Downwelling spectral irradiance as measured in different depths, remote sensing reflectance and phytoplankton pigment concentration during POLARSTERN cruises ANT-XXIV/1, ANT-XXIV/4, ANT-XXVI/4 and Maria S. Merian cruise MSM18/3

The composition and abundance of algal pigments provide information on phytoplankton community characteristics such as photoacclimation, overall biomass and taxonomic composition. In particular, pigments play a major role in photoprotection and in the light-driven part of photosynthesis. Most phytoplankton pigments can be measured by high-performance liquid chromatography (HPLC) techniques applied to filtered water samples. This method, as well as other laboratory analyses, is time consuming and therefore limits the number of samples that can be processed in a given time. In order to receive information on phytoplankton pigment composition with a higher temporal and spatial resolution, we have developed a method to assess pigment concentrations from continuous optical measurements. The method applies an empirical orthogonal function (EOF) analysis to remote-sensing reflectance data derived from ship-based hyperspectral underwater radiometry and from multispectral satellite data (using the Medium Resolution Imaging Spectrometer - MERIS - Polymer product developed by Steinmetz et al., 2011, doi:10.1364/OE.19.009783) measured in the Atlantic Ocean. Subsequently we developed multiple linear regression models with measured (collocated) pigment concentrations as the response variable and EOF loadings as predictor variables. The model results show that surface concentrations of a suite of pigments and pigment groups can be well predicted from the ship-based reflectance measurements, even when only a multispectral resolution is chosen (i.e., eight bands, similar to those used by MERIS). Based on the MERIS reflectance data, concentrations of total and monovinyl chlorophyll a and the groups of photoprotective and photosynthetic carotenoids can be predicted with high quality. As a demonstration of the utility of the approach, the fitted model based on satellite reflectance data as input was applied to 1 month of MERIS Polymer data to predict the concentration of those pigment groups for the whole eastern tropical Atlantic area. Bootstrapping explorations of cross-validation error indicate that the method can produce reliable predictions with relatively small data sets (e.g., < 50 collocated values of reflectance and pigment concentration). The method allows for the derivation of time series from continuous reflectance data of various pigment groups at various regions, which can be used to study variability and change of phytoplankton composition and photophysiology.

Methane fluxes and carbonate deposits at eastern Mediterranean cold seeps

High acoustic seafloor-backscatter signals characterize hundreds of patches of methane-derived authigenic carbonates and chemosynthetic communities associated with hydrocarbon seepage on the Nile Deep Sea Fan (NDSF) in the Eastern Mediterranean Sea. During a high-resolution ship-based multibeam survey covering a ~ 225 km**2 large seafloor area in the Central Province of the NDSF we identified 163 high-backscatter patches at water depths between 1500 and 1800 m, and investigated the source, composition, turnover, flux and fate of emitted hydrocarbons. Systematic Parasound single beam echosounder surveys of the water column showed hydroacoustic anomalies (flares), indicative of gas bubble streams, above 8% of the high-backscatter patches. In echosounder records flares disappeared in the water column close to the upper limit of the gas hydrate stability zone located at about 1350 m water depth due to decomposition of gas hydrate skins and subsequent gas dissolution. Visual inspection of three high-backscatter patches demonstrated that sediment cementation has led to the formation of continuous flat pavements of authigenic carbonates typically 100 to 300 m in diameter. Volume estimates, considering results from high-resolution autonomous underwater vehicle (AUV)-based multibeam mapping, were used to calculate the amount of carbonate-bound carbon stored in these slabs. Additionally, the flux of methane bubbles emitted at one high-backscatter patch was estimated (0.23 to 2.3 × 10**6 mol a**-1) by combined AUV flare mapping with visual observations by remotely operated vehicle (ROV). Another high-backscatter patch characterized by single carbonate pieces, which were widely distributed and interspaced with sediments inhabited by thiotrophic, chemosynthetic organisms, was investigated using in situ measurements with a benthic chamber and ex situ sediment core incubation and allowed for estimates of the methane consumption (0.1 to 1 × 10**6 mol a**-1) and dissolved methane flux (2 to 48 × 10**6 mol a**-1). Our comparison of dissolved and gaseous methane fluxes as well as methane-derived carbonate reservoirs demonstrates the need for quantitative assessment of these different methane escape routes and their interaction with the geo-, bio-, and hydrosphere at cold seeps.

