An approach to emotion recognition in single-channel EEG signals: a mother child interaction

In this work, we perform a first approach to emotion recognition from EEG single channel signals extracted in four (4) mother-child dyads experiment in developmental psychology -- Single channel EEG signals are analyzed and processed using several window sizes by performing a statistical analysis over features in the time and frequency domains -- Finally, a neural network obtained an average accuracy rate of 99% of classification in two emotional states such as happiness and sadness

Second-order cyclostationarity-based detection and classification of LTE SC-FDMA signals for cognitive radio

Cognitive radio (CR) was developed for utilizing the spectrum bands efficiently. Spectrum sensing and awareness represent main tasks of a CR, providing the possibility of exploiting the unused bands. In this thesis, we investigate the detection and classification of Long Term Evolution (LTE) single carrier-frequency division multiple access (SC-FDMA) signals, which are used in uplink LTE, with applications to cognitive radio. We explore the second-order cyclostationarity of the LTE SC-FDMA signals, and apply results obtained for the cyclic autocorrelation function to signal detection and classification (in other words, to spectrum sensing and awareness). The proposed detection and classification algorithms provide a very good performance under various channel conditions, with a short observation time and at low signal-to-noise ratios, with reduced complexity. The validity of the proposed algorithms is verified using signals generated and acquired by laboratory instrumentation, and the experimental results show a good match with computer simulation results.

How effective are acoustic signals in territorial defence in the Lusitanian toadfish?

The function of fish sounds in territorial defence, in particular its influence on the intruder's behaviour during territorial invasions, is poorly known. Breeding Lusitanian toadfish males (Halobatrachus didactylus) use sounds (boatwhistles) to defend nests from intruders. Results from a previous study suggest that boatwhistles function as a 'keep-out signal' during territorial defence. To test this hypothesis we performed territorial intrusion experiments with muted Lusitanian toadfish. Males were muted by making a cut and deflating the swimbladder (the sound-producing apparatus) under anaesthesia. Toadfish nest-holder males reacted to intruders mainly by emitting sounds (sham-operated and control groups) and less frequently with escalated bouts of fighting. When the nest-holder produced a boatwhistle, the intruder fled more frequently than expected by chance alone. Muted males experienced a higher number of intrusions than the other groups, probably because of their inability to vocalise. Together, our results show that fish acoustic signals are effective deterrents in nest/territorial intrusions, similar to bird song.

A Quantitative analysis of pulsed signals emitted by wild bottlenose dolphins

Common bottlenose dolphins (Tursiops truncatus), produce a wide variety of vocal emissions for communication and echolocation, of which the pulsed repertoire has been the most difficult to categorize. Packets of high repetition, broadband pulses are still largely reported under a general designation of burst-pulses, and traditional attempts to classify these emissions rely mainly in their aural characteristics and in graphical aspects of spectrograms. Here, we present a quantitative analysis of pulsed signals emitted by wild bottlenose dolphins, in the Sado estuary, Portugal (2011-2014), and test the reliability of a traditional classification approach. Acoustic parameters (minimum frequency, maximum frequency, peak frequency, duration, repetition rate and inter-click-interval) were extracted from 930 pulsed signals, previously categorized using a traditional approach. Discriminant function analysis revealed a high reliability of the traditional classification approach (93.5% of pulsed signals were consistently assigned to their aurally based categories). According to the discriminant function analysis (Wilk's Λ = 0.11, F3, 2.41 = 282.75, P < 0.001), repetition rate is the feature that best enables the discrimination of different pulsed signals (structure coefficient = 0.98). Classification using hierarchical cluster analysis led to a similar categorization pattern: two main signal types with distinct magnitudes of repetition rate were clustered into five groups. The pulsed signals, here described, present significant differences in their time-frequency features, especially repetition rate (P < 0.001), inter-click-interval (P < 0.001) and duration (P < 0.001). We document the occurrence of a distinct signal type-short burst-pulses, and highlight the existence of a diverse repertoire of pulsed vocalizations emitted in graded sequences. The use of quantitative analysis of pulsed signals is essential to improve classifications and to better assess the contexts of emission, geographic variation and the functional significance of pulsed signals.

Processing of laser Doppler flowmetry signals from healthy subjects and patients with varicose veins: information categorization approach based on intrinsic mode functions and entropy computation

International audience

Modulation of GABA and glutamate release by brain-derived neurotrophic factor : role of adenosine A2A receptors

Trabalho Final do Curso de Mestrado Integrado em Medicina, Faculdade de Medicina, Universidade de Lisboa, 2014

The Araucaria dendrochronological network: growth patterns and climatic signals of paraná-pine on the Southern Brazilian plateau.

