A Comparison of the Pac-X Trans-Pacific Wave Glider Data and Satellite Data (MODIS, Aquarius, TRMM and VIIRS)

Tracy A. Villareal, Marine Science Institute and Department of Marine Science, The University of Texas at Austin, Port Aransas, Texas, United States of AmericaCara Wilson, Environmental Research Division, Southwest Fisheries Science Center, National Marine Fisheries Service, NOAA, Pacific Grove, California, United States of AmericaFour wave-propelled autonomous vehicles (Wave Gliders) instrumented with a variety of oceanographic and meteorological sensors were launched from San Francisco, CA in November 2011 for a trans-Pacific (Pac-X) voyage to test platform endurance. Two arrived in Australia, one in Dec 2012 and one in February 2013, while the two destined for Japan both ran into technical difficulties and did not arrive at their destination. The gliders were all equipped with sensors to measure temperature, salinity, turbidity, oxygen, and both chlorophyll and oil fluorescence. Here we conduct an initial assessment of the data set, noting necessary quality control steps and instrument utility. We conduct a validation of the Pac-X dataset by comparing the glider data to equivalent, or near-equivalent, satellite measurements. Sea surface temperature and salinity compared well to satellite measurements. Chl fluorescence from the gliders was more poorly correlated, with substantial between glider variability. Both turbidity and oil CDOM sensors were compromised to some degree by interfering processes. The well-known diel cycle in chlorophyll fluorescence was observed suggesting that mapping physiological data over large scales is possible. The gliders captured the Pacific Ocean’s major oceanographic features including the increased chlorophyll biomass of the California Current and equatorial upwelling. A comparison of satellite sea surface salinity (Aquarius) and glider-measured salinity revealed thin low salinity lenses in the southwestern Pacific Ocean. One glider survived a direct passage through a tropical cyclone. Two gliders traversed an open ocean phytoplankton bloom; extensive spiking in the chlorophyll fluorescence data is consistent with aggregation and highlights another potential future use for the gliders. On long missions, redundant instrumentation would aid in interpreting unusual data streams, as well as a means to periodically image the sensor heads. Instrument placement is critical to minimize bubble-related problems in the data.The authors have no support or funding to report.Marine ScienceEmail: [email protected]

Advances in fault diagnosis for high-speed railway: A review

The high speed railway (HSR) is a complex system with many subsystems and components. The reliability of its core subsystems is a key consideration in ensuring the safety and operation efficiency of the whole system. As the service time increases, the degradation of these subsystems and components may lead to a range of faults and deteriorate the whole system performance. To ensure the operation safety and to develop reasonable maintenance strategies, fault detection and isolation is an indispensable functionality in high speed railway systems. In this paper, the traction power supply system, bogie system, civil infrastructure system, and control and signaling system of HSR are briefly summarized, and then different fault diagnosis methods for these subsystems are comprehensively reviewed. Finally, some future research topics are discussed

Exploring the application of ultrasonic phased arrays for industrial process analysis

This thesis was previously held under moratorium from 25/11/19 to 25/11/21Typical industrial process analysis techniques require an optical path to exist between the measurement sensor and the process to acquire data used to optimise and control an industrial process. Ultrasonic sensing is a well-established method to measure into optically opaque structures and highly focussed images can be generated using multiple element transducer arrays. In this Thesis, such arrays are explored as a real-time imaging tool for industrial process analysis. A novel methodology is proposed to characterise the variation between consecutive ultrasonic data sets deriving from the ultrasonic hardware. The pulse-echo response corresponding to a planar back wall acoustic interface is used to infer the bandwidth, pulse length and sensitivity of each array element. This led to the development of a calibration methodology to enhance the accuracy of experimentally generated ultrasonic images. An algorithm enabling non-invasive through-steel imaging of an industrial process is demonstrated using a simulated data set. Using principal component analysis, signals corresponding to reverberations in the steel vessel wall are identified and deselected from the ultrasonic data set prior to image construction. This facilitates the quantification of process information from the image. An image processing and object tracking algorithm are presented to quantify the bubble size distribution (BSD) and bubble velocity from ultrasonic images. When tested under controlled dynamic conditions, the mean value of the BSD was predicted within 50% at 100 mms-1 and the velocity could be predicted within 30% at 100 mms-1. However, these algorithms were sensitive to the quality of the input image to represent the true bubble shape. The consolidation of these techniques demonstrates successful application of ultrasonic phased array imaging, both invasively and noninvasively, to a dynamic process stream. Key to industrial uptake of the technology are data throughput and processing, which currently limit its applicability to real-time process analysis, and low sensitivity for some non-invasive applications.Typical industrial process analysis techniques require an optical path to exist between the measurement sensor and the process to acquire data used to optimise and control an industrial process. Ultrasonic sensing is a well-established method to measure into optically opaque structures and highly focussed images can be generated using multiple element transducer arrays. In this Thesis, such arrays are explored as a real-time imaging tool for industrial process analysis. A novel methodology is proposed to characterise the variation between consecutive ultrasonic data sets deriving from the ultrasonic hardware. The pulse-echo response corresponding to a planar back wall acoustic interface is used to infer the bandwidth, pulse length and sensitivity of each array element. This led to the development of a calibration methodology to enhance the accuracy of experimentally generated ultrasonic images. An algorithm enabling non-invasive through-steel imaging of an industrial process is demonstrated using a simulated data set. Using principal component analysis, signals corresponding to reverberations in the steel vessel wall are identified and deselected from the ultrasonic data set prior to image construction. This facilitates the quantification of process information from the image. An image processing and object tracking algorithm are presented to quantify the bubble size distribution (BSD) and bubble velocity from ultrasonic images. When tested under controlled dynamic conditions, the mean value of the BSD was predicted within 50% at 100 mms-1 and the velocity could be predicted within 30% at 100 mms-1. However, these algorithms were sensitive to the quality of the input image to represent the true bubble shape. The consolidation of these techniques demonstrates successful application of ultrasonic phased array imaging, both invasively and noninvasively, to a dynamic process stream. Key to industrial uptake of the technology are data throughput and processing, which currently limit its applicability to real-time process analysis, and low sensitivity for some non-invasive applications

