A Logistic Model Tree Solution

Beretta, S., Castelli, M., Gonçalves, I., Kel, I., Giansanti, V., & Merelli, I. (2018). Improving eQTL Analysis Using a Machine Learning Approach for Data Integration: A Logistic Model Tree Solution. Journal of Computational Biology, 25(10), 1091-1105. DOI: 10.1089/cmb.2017.0167Expression quantitative trait loci (eQTL) analysis is an emerging method for establishing the impact of genetic variations (such as single nucleotide polymorphisms) on the expression levels of genes. Although different methods for evaluating the impact of these variations are proposed in the literature, the results obtained are mostly in disagreement, entailing a considerable number of false-positive predictions. For this reason, we propose an approach based on Logistic Model Trees that integrates the predictions of different eQTL mapping tools to produce more reliable results. More precisely, we employ a machine learning-based method using logistic functions to perform a linear regression able to classify the predictions of three eQTL analysis tools (namely, R/qtl, MatrixEQTL, and mRMR). Given the lack of a reference dataset and that computational predictions are not so easy to test experimentally, the performance of our approach is assessed using data from the DREAM5 challenge. The results show the quality of the aggregated prediction is better than that obtained by each single tool in terms of both precision and recall. We also performed a test on real data, employing genotypes and microRNA expression profiles from Caenorhabditis elegans, which proved that we were able to correctly classify all the experimentally validated eQTLs. These good results come both from the integration of the different predictions, and from the ability of this machine learning algorithm to find the best cutoff thresholds for each tool. This combination makes our integration approach suitable for improving eQTL predictions for testing in a laboratory, reducing the number of false-positive results.authorsversionpublishe

Advanced HF Communications for Remote Sensors in Antarctica

The Antarctica is a continent mainly devoted to science with a big amount of sensors located in remote places for biological and geophysical purposes. The data from these sensors need to be sent either to the Antarctic stations or directly to the home country. For the last 15 years, La Salle has been working in the application of HF communications (3–30 MHz) with ionospheric reflection for data collection of remote sensors in Antarctica. We have developed and tested the several types of modulations, the frame structure, the radio-modem, and the antennas for two different scenarios. First, a long-range transequatorial (approximately 12,800 km) and low-power communication system is used as an alternative to satellites, which are often not visible from the poles. This distance is covered with a minimum of four hops with oblique incidence in the ionosphere. Second, a low-power system using near vertical incidence skywave (NVIS) communications provides coverage in a surface of approximately 200–250 km radius, a coverage much longer than any other systems operating in either the VHF or UHF band without the need of line of sight

Auditory Streaming: Behavior, Physiology, and Modeling

Auditory streaming is a fundamental aspect of auditory perception. It refers to the ability to parse mixed acoustic events into meaningful streams where each stream is assumed to originate from a separate source. Despite wide interest and increasing scientific investigations over the last decade, the neural mechanisms underlying streaming still remain largely unknown. A simple example of this mystery concerns the streaming of simple tone sequences, and the general assumption that separation along the tonotopic axis is sufficient for stream segregation. However, this dissertation research casts doubt on the validity of this assumption. First, behavioral measures of auditory streaming in ferrets prove that they can be used as an animal model to study auditory streaming. Second, responses from neurons in the primary auditory cortex (A1) of ferrets show that spectral components that are well-separated in frequency produce comparably segregated responses along the tonotopic axis, no matter whether presented synchronously or consecutively, despite the substantial differences in their streaming percepts when measured psychoacoustically in humans. These results argue against the notion that tonotopic separation per se is a sufficient neural correlate of stream segregation. Thirdly, comparing responses during behavior to those during the passive condition, the temporal correlations of spiking activity between neurons belonging to the same stream display an increased correlation, while responses among neurons belonging to different streams become less correlated. Rapid task-related plasticity of neural receptive fields shows a pattern that is consistent with the changes in correlation. Taken together these results indicate that temporal coherence is a plausible neural correlate of auditory streaming. Finally, inspired by the above biological findings, we propose a computational model of auditory scene analysis, which uses temporal coherence as the primary criterion for predicting stream formation. The promising results of this dissertation research significantly advance our understanding of auditory streaming and perception