Gridded results of swath bathymetric mapping of Disko Bay, Western Greenland, 2007-2008

A ship-based acoustic mapping campaign was conducted at the exit of Ilulissat Ice Fjord and in the sedimentary basin of Disko Bay to the west of the fjord mouth. Submarine landscape and sediment distribution patterns are interpreted in terms of glaciomarine facies types that are related to variations in the past position of the glacier front. In particular, asymmetric ridges that form a curved entity and a large sill at the fjord mouth may represent moraines that depict at least two relatively stable positions of the ice front in the Disko Bay and at the fjord mouth. In this respect, Ilulissat Glacier shows prominent differences to the East Greenland Kangerlussuaq Glacier which is comparable in present size and present role for the ice discharge from the inland ice sheet. Two linear clusters of pockmarks in the center of the sedimentary basin seem to be linked to ongoing methane release due to dissociation of gas hydrates, a process fueled by climate warming in the Arctic realm.

Axis Mapping: The Estimation of Surface Orientations and its Applications in Vehicle Localization and Structural Geology

The map representation of an environment should be selected based on its intended application. For example, a geometrically accurate map describing the Euclidean space of an environment is not necessarily the best choice if only a small subset its features are required. One possible subset is the orientations of the flat surfaces in the environment, represented by a special parameterization of normal vectors called axes. Devoid of positional information, the entries of an axis map form a non-injective relationship with the flat surfaces in the environment, which results in physically distinct flat surfaces being represented by a single axis. This drastically reduces the complexity of the map, but retains important information about the environment that can be used in meaningful applications in both two and three dimensions. This thesis presents axis mapping, which is an algorithm that accurately and automatically estimates an axis map of an environment based on sensor measurements collected by a mobile platform. Furthermore, two major applications of axis maps are developed and implemented. First, the LiDAR compass is a heading estimation algorithm that compares measurements of axes with an axis map of the environment. Pairing the LiDAR compass with simple translation measurements forms the basis for an accurate two-dimensional localization algorithm. It is shown that this algorithm eliminates the growth of heading error in both indoor and outdoor environments, resulting in accurate localization over long distances. Second, in the context of geotechnical engineering, a three-dimensional axis map is called a stereonet, which is used as a tool to examine the strength and stability of a rock face. Axis mapping provides a novel approach to create accurate stereonets safely, rapidly, and inexpensively compared to established methods. The non-injective property of axis maps is leveraged to probabilistically describe the relationships between non-sequential measurements of the rock face. The automatic estimation of stereonets was tested in three separate outdoor environments. It is shown that axis mapping can accurately estimate stereonets while improving safety, requiring significantly less time and effort, and lowering costs compared to traditional and current state-of-the-art approaches.

Breaking Waves on the Ocean Surface

Thesis (Ph.D.)--University of Washington, 2016-08

IntelliChair: a non-intrusive sitting posture and sitting activity recognition system