Solitonic State in Microscopic Dynamic Failures

Onset of permanent deformation in crystalline materials under a sharp indenter tip is accompanied by nucleation and propagation of defects. By measuring the spatio-temporal strain field nearthe indenter tip during indentation tests, we demonstrate that the dynamic strain history at the moment of a displacement burst carries characteristics of formation and interaction of local excitations, or solitons. We show that dynamic propagation of multiple solitons is followed by a short time interval where the propagating fronts can accelerate suddenly. As a result of such abrupt local accelerations, duration of the fast-slip phase of a failure event is shortened. Our results show that formation and annihilation of solitons mediate the microscopic fast weakening phase, during which extreme acceleration and collision of solitons lead to non-Newtonian behavior and Lorentz contraction, i.e., shortening of solitons characteristic length. The results open new horizons for understanding dynamic material response during failure and, more generally, complexity of earthquake sources

Bridges Structural Health Monitoring and Deterioration Detection Synthesis of Knowledge and Technology

INE/AUTC 10.0

The role of multi-scale phase synchronization and cross-frequency interactions in cognitive integration

Neuronal processing is distributed into anatomically distinct, largely specialized, neuronal populations. These populations undergo rhythmic fluctuations in excitability, which are commonly known as neuronal oscillations. Electrophysiological studies of neuronal activity have shown that phase synchronization of oscillations within frequencies characterizes both resting state and task execution and that its strength is correlated with task performance. Therefore phase-synchronization within frequencies is thought to support communication between oscillating neuronal populations and thereby integration and coordination of anatomically distributed processing in cognitive functions. However, it has remained open if and how phase synchronization is associated with directional flow of information. Furthermore, oscillations and synchronization are observed concurrently in multiple frequencies, which are thought to underlie distinct computational functions. Little is known how oscillations and synchronized networks of different frequencies in the human brain are integrated and enable unified cognitive function and experience. In the first study of this thesis, we developed a measure of directed connectivity in networks of coupled oscillators, called Phase Transfer Entropy (Phase TE) and tested if Phase TE could detect directional flow in simulated data in the presence of noise and signal mixing. Results showed that Phase TE indeed reliably detected information flow under these conditions and was computationally efficient. In the other three studies, we investigated if two different forms of inter-areal cross-frequency coupling (CFC), namely cross-frequency phase synchrony (CFS) and phase-amplitude coupling (PAC), could support integration and coordination of neuronal processing distributed across frequency bands in the human brain. In the second study, we analyzed source-reconstructed magneto- and electroencephalographic (M/EEG) data to investigate whether inter-areal CFS could be observed between within-frequency synchronized networks and thereby support the coordination of spectrally distributed processing in visual working memory (VWM). The results showed that CFS was increased during VWM maintenance among theta to gamma frequency bands and the strength of CFS networks predicted individual VWM capacity. Spectral patterns of CFS were found to be different from PAC, indicating complementary roles for both mechanisms. In the third study, we analyzed source-reconstructed M/EEG data to investigate whether inter-areal CFS and PAC could be observed during two multi-object visual tracking tasks and thereby support visual attention. PAC was found to be significantly correlated with object load in both tasks, and CFS in one task. Further, patterns of CFS and PAC differed significantly between subjects with high and low capacity for visual attention. In the fourth study, we analyzed intracerebral stereo-electroencephalographic data (SEEG) and source-reconstructed MEG data to investigate whether CFS and PAC are present also in resting state. Further, in order to address concerns about observations of CFC being spurious and caused by non-sinusoidal or non-zero