2016

Bayesian nonparametric learning of contexts and activities from pervasive signals

This thesis develops machine learning techniques to discover activities and contexts from pervasive sensor data. These techniques are especially suitable for streaming sensor data as they can infer the context space automatically. They are applicable in many real world applications such as activity monitoring or organization management.

Distribution entropy analysis of epileptic EEG signals

It is an open-ended challenge to accurately detect the epileptic seizures through electroencephalogram (EEG) signals. Recently published studies have made elaborate attempts to distinguish between the normal and epileptic EEG signals by advanced nonlinear entropy methods, such as the approximate entropy, sample entropy, fuzzy entropy, and permutation entropy, etc. Most recently, a novel distribution entropy (DistEn) has been reported to have superior performance compared with the conventional entropy methods for especially short length data. We thus aimed, in the present study, to show the potential of DistEn in the analysis of epileptic EEG signals. The publicly-accessible Bonn database which consisted of normal, interictal, and ictal EEG signals was used in this study. Three different measurement protocols were set for better understanding the performance of DistEn, which are: i) calculate the DistEn of a specific EEG signal using the full recording; ii) calculate the DistEn by averaging the results for all its possible non-overlapped 5 second segments; and iii) calculate it by averaging the DistEn values for all the possible non-overlapped segments of 1 second length, respectively. Results for all three protocols indicated a statistically significantly increased DistEn for the ictal class compared with both the normal and interictal classes. Besides, the results obtained under the third protocol, which only used very short segments (1 s) of EEG recordings showed a significantly (p <; 0.05) increased DistEn for the interictal class in compassion with the normal class, whereas both analyses using relatively long EEG signals failed in tracking this difference between them, which may be due to a nonstationarity effect on entropy algorithm. The capability of discriminating between the normal and interictal EEG signals is of great clinical relevance since it may provide helpful tools for the detection of a seizure onset. Therefore, our study suggests that the DistEn analysis of EEG signals is very promising for clinical and even portable EEG monitoring.

Robust time-spread echo watermarking using characteristics of host signals

A robust audio watermarking method based on the time-spread (TS) echo hiding scheme is proposed. Compared with existing TS watermarking methods, the approach is more robust as it exploits the characteristics of host signals in the encoding stage. Theoretical analysis and simulation examples demonstrate the effectiveness and advantages of the method.

Paleoenvironments and Geochemical Signals from the Late Barremian to the Middle Aptian in a Tethyan Marginal Basin, Northeast Spain: Implications for Carbon Sequestration in Restricted Basins

The hallmark of oceanic anoxic event 1a (OAE1a) (early Aptian ~125 Ma) corresponds to worldwide deposition of black shales with total organic carbon (TOC) content > 2% and a d13C positive excursion up to ~5‰. OAE1a has been related to large igneous province volcanism and dissociation of methane hydrates during the Lower Cretaceous. However, the occurrence of atypical, coeval and diachronous organic-rich deposits associated with OAE1a, which are also characterized by positive spikes of the d13C in epicontinental to restricted marine environments of the Tethys Ocean, indicates localized responses decoupled from complex global forcing factors. The present research is a high-resolution, multiproxy approach to assess the paleoenvironmental conditions that led to enhanced carbon sequestration from the late Barremian to the middle Aptian in a restricted, Tethyan marginal basin prior to and during OAE1a. I studied the lower 240 m of the El Pui section, Organyà Basin, Spanish Pyrenees. The basin developed as the result of extensional tectonism linked to the opening of the Atlantic Ocean. At the field scale the section consists of a sequence of alternating beds of cm – m-scale, medium-gray to grayish-black limestones and marlstones with TOC up to ~4%. The results indicate that the lowest 85 m of the section, from latest Barremian –earliest Aptian, characterize a deepening phase of the basin concomitant with sustained riverine flux and intensified primary productivity. These changes induced a shift in the sedimentation pattern and decreased the oxygen levels in the water column through organic matter respiration and limited ventilation of the basin. The upper 155 m comprising the earliest – late-early Aptian document the occurrence of OAE1a and its associated geochemical signatures (TOC up to 3% and a positive shift in d13C of ~5‰). However, a low enrichment of redox-sensitive trace elements indicates that the basin did not achieve anoxic conditions. The results also suggest that a shallower-phase of the basin, coeval with platform progradation, may have increased ventilation of the basin at the same time that heightened sedimentation rates and additional input of organic matter from terrestrial sources increased the burial and preservation rate of TOC in the sediment.