Current Ambient Intelligence and Intelligent Environment research focuses on the interpretation of a subject’s behaviour at the activity level by logging the Activity of Daily Living (ADL) such as eating, cooking, etc. In general, the sensors employed (e.g. PIR sensors, contact sensors) provide low resolution information. Meanwhile, the expansion of ubiquitous computing allows researchers to gather additional information from different types of sensor which is possible to improve activity analysis. Based on the previous research about sitting posture detection, this research attempts to further analyses human sitting activity. The aim of this research is to use non-intrusive low cost pressure sensor embedded chair system to recognize a subject’s activity by using their detected postures. There are three steps for this research, the first step is to find a hardware solution for low cost sitting posture detection, second step is to find a suitable strategy of sitting posture detection and the last step is to correlate the time-ordered sitting posture sequences with sitting activity. The author initiated a prototype type of sensing system called IntelliChair for sitting posture detection. Two experiments are proceeded in order to determine the hardware architecture of IntelliChair system. The prototype looks at the sensor selection and integration of various sensor and indicates the best for a low cost, non-intrusive system. Subsequently, this research implements signal process theory to explore the frequency feature of sitting posture, for the purpose of determining a suitable sampling rate for IntelliChair system. For second and third step, ten subjects are recruited for the sitting posture data and sitting activity data collection. The former dataset is collected byasking subjects to perform certain pre-defined sitting postures on IntelliChair and it is used for posture recognition experiment. The latter dataset is collected by asking the subjects to perform their normal sitting activity routine on IntelliChair for four hours, and the dataset is used for activity modelling and recognition experiment. For the posture recognition experiment, two Support Vector Machine (SVM) based classifiers are trained (one for spine postures and the other one for leg postures), and their performance evaluated. Hidden Markov Model is utilized for sitting activity modelling and recognition in order to establish the selected sitting activities from sitting posture sequences.2. After experimenting with possible sensors, Force Sensing Resistor (FSR) is selected as the pressure sensing unit for IntelliChair. Eight FSRs are mounted on the seat and back of a chair to gather haptic (i.e., touch-based) posture information. Furthermore, the research explores the possibility of using alternative non-intrusive sensing technology (i.e. vision based Kinect Sensor from Microsoft) and find out the Kinect sensor is not reliable for sitting posture detection due to the joint drifting problem. A suitable sampling rate for IntelliChair is determined according to the experiment result which is 6 Hz. The posture classification performance shows that the SVM based classifier is robust to “familiar” subject data (accuracy is 99.8% with spine postures and 99.9% with leg postures). When dealing with “unfamiliar” subject data, the accuracy is 80.7% for spine posture classification and 42.3% for leg posture classification. The result of activity recognition achieves 41.27% accuracy among four selected activities (i.e. relax, play game, working with PC and watching video). The result of this thesis shows that different individual body characteristics and sitting habits influence both sitting posture and sitting activity recognition. In this case, it suggests that IntelliChair is suitable for individual usage but a training stage is required.

Panossyöttökasvatusprosessin automatisointi

Tutkimuskäyttöön tarkoitettujen rekombinanttiproteiinien tuottaminen fermentoimalla on yleinen menetelmä bioteollisuudessa. Mikrobit kasvatetaan fermentorissa, joka tarjoaa kontrolloidun kasvuympäristön ja sopivat tuotto-olosuhteet halutulle tuotteelle. Eräs fermentointimuodoista on korkeatuottoinen ja pitkäkestoinen panossyöttökasvatus, jossa saavutetaan panoskavatusta merkittävästi korkeampi solutiheys jatkamalla panosvaiheen jälkeen kasvua rajoittavan substraatin syöttöä. Laboratoriomittakaavassa fermentorikasvatusten tilavuudet vaihtelevat litrasta kymmeniin ja niissä kasvatusta seurataan sekä ohjataan joko fermentorista tai tietokoneesta. Tyypillisessä fermentointiprosessissa operaattori tarkkailee muun muassa vaahdonkorkeutta sekä käynnistää pumppuja olosuhteiden muuttuessa. Tällaiset tehtävät ovat teollisen mittakaavan laitteistoissa usein automatisoituja. Diplomityön tarkoituksena oli päivittää kahden Turun yliopiston biotekniikan laboratoriossa sijaitsevan BioFlo® -sarjan pöytäfermentorin MS-DOS -pohjainen tietokoneohjausohjelma nykyaikaiseksi ja lisätä siihen etäseuranta ja -ohjaus. Ohjelmaan oli tarkoitus liittää erillinen optinen solutiheysanturi, jonka lukemien häiriötä haluttiin myös vähentää signaalinkäsittelyllä. Lisäksi vaahdonestoaineen ja indusorin lisäykset haluttiin automatisoida panossyöttökasvatuksessa. Vaahdonkorkeuden havaitsemisen mahdollisuutta konenäön menetelmin haluttiin selvittää, jotta vaahdonestoaineen automaattiset lisäykset voitaisiin toteuttaa nettikameran syötteen perusteella. Koekasvatuksilla osoitettiin päivitetyn ohjausohjelman toimivan panos- ja panossyöttömuodoilla. Uuden käyttöliittymän avulla pystyttiin automatisoimaan panoskasvatuksen lisäykset ja syöttönopeuden muutokset sekä tunnistamaan kasvatusliuosten vaahdonkorkeutta vaahdonestoaineen lisäykseen riittävällä kahden senttimetrin tarkkuudella. Lisäksi käyttöliittymä mahdollisti kasvatuksen ohjauksen ja seurauksen myös etänä. Työssä kehitetty ohjausohjelma julkaistiin avoimena ohjelmana ilman etä- ja nettikameratoimintoja. Ohjelma toimii hyvin BioFlo® -sarjan fermentorien käyttöliittymänä, mutta avoimen lähdekoodin ansiosta kuka tahansa voi hyödyntää ohjelmaa pohjana myös uusissa projekteissa tai muissa fermentorimalleissa.