Colour local feature fusion for image matching and recognition

This thesis investigates the use of colour information for local image feature extraction. The work is motivated by the inherent limitation of the most widely used state of the art local feature techniques, caused by their disregard of colour information. Colour contains important information that improves the description of the world around us, and by disregarding it; chromatic edges may be lost and thus decrease the level of saliency and distinctiveness of the resulting grayscale image. This thesis addresses the question of whether colour can improve the distinctive and descriptive capabilities of local features, and if this leads to better performances in image feature matching and object recognition applications. To ensure that the developed local colour features are robust to general imaging conditions and capable for real-world applications, this work utilises the most prominent photometric colour invariant gradients from the literature. The research addresses several limitations of previous studies that used colour invariants, by implementing robust local colour features in the form of a Harris-Laplace interest region detection and a SIFT description which characterises the detected image region. Additionally, a comprehensive and rigorous evaluation is performed, that compares the largest number of colour invariants of any previous study. This research provides for the first time, conclusive findings on the capability of the chosen colour invariants for practical real-world computer vision tasks. The last major aspect of the research involves the proposal of a feature fusion extraction strategy, that uses grayscale intensity and colour information conjointly. Two separate fusion approaches are implemented and evaluated, one for local feature matching tasks and another approach for object recognition. Results from the fusion analysis strongly indicate, that the colour invariants contain unique and useful information that can enhance the performance of techniques that use grayscale only based features

Cooperative Distributed Transmission and Reception

In telecommunications, a cooperative scheme refers to a method where two or more users share or combine their information in order to increase diversity gain or power gain. In contrast to conventional point-to-point communications, cooperative communications allow different users in a wireless network to share resources so that instead of maximizing the performance of its own link, each user collaborates with its neighbours to achieve an overall improvement in performance. In this dissertation, we consider different models for transmission and reception and explore cooperative techniques that increase the reliability and capacity gains in wireless networks, with consideration to practical issues such as channel estimation errors and backhaul constraints. This dissertation considers the design and performance of cooperative communication techniques. Particularly, the first part of this dissertation focuses on the performance comparison between interference alignment and opportunistic transmission for a 3-user single-input single- output (SISO) interference channel in terms of average sum rate in the presence of channel estimation errors. In the case of interference alignment, channel estimation errors cause interference leakage which consequently results in a loss of achievable rate. In the case of opportunistic transmission, channel estimation errors result in a non-zero probability of incorrectly choosing the node with the best channel. The effect of these impairments is quantified in terms of the achievable average sum rate of these transmission techniques. Analysis and numerical examples show that SISO interference alignment can achieve better average sum rate with good channel estimates and at high SNR whereas opportunistic transmission provides better performance at low SNR and/or when the channel estimates are poor. We next considers the problem of jointly decoding binary phase shift keyed (BPSK) messages from a single distant transmitter to a cooperative receive cluster connected by a local area network (LAN). An approximate distributed receive beamforming algorithm is proposed based on the exchange of coarsely- quantized observations among some or all of the nodes in the receive cluster. By taking into account the differences in channel quality across the receive cluster, the quantized information from other nodes in the receive cluster can be appropriately combined with locally unquantized information to form an approximation of the ideal receive beamformer decision statistic. The LAN throughput requirements of this technique are derived as a function of the number of participating nodes in the receive cluster, the forward link code rate, and the quantization parameters. Using information-theoretic analysis and simulations of an LDPC coded system in fading channels, numerical results show that the performance penalty (in terms of outage probability and block error rate) due to coarse quantization is small in the low SNR regimes enabled by cooperative distributed reception. An upper/lower bound approximation is derived based on a circle approximation in the channel magnitude domain which provides a pretty fast way to compute the outage probability performance for a system with arbitrary number of receivers at a given SNR. In the final part of this dissertation, we discuss the distributed reception technique with higher- order modulation schemes in the forward link. The extension from BPSK to QPSK is straightforward and is studied in the second part of this dissertation. The extension to 8PSK, 4PAM and 16QAM forward links, however, is not trivial. For 8PSK, two techniques are proposed: pseudobeamforming and 3-bit belief combining where the first one is intuitive and turns out to be suboptimal,the latter is optimal in terms of outage probability performance. The idea of belief combining can be applied to the 4PAM and 16QAM and it is shown that better/finer quantizer design can further improve the block error rate performance. Information-theoretic analysis and numerical results are provided to show that significant reliability and SNR gains can be achieved by using the proposed schemes