Canine mesenchymal stem cells are neurotrophic and angiogenic:an in vitro assessment of their paracrine activity

Mesenchymal stem cells (MSCs) have been used in cell replacement therapies for connective tissue damage, but also can stimulate wound healing through paracrine activity. In order to further understand the potential use of MSCs to treat dogs with neurological disorders, this study examined the paracrine action of adipose-derived canine MSCs on neuronal and endothelial cell models. The culture-expanded MSCs exhibited a MSC phenotype according to plastic adherence, cell morphology, CD profiling and differentiation potential along mesenchymal lineages. Treating the SH-SY5Y neuronal cell line with serum-free MSC culture-conditioned medium (MSC CM) significantly increased SH-SY5Y cell proliferation (P < 0.01), neurite outgrowth (P = 0.0055) and immunopositivity for the neuronal marker βIII-tubulin (P = 0.0002). Treatment of the EA.hy926 endothelial cell line with MSC CM significantly increased the rate of wound closure in endothelial cell scratch wound assays (P = 0.0409), which was associated with significantly increased endothelial cell proliferation (P < 0.05) and migration (P = 0.0001). Furthermore, canine MSC CM induced endothelial tubule formation in EA.hy926 cells in a soluble basement membrane matrix. Hence, this study has demonstrated that adipose-derived canine MSC CM stimulated neuronal and endothelial cells probably through the paracrine activity of MSC-secreted factors. This supports the use of canine MSC transplants or their secreted products in the clinical treatment of dogs with neurological disorders and provides some insight into possible mechanisms of action.

Harnessing bacterial signals for suppression of biofilm formation in the nosocomial fungal pathogen Aspergillus fumigatus

Faced with the continued emergence of antibiotic resistance to all known classes of antibiotics, a paradigm shift in approaches toward antifungal therapeutics is required. Well characterized in a broad spectrum of bacterial and fungal pathogens, biofilms are a key factor in limiting the effectiveness of conventional antibiotics. Therefore, therapeutics such as small molecules that prevent or disrupt biofilm formation would render pathogens susceptible to clearance by existing drugs. This is the first report describing the effect of the Pseudomonas aeruginosa alkylhydroxyquinolone interkingdom signal molecules 2-heptyl-3-hydroxy-4-quinolone and 2-heptyl-4-quinolone on biofilm formation in the important fungal pathogen Aspergillus fumigatus. Decoration of the anthranilate ring on the quinolone framework resulted in significant changes in the capacity of these chemical messages to suppress biofilm formation. Addition of methoxy or methyl groups at the C5–C7 positions led to retention of anti-biofilm activity, in some cases dependent on the alkyl chain length at position C2. In contrast, halogenation at either the C3 or C6 positions led to loss of activity, with one notable exception. Microscopic staining provided key insights into the structural impact of the parent and modified molecules, identifying lead compounds for further development.

Singularity and multifractal characterization of signals with wavelets. Application to clay soil images

In the field of multiscale analysis of signals, including images, the wavelet transform is one of the most attractive and powerful tool due to its ability to focus on signals structures at different scales. Wavelet Transform at different scales is successfully applied to image characterization (which can be applied to a watermarking scheme) and multiscale singularity detection and processing. In this work we show further research of computation of multifractals properties such as the multifractal spectrum (D(alpha)) applied to dye stained images of natural terrain. This can be useful for statically describing preferential flow path geometry.

Peripheral brain-derived neurotrophic factor levels in alzheimer's disease and mild cognitive impairment: A comprehensive systematic review and meta-analysis

Alzheimer's disease (AD) is becoming a growing global problem, and there is an urgent need to identify reliable blood biomarkers of the risk and progression of this condition. A potential candidate is the brain-derived neurotrophic factor (BDNF), which modulates major trophic effects in the brain. However, findings are apparently inconsistent regarding peripheral blood BDNF levels in AD patients vs. healthy people. We thus performed a systematic review and meta-analysis of the studies that have examined peripheral BDNF levels in patients with AD or mild cognitive impairment (MCI) and healthy controls. We searched articles through PubMed, EMBASE, and hand searching. Over a total pool of 2061 potential articles, 26 met all inclusion criteria (including a total of 1584 AD patients, 556 MCI patients, and 1294 controls). A meta-analysis of BDNF levels between early AD and controls showed statistically significantly higher levels (SMD [95 % CI]: 0.72 [0.31, 1.13]) with no heterogeneity. AD patients with a low (<20) mini-mental state examination (MMSE) score had lower peripheral BDNF levels compared with controls (SMD [95 % CI]: -0.33 [-0.60, -0.05]). However, we found no statistically significant difference in blood (serum/plasma) BDNF levels between all AD patients and controls (standard mean difference, SMD [95 % CI]: -0.16 [-0.4, 0.07]), and there was heterogeneity among studies (P < 0.0001, I 2 = 85.8 %). There were no differences in blood BDNF levels among AD or MCI patients vs. controls by subgroup analyses according to age, sex, and drug use. In conclusion, this meta-analysis shows that peripheral blood BDNF levels seem to be increased in early AD and decreased in AD patients with low MMSE scores respectively compared with their age- and sex-matched healthy referents. At present, however, this could not be concluded from individual studies.