Integration of virus-like particle macromolecular bioreceptors in electrochemical biosensors

Rapid, sensitive and selective detection of chemical hazards and biological pathogens has shown growing importance in the fields of homeland security, public safety and personal health. In the past two decades, efforts have been focusing on performing point-of-care chemical and biological detections using miniaturized biosensors. These sensors convert target molecule binding events into measurable electrical signals for quantifying target molecule concentration. However, the low receptor density and the use of complex surface chemistry in receptors immobilization on transducers are common bottlenecks in the current biosensor development, adding to the cost, complexity and time. This dissertation presents the development of selective macromolecular Tobacco mosaic virus-like particle (TMV VLP) biosensing receptor, and the microsystem integration of VLPs in microfabricated electrochemical biosensors for rapid and performance-enhanced chemical and biological sensing. Two constructs of VLPs carrying different receptor peptides targeting at 2,4,6-trinitrotoluene (TNT) explosive or anti-FLAG antibody are successfully bioengineered. The VLP-based TNT electrochemical sensor utilizes unique diffusion modulation method enabled by biological binding between target TNT and receptor VLP. The method avoids the influence from any interfering species and environmental background signals, making it extremely suitable for directly quantifying the TNT level in a sample. It is also a rapid method that does not need any sensor surface functionalization process. For antibody sensing, the VLPs carrying both antibody binding peptides and cysteine residues are assembled onto the gold electrodes of an impedance microsensor. With two-phase immunoassays, the VLP-based impedance sensor is able to quantify antibody concentrations down to 9.1 ng/mL. A capillary microfluidics and impedance sensor integrated microsystem is developed to further accelerate the process of VLP assembly on sensors and improve the sensitivity. Open channel capillary micropumps and stop-valves facilitate localized and evaporation-assisted VLP assembly on sensor electrodes within 6 minutes. The VLP-functionalized impedance sensor is capable of label-free sensing of antibodies with the detection limit of 8.8 ng/mL within 5 minutes after sensor functionalization, demonstrating great potential of VLP-based sensors for rapid and on-demand chemical and biological sensing.

L’épave du Machault, 1760 : entre tradition et innovation.

Cette étude s’intéresse à l’industrie de la construction navale pour le milieu du XVIIIe siècle en France dans la région de Bayonne. L’objectif est de documenter la relation qu’entretiennent les pratiques de construction traditionnelles et innovatrices à cette période. L’architecture de la frégate le Machault est au cœur de cette analyse. Construit en 1757 à Bayonne et perdu en 1760, le Machault a été fouillé, documenté et parallèlement récupéré par les archéologues de Parcs Canada entre 1969 et 1972 à Ristigouche dans la baie des Chaleurs, Québec. Cette étude constitue la première analyse architecturale approfondie menée sur ces vestiges. L’analyse est réalisée en trois temps qui correspondent aux trois grandes étapes de la chaine opératoire de la construction du navire. Tout d’abord, il est question d’aborder l’aspect de la foresterie afin de saisir la nature de la ressource forestière mobilisée pour la construction de la frégate. Ensuite, ce mémoire se penche sur la conception architecturale des navires qui renvoie à un aspect plus théorique, car il relève de la façon dont les formes du navire ont été « pensées ». Enfin, la charpenterie est abordée afin de saisir la séquence d’assemblage du navire. Ensemble, ces trois grands aspects dressent un portrait général de la construction navale pour la région de Bayonne au milieu du XVIIIe siècle.

