Multichannel dynamic modeling of non-Gaussian mixtures

[EN] This paper presents a novel method that combines coupled hidden Markov models (HMM) and non Gaussian mixture models based on independent component analyzer mixture models (ICAMM). The proposed method models the joint behavior of a number of synchronized sequential independent component analyzer mixture models (SICAMM), thus we have named it generalized SICAMM (G-SICAMM). The generalization allows for flexible estimation of complex data densities, subspace classification, blind source separation, and accurate modeling of both local and global dynamic interactions. In this work, the structured result obtained by G-SICAMM was used in two ways: classification and interpretation. Classification performance was tested on an extensive number of simulations and a set of real electroencephalograms (EEG) from epileptic patients performing neuropsychological tests. G-SICAMM outperformed the following competitive methods: Gaussian mixture models, HMM, Coupled HMM, ICAMM, SICAMM, and a long short-term memory (LSTM) recurrent neural network. As for interpretation, the structured result returned by G-SICAMM on EEGs was mapped back onto the scalp, providing a set of brain activations. These activations were consistent with the physiological areas activated during the tests, thus proving the ability of the method to deal with different kind of data densities and changing non-stationary and non-linear brain dynamics. (C) 2019 Elsevier Ltd. All rights reserved.This work was supported by Spanish Administration (Ministerio de Economia y Competitividad) and European Union (FEDER) under grants TEC2014-58438-R and TEC2017-84743-P.Safont Armero, G.; Salazar Afanador, A.; Vergara Domínguez, L.; Gomez, E.; Villanueva, V. (2019). Multichannel dynamic modeling of non-Gaussian mixtures. Pattern Recognition. 93:312-323. https://doi.org/10.1016/j.patcog.2019.04.022S3123239

Molecular Response of Retinal Pigment Epithelial Cells to Oxidized Lipoproteins: Global and Targeted Studies

Global-scale examinations of biological systems at the molecular level complement targeted approaches to scientific inquiry that focus on specific subsets of biomolecules, or on a single molecule of interest. In this dissertation, we utilized both the discovery-based approach to evaluate the proteomics workflows centered around mass spectrometry as the key technology, and the targeted approach to examine the molecular response of RPE due to oxidized lipoproteins (oxLDL) treatments. A crucial aspect in proteomics studies is the design of bioanalytical strategies that maximize coverage of the complex repertoire of a proteome. A comprehensive, unbiased examination of the proteome represents a powerful approach toward system-level insights into disease mechanisms. We evaluated the performance of bioanalytical platforms for profiling of the proteome in a biological system. We applied a discovery-based approach to evaluate the global transcriptome and proteome changes due to oxLDL treatment in ARPE-19 cells. We studied the role of scavenger receptors CD36 and CD5L/AIM in ARPE-19 cells when induced with oxLDL. We compared three different multidimensional proteome fractionation platforms: polymeric reversed-phase liquid chromatography at high pH (PLRP), sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE), and isoelectric focusing (IEF) separations. We applied a liquid chromatography-mass spectrometry/mass spectrometry (LC-MS/MS) in a data-dependent setting and used bioinformatics for protein identification. The three platforms identified a total of 1043 proteins altogether. Among the three bioanalytical strategies, SDS-PAGE followed by LC-MS/MS provided the best coverage. We also evaluated another bioanalytical platform which consists of a highresolution mass spectrometer combined with nano-UPLC in a data-independent setting without pre-fractionation for oxLDL mediated proteome alteration in ARPE-19 cells. This platform outperformed the SDS-PAGE based analytical platform in terms of proteome coverage as it identified around 2500 proteins, ca. 3-fold more proteins than the latter. Most importantly, this platform was able to perform label free quantification of differentially expressed proteome alteration. The platforms identified proteins with diverse physicochemical characteristics involved in various functional roles within the biological system. Furthermore, we carried out the first comparative transcriptomic and proteomic study for the evaluation of oxLDL effects on ARPE-19 cells after a 4 h exposure. The treatment with oxLDL affected the regulation of more than 700 genes that were involved in regulation of cell cycle, oxidative stress, cholesterol efflux, circadian rhythm, NRF-2 pathways. However, LDL treatment alone did not induce the regulation of these pathways. The differential proteomic analysis found 41 proteins affected due to the oxLDL treatment. This study provided a foundation for a bioanalytical platform for identification and label-free quantification in the human retinal pigment epithelial cells (ARPE-19) proteome. The list of differentially expressed proteins due to oxLDL treatment identified in this study gives insights to the change in proteins that might be interrogated for their roles in pathogenesis of macular degeneration. These findings could give us targets to intervene in the pathogenesis of AMD progression in human for the development of better treatment and prevention against this degenerative disease. Lastly, we studied the mechanistic role of scavenger receptors CD36 and CD5L/AIM in oxLDL uptake by ARPE-19 cells. We, for the first time, demonstrated the presence of scavenger receptor CD5L in ARPE-19 cell. The oxLDL uptake was primarily dependent on CD36, and both the CD5L/AIM and CD36 were seen to co-localize in the presence of oxLDL. Our results suggest a new dynamics on CD5L/AIM on the oxLDL uptake that was not seen in macrophages. The reduction in intracellular accumulation of oxLDL in the presence of extracellular recombinant CD5L/AIM is an interesting phenomenon as it has been recently shown the involvement of CD5L/AIM in autophagy

Trapped Ion Mobility Spectrometry coupled to Fourier Transform Ion Cyclotron Resonance Mass Spectrometry for the analysis of Complex Mixtures.

