures the temporal inter-hemispheric connectivity of the STN as well as the connectivity between STN and Pre-frontal Cortex (PFC). Experimental results demonstrate that different behaviors create different m odulation patterns in STN and it’s connectivity. We use these patterns as features to classify behaviors. A method for single trial recognition of the patient’s current task is proposed. This method uses wavelet coefficients as features and support vector machine (SVM) as the classifier for recognition of a selection of behaviors: speech, motor, and random. The proposed method is 82.4% accurate for the binary classification and 73.2% for classifying three tasks. As the next step, a practical behavior detection method which asynchronously detects behaviors is proposed. This method does not use any priori knowledge of behavior onsets and is capable of asynchronously detect the finger movements of PD patients. Our study indicates that there is a motor-modulated inter-hemispheric connectivity between LFP signals recorded bilaterally from STN. We utilize a non-linear regression method to measure this inter-hemispheric connectivity and to detect the finger movements. Our experimental results using STN LFP recorded from eight patients with PD demonstrate this is a promising approach for behavior detection and developing novel closed-loop DBS systems.

Analysis of Protein Turnover by Quantitative SNAP-Based Pulse-Chase Imaging

Assessment of protein dynamics in living cells is crucial for understanding their biological properties and functions. The SNAP-tag, a self labeling suicide enzyme, presents a tool with unique features that can be adopted for determining protein dynamics in living cells. Here we present detailed protocols for the use of SNAP in fluorescent pulse-chase and quench-chase-pulse experiments. These time-slicing methods provide powerful tools to assay and quantify the fate and turnover rate of proteins of different ages. We cover advantages and pitfalls of SNAP-tagging in fixed- and live-cell studies and evaluate the recently developed fast-acting SNAPf variant. In addition, to facilitate the analysis of protein turnover datasets, we present an automated algorithm for spot recognition and quantification.

Identification of differentially expressed genes in a Giardia lamblia WB C6 clone resistant to nitazoxanide and metronidazole.

OBJECTIVES The characterization of differential gene expression in Giardia lamblia WB C6 strain C4 resistant to metronidazole and nitazoxanide using microarray technology and quantitative real-time PCR. METHODS In a previous study, we created and characterized the G. lamblia WB C6 clone C4 resistant to nitazoxanide and metronidazole. In this study, using a microarray-based approach, we have identified open-reading frames (ORFs) that were differentially expressed in C4 when compared with its wild-type WB C6. Using quantitative real-time PCR, we have validated the expression patterns of some of those ORFs, focusing on chaperones such as heat-shock proteins in wild-type and C4 trophozoites. In order to induce an antigenic shift, trophozoites of both strains were subjected to a cycle of en- and excystation. Expression of selected genes and resistance to nitazoxanide and metronidazole were investigated after this cycle. RESULTS Forty of a total of 9115 ORFs were found to be up-regulated and 46 to be down-regulated in C4 when compared with wild-type. After a cycle of en- and excystation, resistance of C4 to nitazoxanide and metronidazole was lost. Resistance formation and en-/excystation were correlated with changes in expression of ORFs encoding for major surface antigens such as the variant surface protein TSA417 or AS7 ('antigenic shift'). Moreover, expression patterns of the cytosolic heat-shock protein HSP70 B2, HSP40, and of the previously identified nitazoxanide-binding proteins nitroreductase and protein disulphide isomerase PDI4 were correlated with resistance and loss of resistance after en-/excystation. C4 trophozoites had a higher thermotolerance level than wild-type trophozoites. After en-/excystation, this tolerance was lost. CONCLUSIONS These results suggest that resistance formation in Giardia to nitazoxanide and metronidazole is correlated with altered expression of genes involved in stress response such as heat-shock proteins.

Fluctuations and single molecules

The fluorescence of single molecules coupled to a thermal bath is studied both experimentally and theoretically. The effect of different fluctuations on the coherence properties of resonance fluorescence is considered first. Coherence is measured in an interference experiment where a single molecule is used as a light source. A standard approach based on the optical Bloch equations apparently provides quite an accurate description of the interference experiment. Systems with long correlation times (where spectra are time dependent on any timescale) are considered next. It is shown that intensity-time-frequency correlation spectroscopy, which provides both high signal-to-noise ratio and high time resolution, is very suitable for such a case. The Bloch equations are further tested in an experiment where the shape of an excitation spectral line of a single molecule is accurately measured over six orders of magnitude of the exciting laser power. Significant deviations from the predictions of the Bloch equations are found. The role of critical parameters-the correlation time of the bath, the Rabi oscillation period, and the coupling constant between the bath and the molecule-is discussed. The paper also includes a short general introduction to the methodology of single-molecule studies.