L’épave du Machault, 1760 : entre tradition et innovation

Cette étude s’intéresse à l’industrie de la construction navale pour le milieu du XVIIIe siècle en France dans la région de Bayonne. L’objectif est de documenter la relation qu’entretiennent les pratiques de construction traditionnelles et innovatrices à cette période. L’architecture de la frégate le Machault est au cœur de cette analyse. Construit en 1757 à Bayonne et perdu en 1760, le Machault a été fouillé, documenté et parallèlement récupéré par les archéologues de Parcs Canada entre 1969 et 1972 à Ristigouche dans la baie des Chaleurs, Québec. Cette étude constitue la première analyse architecturale approfondie menée sur ces vestiges. L’analyse est réalisée en trois temps qui correspondent aux trois grandes étapes de la chaine opératoire de la construction du navire. Tout d’abord, il est question d’aborder l’aspect de la foresterie afin de saisir la nature de la ressource forestière mobilisée pour la construction de la frégate. Ensuite, ce mémoire se penche sur la conception architecturale des navires qui renvoie à un aspect plus théorique, car il relève de la façon dont les formes du navire ont été « pensées ». Enfin, la charpenterie est abordée afin de saisir la séquence d’assemblage du navire. Ensemble, ces trois grands aspects dressent un portrait général de la construction navale pour la région de Bayonne au milieu du XVIIIe siècle.

Development of textile wearable chemical sensors

In this elaborate, a textile-based Organic Electrochemical Transistor (OECT) was first developed for the determination of uric acid in wound exudate based on the conductive polymer poly(3,4-ethylenedioxythiophene):polystyrene sulfonate (PEDOT:PSS), which was then coupled to an electrochemically gated textile transistor consisting of a composite of iridium oxide particles and PEDOT:PSS for pH monitoring in wound exudate. In that way a sensor for multiparameter monitoring of wound health status was assembled, including the ability to differentiate between a wet-dry status of the smart bandage by implementing impedance measurements exploiting the OECT architecture. Afterwards, for both wound management as well as generic health status tracking applications, a glass-based calcium sensor was developed employing polymeric ion-selective membranes on a novel architecture inspired by the Wrighton OECT configuration, which was later converted to a Proof-of-Concept textile prototype for wearable applications. Lastly, in collaboration with the King Abdullah University of Science and Technology (KAUST, Thuwal, Saudi Arabia) under the supervision of Prof. Sahika Inal, different types of ion-selective thiophene-based monomers were used to develop ion-selective conductive polymers to detect sodium ion by different methods, involving standard potentiometry and OECT-based approaches. The textile OECTs for uric acid detection performances were optimized by investigating the geometry effect on the instrumental response and the properties of the different textile materials involved in their production, with a special focus on the final application that implies the operativity in flow conditions to simulate the wound environment. The same testing route was followed for the multiparameter sensor and the calcium sensor prototype, with a particular care towards the ion-selective membrane composition and electrode conditioning protocol optimization. The sodium-selective polymer electrosynthesis was optimized in non-aqueous environments and was characterized by means of potentiostatic and potentiodynamic techniques coupled with Quartz Crystal Microbalance and spectrophotometric measurements.

Kernel-based Mapping of Meteorological Fields in Complex Orography

Due to the advances in sensor networks and remote sensing technologies, the acquisition and storage rates of meteorological and climatological data increases every day and ask for novel and efficient processing algorithms. A fundamental problem of data analysis and modeling is the spatial prediction of meteorological variables in complex orography, which serves among others to extended climatological analyses, for the assimilation of data into numerical weather prediction models, for preparing inputs to hydrological models and for real time monitoring and short-term forecasting of weather.In this thesis, a new framework for spatial estimation is proposed by taking advantage of a class of algorithms emerging from the statistical learning theory. Nonparametric kernel-based methods for nonlinear data classification, regression and target detection, known as support vector machines (SVM), are adapted for mapping of meteorological variables in complex orography.With the advent of high resolution digital elevation models, the field of spatial prediction met new horizons. In fact, by exploiting image processing tools along with physical heuristics, an incredible number of terrain features which account for the topographic conditions at multiple spatial scales can be extracted. Such features are highly relevant for the mapping of meteorological variables because they control a considerable part of the spatial variability of meteorological fields in the complex Alpine orography. For instance, patterns of orographic rainfall, wind speed and cold air pools are known to be correlated with particular terrain forms, e.g. convex/concave surfaces and upwind sides of mountain slopes.Kernel-based methods are employed to learn the nonlinear statistical dependence which links the multidimensional space of geographical and topographic explanatory variables to the variable of interest, that is the wind speed as measured at the weather stations or the occurrence of orographic rainfall patterns as extracted from sequences of radar images. Compared to low dimensional models integrating only the geographical coordinates, the proposed framework opens a way to regionalize meteorological variables which are multidimensional in nature and rarely show spatial auto-correlation in the original space making the use of classical geostatistics tangled.The challenges which are explored during the thesis are manifolds. First, the complexity of models is optimized to impose appropriate smoothness properties and reduce the impact of noisy measurements. Secondly, a multiple kernel extension of SVM is considered to select the multiscale features which explain most of the spatial variability of wind speed. Then, SVM target detection methods are implemented to describe the orographic conditions which cause persistent and stationary rainfall patterns. Finally, the optimal splitting of the data is studied to estimate realistic performances and confidence intervals characterizing the uncertainty of predictions.The resulting maps of average wind speeds find applications within renewable resources assessment and opens a route to decrease the temporal scale of analysis to meet hydrological requirements. Furthermore, the maps depicting the susceptibility to orographic rainfall enhancement can be used to improve current radar-based quantitative precipitation estimation and forecasting systems and to generate stochastic ensembles of precipitation fields conditioned upon the orography.