A search for pulsars around Sgr A* in the first Event Horizon Telescope data set

In 2017 the Event Horizon Telescope (EHT) observed the supermassive black hole at the center of the Milky Way, Sagittarius A* (Sgr A*), at a frequency of 228.1 GHz (λ = 1.3 mm). The fundamental physics tests that even a single pulsar orbiting Sgr A* would enable motivate searching for pulsars in EHT data sets. The high observing frequency means that pulsars—which typically exhibit steep emission spectra—are expected to be very faint. However, it also negates pulse scattering, an effect that could hinder pulsar detections in the Galactic center. Additionally, magnetars or a secondary inverse Compton emission could be stronger at millimeter wavelengths than at lower frequencies. We present a search for pulsars close to Sgr A* using the data from the three most sensitive stations in the EHT 2017 campaign: the Atacama Large Millimeter/submillimeter Array, the Large Millimeter Telescope, and the IRAM 30 m Telescope. We apply three detection methods based on Fourier-domain analysis, the fast folding algorithm, and single-pulse searches targeting both pulsars and burst-like transient emission. We use the simultaneity of the observations to confirm potential candidates. No new pulsars or significant bursts were found. Being the first pulsar search ever carried out at such high radio frequencies, we detail our analysis methods and give a detailed estimation of the sensitivity of the search. We conclude that the EHT 2017 observations are only sensitive to a small fraction (≲2.2 of the pulsars that may exist close to Sgr A*, motivating further searches for fainter pulsars in the region

Comparison of optimisation algorithms for centralised anaerobic co-digestion in a real river basin case study in Catalonia

Anaerobic digestion (AnD) is a process that allows the conversion of organic waste into a source of energy such as biogas, introducing sustainability and circular economy in waste treatment. AnD is an intricate process because of multiple parameters involved, and its complexity increases when the wastes are from different types of generators. In this case, a key point to achieve good performance is optimisation methods. Currently, many tools have been developed to optimise a single AnD plant. However, the study of a network of AnD plants and multiple waste generators, all in different locations, remains unexplored. This novel approach requires the use of optimisation methodologies with the capacity to deal with a highly complex combinatorial problem. This paper proposes and compares the use of three evolutionary algorithms: ant colony optimisation (ACO), genetic algorithm (GA) and particle swarm optimisation (PSO), which are especially suited for this type of application. The algorithms successfully solve the problem, using an objective function that includes terms related to quality and logistics. Their application to a real case study in Catalonia (Spain) shows their usefulness (ACO and GA to achieve maximum biogas production and PSO for safer operation conditions) for AnD facilities.Peer ReviewedPostprint (published version

The interaction of infra-red laser radiation with solid targets

The pulsed HF chemical laser was discovered in 1966 by Deutsch. Early lasers had very low power outputs; it is only more recently that high power pulsed HF/DF lasers have emerged. This thesis is concerned with the development of a 10J HF laser in 1976 and subsequent interaction experiments. The high power HF/DF laser is a potentially valuable new device in view of its large gain coefficient and output intermediate in wavelength to the Nd:glass and CO2 laser. Information on interactions at this wavelength has been lacking and the solid target interactions presented here help to remedy this deficiency. In addition, certain investigations were carried out using the CO2 laser. These experiments aided direct comparison of the interaction data at the two infra-red wavelengths.In the first chapter basic laser-plasma interaction theory is discussed. A vacuum environment is firstly considered, and emphasis is given to those models relevant to target irradiances available in our laboratories. Anomalous heating is only superficially treated as these studies were carried out below the non-linear thresholds. The theoretical variation of plasma parameters with laser wavelength is presented next, followed by a consideration of the gaseous environment. A brief review of pulsed HF laser design is gIven In chapter 2 followed by an account of our own design studies in the next  chapter. Chapters 4 and 5 are devoted to laser-target interaction studies employing vacuum and gaseous environments respectively. The first published comprehensive vacuum interaction study, using the HF laser, is presented in chapter 4. The Z dependence of ion-velocity scaling, ion-number scaling, and reflection variation is recorded, together with the first x-ray temperature measurements at this wavelength. The gaseous environment is considered in the following chapter, where thermal coupling and laser supported detonation wave observations are given. Chapter 6 deals with vacuum interaction studies carried out at the CO2 wavelength. The final chapters deal with the comparison of experimental results with theory, together with a general review of other published interaction investigations

Responding to the challenges of Water and Global Warming: Environmental Hydrogeology and Global Change Research Group (HYGLO-Lab)

[EN] The current Global Warming of planet Earth is probably the most important geological phenomenon in the last 20,000 years of its history and for human race. This process is having nowadays notable effects on the climate, ecosystems and natural resources. Possibly the most important renewable geological resource is water. One of the most strategic phases of the water cycle is groundwater. Despite its low visibility, quantitatively (and qualitatively too) it is essential for life on Planet Earth. Foreseeable consequences on groundwater due to climate change and sea level rise will be very significant. Hydrogeology can provide answers to many of the questions that are beginning to be raised in relation to these impacts and their effects. Environmental hydrogeology is a way of understanding the set of disciplines mixed in Hydrogeology as a Science of Nature. The HYGLO-Lab Research Group of the IGME-CSIC National Center attempts, through its lines of research, with a double global and local component, to provide answers to some of these questions.Peer reviewe