Reconstruction of spatiotemporal capture data by means of orthogonal functions: the case of skipjack tuna (Katsuwonus pelamis) in the central-east Atlantic

[EN] The information provided by the International Commission for the Conservation of Atlantic Tunas (ICCAT) on captures of skipjack tuna (Katsuwonus pelamis) in the central-east Atlantic has a number of limitations, such as gaps in the statistics for certain fleets and the level of spatiotemporal detail at which catches are reported. As a result, the quality of these data and their effectiveness for providing management advice is limited. In order to reconstruct missing spatiotemporal data of catches, the present study uses Data INterpolating Empirical Orthogonal Functions (DINEOF), a technique for missing data reconstruction, applied here for the first time to fisheries data. DINEOF is based on an Empirical Orthogonal Functions decomposition performed with a Lanczos method. DINEOF was tested with different amounts of missing data, intentionally removing values from 3.4% to 95.2% of data loss, and then compared with the same data set with no missing data. These validation analyses show that DINEOF is a reliable methodological approach of data reconstruction for the purposes of fishery management advice, even when the amount of missing data is very high.

Validation of a numerical simulation of the North Atlantic Ocean with ARGO Data

Degree in Marine Sciences. Faculty of Marine Sciences, University of Las Palmas de Gran Canaria. Institut de Ciències del Mar, Consejo Superior de Investigaciones Científicas

The rupture process of recent tsunamigenic earthquakes by geophysical data inversion

Subduction zones are the favorite places to generate tsunamigenic earthquakes, where friction between oceanic and continental plates causes the occurrence of a strong seismicity. The topics and the methodologies discussed in this thesis are focussed to the understanding of the rupture process of the seismic sources of great earthquakes that generate tsunamis. The tsunamigenesis is controlled by several kinematical characteristic of the parent earthquake, as the focal mechanism, the depth of the rupture, the slip distribution along the fault area and by the mechanical properties of the source zone. Each of these factors plays a fundamental role in the tsunami generation. Therefore, inferring the source parameters of tsunamigenic earthquakes is crucial to understand the generation of the consequent tsunami and so to mitigate the risk along the coasts. The typical way to proceed when we want to gather information regarding the source process is to have recourse to the inversion of geophysical data that are available. Tsunami data, moreover, are useful to constrain the portion of the fault area that extends offshore, generally close to the trench that, on the contrary, other kinds of data are not able to constrain. In this thesis I have discussed the rupture process of some recent tsunamigenic events, as inferred by means of an inverse method. I have presented the 2003 Tokachi-Oki (Japan) earthquake (Mw 8.1). In this study the slip distribution on the fault has been inferred by inverting tsunami waveform, GPS, and bottom-pressure data. The joint inversion of tsunami and geodetic data has revealed a much better constrain for the slip distribution on the fault rather than the separate inversions of single datasets. Then we have studied the earthquake occurred on 2007 in southern Sumatra (Mw 8.4). By inverting several tsunami waveforms, both in the near and in the far field, we have determined the slip distribution and the mean rupture velocity along the causative fault. Since the largest patch of slip was concentrated on the deepest part of the fault, this is the likely reason for the small tsunami waves that followed the earthquake, pointing out how much the depth of the rupture plays a crucial role in controlling the tsunamigenesis. Finally, we have presented a new rupture model for the great 2004 Sumatra earthquake (Mw 9.2). We have performed the joint inversion of tsunami waveform, GPS and satellite altimetry data, to infer the slip distribution, the slip direction, and the rupture velocity on the fault. Furthermore, in this work we have presented a novel method to estimate, in a self-consistent way, the average rigidity of the source zone. The estimation of the source zone rigidity is important since it may play a significant role in the tsunami generation and, particularly for slow earthquakes, a low rigidity value is sometimes necessary to explain how a relatively low seismic moment earthquake may generate significant tsunamis; this latter point may be relevant for explaining the mechanics of the tsunami earthquakes, one of the open issues in present day seismology. The investigation of these tsunamigenic earthquakes has underlined the importance to use a joint inversion of different geophysical data to determine the rupture characteristics. The results shown here have important implications for the implementation of new tsunami warning systems – particularly in the near-field – the improvement of the current ones, and furthermore for the planning of the inundation maps for tsunami-hazard assessment along the coastal area.

Exchange of nitrogen dioxide (NO 2) between plants and the atmosphere under laboratory and field conditions