Charge measurements in stratiform cloud from a balloon based sensor

Abstract. The electrification of stratiform clouds has is little investigated in comparison with thunderstorms and fair weather atmospheric electricity. Theory indicates that, at the upper and lower horizontal boundaries of layer clouds, charging will arise from vertical flow of cosmogenic ions in the global atmospheric electric circuit. Charge is transferred to droplets and particles, affecting cloud microphysical processes such as collision and droplet activation. Due to the lack of in-situ measurements, the magnitude and distribution of charge in stratiform clouds is not well known. A sensitive, inexpensive, balloon borne charge sensor has been developed to make in-situ measurements of edge charging in stratiform cloud using a standard meteorological radiosonde system. The charge sensor has now been flown through over 20 stratiform clouds and frequently detected charge up to 200 pC m-3 near cloud edges. These results are compared with measurements from the same sensor used to investigate charge in particle layers, such as volcanic ash from the Eyjafjallajökull eruption, and Saharan dust in the Cape Verde Isles. 1.

Climatological observations from ship logbooks between 1750 and 1854 (release 2.1)

The Climatological Database for the World's Oceans: 1750-1854 (CLIWOC) project, which concluded in 2004, abstracted more than 280,000 daily weather observations from ships' logbooks from British, Dutch, French, and Spanish naval vessels engaged in imperial business in the eighteenth and nineteenth centuries. These data, now compiled into a database, provide valuable information for the reconstruction of oceanic wind field patterns for this key period that precedes the time in which anthropogenic influences on climate became evident. These reconstructions, in turn, provide evidence for such phenomena as the El Niño-Southern Oscillation and the North Atlantic Oscillation. Of equal importance is the finding that the CLIWOC database the first coordinated attempt to harness the scientific potential of this resource represents less than 10 percent of the volume of data currently known to reside in this important but hitherto neglected source.

Ihwg-μnir: A Miniaturised Near-infrared Gas Sensor Based On Substrate-integrated Hollow Waveguides Coupled To A Micro-nir-spectrophotometer.

A miniaturised gas analyser is described and evaluated based on the use of a substrate-integrated hollow waveguide (iHWG) coupled to a microsized near-infrared spectrophotometer comprising a linear variable filter and an array of InGaAs detectors. This gas sensing system was applied to analyse surrogate samples of natural fuel gas containing methane, ethane, propane and butane, quantified by using multivariate regression models based on partial least square (PLS) algorithms and Savitzky-Golay 1(st) derivative data preprocessing. The external validation of the obtained models reveals root mean square errors of prediction of 0.37, 0.36, 0.67 and 0.37% (v/v), for methane, ethane, propane and butane, respectively. The developed sensing system provides particularly rapid response times upon composition changes of the gaseous sample (approximately 2 s) due the minute volume of the iHWG-based measurement cell. The sensing system developed in this study is fully portable with a hand-held sized analyser footprint, and thus ideally suited for field analysis. Last but not least, the obtained results corroborate the potential of NIR-iHWG analysers for monitoring the quality of natural gas and petrochemical gaseous products.