Analytical Characterization of complex mixtures, such as crude oil, environmental samples, and biological mixtures, is challenging because of the large diversity of molecular components. Mass spectrometry based techniques are among the most powerful tools for the separation of molecules based on their molecular composition, and the coupling of ion mobility spectrometry has enabled the separation and structural elucidation using the tridimensional structure of the molecule. The present work expands the ability of analytical chemists by furthering the development of IMS-MS instrumentation by coupling Trapped Ion Mobility Spectrometry to Fourier Transform Ion Cyclotron Resonance Mass Spectrometry (TIMS-FT-ICR MS). The TIMS-FT-ICR MS platform combines the high-resolution separation of TIMS, which has mobility resolving powers up to 400, and ultra-high mass resolution of FT-ICR MS, with mass resolving power over 1,000,000. This instrumentation allows the assignment of exact chemical composition for compounds in a complex mixture, as well as measurement of the collision cross-section of the molecule. Herein, the principles of the TIMS separation and its coupling to FT-ICR MS are described, as well as how the platform can be applied to targeted analysis of molecules, and untargeted characterization of complex mixtures. Molecular standards were analyzed by TIMS-MS in order to develop a computational workflow that can be utilized to elucidate molecular structure, using the measured collision cross-section of the ion. This workflow enabled identification of structural, cis/trans isomers, and chelated molecules and provides the basis for unsupervised structural elucidation of a complex mixture, and in particular for the elucidation of hydrocarbons from fossil fuels. In summary, this work presents the coupling of TIMS-FT-ICR MS and provides examples of applications as a proof of concept of the potential of this platform for solving complex analytical challenges

Summary of the second workshop on liquid argon time projection chamber research and development in the United States

The second workshop to discuss the development of liquid argon time projection chambers (LArTPCs) in the United States was held at Fermilab on July 8-9, 2014. The workshop was organized under the auspices of the Coordinating Panel for Advanced Detectors, a body that was initiated by the American Physical Society Division of Particles and Fields. All presentations at the workshop were made in six topical plenary sessions: i) Argon Purity and Cryogenics, ii) TPC and High Voltage, iii) Electronics, Data Acquisition and Triggering, iv) Scintillation Light Detection, v) Calibration and Test Beams, and vi) Software. This document summarizes the current efforts in each of these areas. It primarily focuses on the work in the US, but also highlights work done elsewhere in the world