mean signal waveforms, we introduced a new approach to identify true inter-areal CFC connections and discard potentially spurious ones. We observed both inter-areal CFS and PAC, and showed that a significant part of connections was unambiguously true and non-spurious. Spatial profiles differed between CFS and PAC, but were consistent across datasets. Together, the results from studies II-IV provide evidence that inter-areal CFS and PAC, in complementary ways, connect frequency-specific phase-synchronized networks that involve functionally specialized regions across the cortex to support complex functions such as VWM and attention, and also characterize the resting state. Inter-areal CFC thus may be crucial for the coordination and integration of spectrally distributed processing and the emergence of introspectively coherent cognitive function.Keskeinen kysymys aivotutkimuksessa on, kuinka ajattelu ja kognitio syntyvät ihmisaivojen 10^15 hermosolussa. Informaation käsittely aivoissa tapahtuu suurissa hermosolupopulaatioissa, jotka ovat toiminnallisesti erikoistuneita ja anatomisesti eroteltuja eri aivoalueille. Niiden aktivaatiorakenteiden jaksollisia muutoksia kutsutaan aivorytmeiksi eli oskillaatioiksi. Hermosolupopulaatioiden välistä viestintää edesauttaa niiden toiminnan samantahtisuus eli synkronoituminen. Sähköfysiologisissa tutkimuksissa on havaittu aivorytmien synkronoituvan sekä lepomittausten että tehtävien suorituksen aikana siten että tämä synkronoituminen ennustaa kognitiivissa tehtävissä suoriutumista. Oskillaatioiden vaihesynkronia ei kuitenkaan kerro niiden välisen vuorovaikutuksen suunnasta. Tämän lisäksi oskillaatioita ja niiden välistä synkroniaa havaitaan yhtäaikaisesti lukuisilla eri taajuuksilla, joiden ajatellaan olevan vastuussa erillisistä laskennallisista ja kognitiivisista toiminnoista. Toistaiseksi on kuitenkin jäänyt kartoittamatta, miten informaation käsittely eri taajuuksilla yhdistetään yhtenäisiksi kognitiivisiksi toiminnoiksi, ja havaitaanko myös eri taajuisten oskillaatioverkkojen välillä synkroniaa. Väitöskirjan ensimmäisessä osatyössä on kehitetty uusi tapata mitata oskillaattoriverkkojen vuorovaikutusten suuntia, jonka toimivuus todennettiin simuloimalla synkronoituneita hermosolupopulaatioita. Väitöskirjan muissa osatöissä on tutkittu havaitaanko ihmisaivoissa eri taajuisten oskillaatioiden välistä synkronoitumista. Erityisesti tutkittiin kahta erilaista synkronian muotoa, joista ensimmäinen (’cross- frequency phase synchrony’,CFS) mittaa kahden oskillaation välistä vaihesuhdetta ja toinen (’phase-amplitude coupling’, PAC) vaiheen ja amplitudin suhdetta. Väitöskirjan toisessa osassa tutkittiin, selittääkö CFS koehenkilöiden suoriutumista näkötyömuistitehtävässä. Tutkimukseen osallistuneilta koehenkilöiltä mitattiin aivosähkökäyrä (EEG) ja aivomagneettikäyrä (MEG), joiden avulla selvitettiin havaitaanko aivoalueiden välistä synkroniaa (CFS). Tutkimustulokset osoittivat, että koehenkilöiden CFS oli korkeampi näkötyömuistitehtävän mielessä pitämisen aikana theta-taajuuksista gamma-taajuuksiin asti ja että CFS-verkkojen vahvuus ennusti yksilöllistä työmuistikapasiteettia. Kolmannessa tutkimuksessa analysoitiin MEG- ja EEG-aivokuvantamislaitteita käyttäen onko aivoalueiden välillä CFS:ä ja PAC:a kahdessa näkötarkkaavaisuustehtävässä. PAC lisääntyi tilastollisesti merkitsevästi tehtävän vaikeuden mukaan kummassakin tehtävässä, kun taas CFS lisääntyi yhdessä tehtävässä. Lisäksi CFS ja PAC taajuusparit olivat erilaisia hyvin suoriutuvien koehenkilöiden sekä heikosti suoriutuvien koehenkilöiden välillä. Neljännessä tutkimuksessa tutkittiin havaitaanko CFS:ä ja PAC:a aivojen lepotilassa. Aivokuoren aktiivisuutta mitattiin MEG:llä sekä epilepsiapotilailta aivoihin kirurgisesti asetetuilla elektrodeilla. CFS:ä sekä PAC:a havaittiin kummallakin menetelmällä. Lisäksi kehitimme menetelmän joka vähentää väärien havaintojen todennäköisyyttä ja lisää aitojen CFS ja PAC yhteyksien havaitsemista. Tulokset osoittavat, että merkittävä osuus yhteyksistä aivoalueiden välillä on aitoja. CFS- ja PAC-profiilit erosivat toisistaan, mutta olivat samanlaisia eri menetelmillä tutkittaessa. Yhdistettynä tulokset tutkimuksista II–IV viittaavat siihen, että CFS ja PAC yhdistävät eri taajuuksille ja aivoalueille hajautettua informaation käsittelyä. CFS:sää ja PAC:ia havaittiin aivojen lepotilassa mutta myös tarkkaavaisuus- ja näkötyömuistitehtävän aikana. CFS ja PAC saattavat mahdollistaa eri taajuisten aivorytmien ja hajautettujen prosessien koordinaation ja yhdistämisen