Screening of obstructive and central apnoea/hypopnoea in children using variability: A preliminary study

Aim: Polysomnography (PSG) is the current standard protocol for sleep disordered breathing (SDB) investigation in children. Presently, there are limited reliable screening tests for both central (CE) and obstructive (OE) respiratory events. This study compared three indices, derived from pulse oximetry and electrocardiogram ( ECG), with the PSG gold standard. These indices were heart rate (HR) variability, arterial blood oxygen de-saturation (SaO(2)) and pulse transit time (PTT). Methods: 15 children (12 male) from routine PSG studies were recruited (aged 3 - 14 years). The characteristics of the three indices were based on known criteria for respiratory events (RPE). Their estimation singly and in combination was evaluated with simultaneous scored PSG recordings. Results: 215 RPE and 215 tidal breathing events were analysed. For OE, the obtained sensitivity was HR (0.703), SaO(2) (0.047), PTT (0.750), considering all three indices (0) and either of the indices (0.828) while specificity was (0.891), (0.938), (0.922), (0.953) and (0.859) respectively. For CE, the sensitivity was HR (0.715), SaO(2) (0.278), PTT (0.662), considering all indices (0.040) and either of the indices (0.868) while specificity was (0.815), (0.954), (0.901), (0.960) and (0.762) accordingly. Conclusions: Preliminary findings herein suggest that the later combination of these non-invasive indices to be a promising screening method of SDB in children.

Physical and MAC layer techniques for next generation satellite communications

In this thesis, we consider four different scenarios of interest in modern satellite communications. For each scenario, we will propose the use of advanced solutions aimed at increasing the spectral efficiency of the communication links. First, we will investigate the optimization of the current standard for digital video broadcasting. We will increase the symbol rate of the signal and determine the optimal signal bandwidth. We will apply the time packing technique and propose a specifically design constellation. We will then compare some receiver architectures with different performance and complexity. The second scenario still addresses broadcast transmissions, but in a network composed of two satellites. We will compare three alternative transceiver strategies, namely, signals completely overlapped in frequency, frequency division multiplexing, and the Alamouti space-time block code, and, for each technique, we will derive theoretical results on the achievable rates. We will also evaluate the performance of said techniques in three different channel models. The third scenario deals with the application of multiuser detection in multibeam satellite systems. We will analyze a case in which the users are near the edge of the coverage area and, hence, they experience a high level of interference from adjacent cells. Also in this case, three different approaches will be compared. A classical approach in which each beam carries information for a user, a cooperative solution based on time division multiplexing, and the Alamouti scheme. The information theoretical analysis will be followed by the study of practical coded schemes. We will show that the theoretical bounds can be approached by a properly designed code or bit mapping. Finally, we will consider an Earth observation scenario, in which data is generated on the satellite and then transmitted to the ground. We will study two channel models, taking into account one or two transmit antennas, and apply techniques such as time and frequency packing, signal predistortion, multiuser detection and the Alamouti scheme.

Statistical mechanics of broadcast channels using low-density parity-check codes

We investigate the use of Gallager's low-density parity-check (LDPC) codes in a degraded broadcast channel, one of the fundamental models in network information theory. Combining linear codes is a standard technique in practical network communication schemes and is known to provide better performance than simple time sharing methods when algebraic codes are used. The statistical physics based analysis shows that the practical performance of the suggested method, achieved by employing the belief propagation algorithm, is superior to that of LDPC based time sharing codes while the best performance, when received transmissions are optimally decoded, is bounded by the time sharing limit.

Cortical oscillatory activity associated with the perception of illusory and real visual contours

We used magnetoencephalography (MEG) to examine the nature of oscillatory brain rhythms when passively viewing both illusory and real visual contours. Three stimuli were employed: a Kanizsa triangle; a Kanizsa triangle with a real triangular contour superimposed; and a control figure in which the corner elements used to form the Kanizsa triangle were rotated to negate the formation of illusory contours. The MEG data were analysed using synthetic aperture magnetometry (SAM) to enable the spatial localisation of task-related oscillatory power changes within specific frequency bands, and the time-course of activity within given locations-of-interest was determined by calculating time-frequency plots using a Morlet wavelet transform. In contrast to earlier studies, we did not find increases in gamma activity (> 30 Hz) to illusory shapes, but instead a decrease in 10–30 Hz activity approximately 200 ms after stimulus presentation. The reduction in oscillatory activity was primarily evident within extrastriate areas, including the lateral occipital complex (LOC). Importantly, this same pattern of results was evident for each stimulus type. Our results further highlight the importance of the LOC and a network of posterior brain regions in processing visual contours, be they illusory or real in nature. The similarity of the results for both real and illusory contours, however, leads us to conclude that the broadband (< 30 Hz) decrease in power we observed is more likely to reflect general changes in visual attention than neural computations specific to processing visual contours.