Integrated Data Acquisition for State-of-the-Art Large-Bore Engine Test Cell

Abstract: Internal combustion engines will have an important role on a road to decarbonization and a sustainable powertrain system in the maritime sector. Electrification of the maritime sector is currently difficult due to its excessive energy density demand. Therefore, internal combustion engines will remain a primary power source for ships in the near future. A novel combustion concept, reactivity-controlled compression ignition (RCCI), can be seen as one of the promising combustion technologies that enables simultaneous ultra-low NOx and soot emissions, as well as high thermal efficiency. Although the concept has been developed for a long time, its feasibility for large-bore engine applications has not been publicly demonstrated. The goal of this thesis was to design and implement a new data acquisition system for the large-bore RCCI test bench in University of Vaasa’s VEBIC engine laboratory, as part of the Clean Propulsion Technologies (CPT) project’s work package 3, novel combustion and advanced aftertreatment. The test bench was instrumented with new sensors, analyzers and data acquisition hardware. Devices required to build the system were acquired and device installations, as well as electrical connections were established and supervised. Additionally, data storing workflow, suitable for the new system, was developed. In order to validate the system performance, a partial system test was carried out due to the inability to start up the engine during the thesis. The results from the partial system test proved that the new data acquisition system is able to measure high sampling frequency signals and record them in reference to crank angle. The system that was designed and implemented in the thesis provided several improvements when compared to the previous system. The number of available high sample frequency channels increased from 8 to 16 and the system provides more flexible real-time post-processing capabilities. The upgraded system also provides a significant improvement in integration, as the high-speed and low-speed measurements can be recorded into a single file. In addition to immediate system improvements, the new system is able to expand according to future requirements of the test bench.Tiivistelmä: Polttomoottoreilla tulee olemaan tärkeä rooli hiilidioksidipäästöjen vähentämisessä ja kestävän voimansiirtojärjestelmän toteuttamisessa merenkulkualalla. Merenkulkualan sähköistäminen on nykyisellään hankalaa valtavan energiantarpeen vuoksi. Sen vuoksi polttomoottorit tulevat pysymään lähitulevaisuudessakin laivojen tärkeimpänä voimanlähteenä. Uutta palamismenetelmää, reaktiivisuudella hallittua puristussytytystä (RCCI), voidaan pitää yhtenä lupaavista polttomoottoriteknologioista, jonka avulla voidaan samanaikaisesti saavuttaa erittäin alhaiset typen oksidi- ja hiukkaspäästöt, sekä korkea hyötysuhde. Vaikka konseptia on kehitetty pitkään, soveltuvuutta isosylinterisissä moottoreissa ei ole osoitettu julkisesti. Tämän opinnäytetyön tavoitteena oli suunnitella ja toteuttaa uusi tiedonkeruujärjestelmä isosylinteriseen RCCI -testipenkkiin Vaasan yliopiston VEBIC moottorilaboratoriossa osana Clean Propulsion Technologies (CPT) -projektin työpakettia 3. Testipenkki instrumentoitiin uusilla antureilla, analysaattoreilla ja tiedonkeruulaitteilla. Järjestelmän rakentamiseen tarvittavat laitteet hankittiin ja laiteasennukset sekä sähköliitännät toteutettiin. Lisäksi mahdollistettiin uuteen järjestelmään soveltuva tiedon tallennusprosessi. Järjestelmän suorituskyvyn arvioimiseksi suoritettiin osittainen järjestelmätesti, koska moottoria ei ollut mahdollista käynnistää vielä opinnäytetyön aikana. Osittaisen järjestelmätestin tulokset osoittivat, että uusi tiedonkeruujärjestelmä kykenee mittaamaan korkealla näytteenottotaajuudella ja tallentamaan mittaukset kampiakselin asennon suhteen. Opinnäytetyössä suunniteltu ja toteutettu järjestelmä tarjosi useita parannuksia edelliseen järjestelmään verrattuna. Käytettävissä olevien korkean näytteenottotaajuuden kanavien lukumäärä kasvoi 8:sta 16:een ja järjestelmä tarjoaa joustavamman reaaliaikaisen tiedon jälkikäsittelyn. Päivitetty järjestelmä tarjoaa myös merkittävän parannuksen datan integroimiseen, koska nopeat ja hitaat mittaukset voidaan tallentaa samaan tiedostoon. Välittömien järjestelmän parannusten lisäksi uusi järjestelmä kykenee mukautumaan tulevaisuuden tarpeiden mukaan

Contextual Mixture of Experts: Integrating Knowledge into Predictive Modeling

This work proposes a new data-driven model devised to integrate process knowledge into its structure to increase the human-machine synergy in the process industry. The proposed Contextual Mixture of Experts (cMoE) explicitly uses process knowledge along the model learning stage to mold the historical data to represent operators' context related to the process through possibility distributions. This model was evaluated in two real case studies for quality prediction, including a sulfur recovery unit and a polymerization process. The contextual mixture of experts was employed to represent different contexts in both experiments. The results indicate that integrating process knowledge has increased predictive performance while improving interpretability by providing insights into the variables affecting the process's different regimes

Molecular Level Characterization of Dissolved Organic Matter Integrating Trapped Ion Mobility Spectrometry and Fourier Transform Ion Cyclotron Resonance Mass Spectrometry

Dissolved organic matter (DOM) is an extremely complex mixture of organic molecules ubiquitous in aquatic systems and a critical component of the global carbon cycle. Little is known about DOM structural composition at the molecular level. The work presented in this dissertation summarizes the development of a novel analytical toolbox based on trapped ion mobility spectrometry and Fourier transform ion cyclotron resonance mass spectrometry (TIMS-FT-ICR MS) that has significantly contributed to expand our knowledge of DOM molecular complexity and diversity. The TIMS-FT-ICR MS/MS analysis provided for the first-time lower and upper estimation of the molecular isomeric diversity. The TIMS-FT-ICR MS/MS methodology was further developed to allow for chemical formula-based isomeric and neutral loss fragmentation structural description and database validation. This novel procedure enabled the unambiguous assignment of candidate isomeric structures based on accurate mass, database MS/MS matching scores, and ion mobility. A fast and routine structural characterization DOM workflow method was developed: GraphDOM. The method utilizes neutral loss fragmentation patterns acquired using continuous accumulation of selected ions (CASI)-collision induced dissociation (CID) FT-ICR MS/MS. The neutral mass loss patterns are used to define structural families leading to the identification and visualization of the DOM transformational processes. The GraphDOM methodology was successfully applied to the characterization of DOM along a salinity transect of the Harney River, Florida Everglades. The GraphDOM method was further implemented with isomeric content description at the molecular level and applied to four common aquatic systems. The application of the GraphDOM methodology allowed for the first time identification of common and unique DOM transformational networks across aquatic ecosystems