Nitrogen is an essential nutrient. It is for human, animal and plants a constituent element of proteins and nucleic acids. Although the majority of the Earth’s atmosphere consists of elemental nitrogen (N2, 78 %) only a few microorganisms can use it directly. To be useful for higher plants and animals elemental nitrogen must be converted to a reactive oxidized form. This conversion happens within the nitrogen cycle by free-living microorganisms, symbiotic living Rhizobium bacteria or by lightning. Humans are able to synthesize reactive nitrogen through the Haber-Bosch process since the beginning of the 20th century. As a result food security of the world population could be improved noticeably. On the other side the increased nitrogen input results in acidification and eutrophication of ecosystems and in loss of biodiversity. Negative health effects arose for humans such as fine particulate matter and summer smog. Furthermore, reactive nitrogen plays a decisive role at atmospheric chemistry and global cycles of pollutants and nutritive substances.rnNitrogen monoxide (NO) and nitrogen dioxide (NO2) belong to the reactive trace gases and are grouped under the generic term NOx. They are important components of atmospheric oxidative processes and influence the lifetime of various less reactive greenhouse gases. NO and NO2 are generated amongst others at combustion process by oxidation of atmospheric nitrogen as well as by biological processes within soil. In atmosphere NO is converted very quickly into NO2. NO2 is than oxidized to nitrate (NO3-) and to nitric acid (HNO3), which bounds to aerosol particles. The bounded nitrate is finally washed out from atmosphere by dry and wet deposition. Catalytic reactions of NOx are an important part of atmospheric chemistry forming or decomposing tropospheric ozone (O3). In atmosphere NO, NO2 and O3 are in photosta¬tionary equilibrium, therefore it is referred as NO-NO2-O3 triad. At regions with elevated NO concentrations reactions with air pollutions can form NO2, altering equilibrium of ozone formation.rnThe essential nutrient nitrogen is taken up by plants mainly by dissolved NO3- entering the roots. Atmospheric nitrogen is oxidized to NO3- within soil via bacteria by nitrogen fixation or ammonium formation and nitrification. Additionally atmospheric NO2 uptake occurs directly by stomata. Inside the apoplast NO2 is disproportionated to nitrate and nitrite (NO2-), which can enter the plant metabolic processes. The enzymes nitrate and nitrite reductase convert nitrate and nitrite to ammonium (NH4+). NO2 gas exchange is controlled by pressure gradients inside the leaves, the stomatal aperture and leaf resistances. Plant stomatal regulation is affected by climate factors like light intensity, temperature and water vapor pressure deficit. rnThis thesis wants to contribute to the comprehension of the effects of vegetation in the atmospheric NO2 cycle and to discuss the NO2 compensation point concentration (mcomp,NO2). Therefore, NO2 exchange between the atmosphere and spruce (Picea abies) on leaf level was detected by a dynamic plant chamber system under labo¬ratory and field conditions. Measurements took place during the EGER project (June-July 2008). Additionally NO2 data collected during the ECHO project (July 2003) on oak (Quercus robur) were analyzed. The used measuring system allowed simultaneously determina¬tion of NO, NO2, O3, CO2 and H2O exchange rates. Calculations of NO, NO2 and O3 fluxes based on generally small differences (∆mi) measured between inlet and outlet of the chamber. Consequently a high accuracy and specificity of the analyzer is necessary. To achieve these requirements a highly specific NO/NO2 analyzer was used and the whole measurement system was optimized to an enduring measurement precision.rnData analysis resulted in a significant mcomp,NO2 only if statistical significance of ∆mi was detected. Consequently, significance of ∆mi was used as a data quality criterion. Photo-chemical reactions of the NO-NO2-O3 triad in the dynamic plant chamber’s volume must be considered for the determination of NO, NO2, O3 exchange rates, other¬wise deposition velocity (vdep,NO2) and mcomp,NO2 will be overestimated. No significant mcomp,NO2 for spruce could be determined under laboratory conditions, but under field conditions mcomp,NO2 could be identified between 0.17 and 0.65 ppb and vdep,NO2 between 0.07 and 0.42 mm s-1. Analyzing field data of oak, no NO2 compensation point concentration could be determined, vdep,NO2 ranged between 0.6 and 2.71 mm s-1. There is increasing indication that forests are mainly a sink for NO2 and potential NO2 emissions are low. Only when assuming high NO soil emissions, more NO2 can be formed by reaction with O3 than plants are able to take up. Under these circumstance forests can be a source for NO2.

Software tools and efficient algorithms for the feature detection, feature tracking, event localization, and visualization of large sets of atmospheric data

Data sets describing the state of the earth's atmosphere are of great importance in the atmospheric sciences. Over the last decades, the quality and sheer amount of the available data increased significantly, resulting in a rising demand for new tools capable of handling and analysing these large, multidimensional sets of atmospheric data. The interdisciplinary work presented in this thesis covers the development and the application of practical software tools and efficient algorithms from the field of computer science, aiming at the goal of enabling atmospheric scientists to analyse and to gain new insights from these large data sets. For this purpose, our tools combine novel techniques with well-established methods from different areas such as scientific visualization and data segmentation. In this thesis, three practical tools are presented. Two of these tools are software systems (Insight and IWAL) for different types of processing and interactive visualization of data, the third tool is an efficient algorithm for data segmentation implemented as part of Insight.Insight is a toolkit for the interactive, three-dimensional visualization and processing of large sets of atmospheric data, originally developed as a testing environment for the novel segmentation algorithm. It provides a dynamic system for combining at runtime data from different sources, a variety of different data processing algorithms, and several visualization techniques. Its modular architecture and flexible scripting support led to additional applications of the software, from which two examples are presented: the usage of Insight as a WMS (web map service) server, and the automatic production of a sequence of images for the visualization of cyclone simulations. The core application of Insight is the provision of the novel segmentation algorithm for the efficient detection and tracking of 3D features in large sets of atmospheric data, as well as for the precise localization of the occurring genesis, lysis, merging and splitting events. Data segmentation usually leads to a significant reduction of the size of the considered data. This enables a practical visualization of the data, statistical analyses of the features and their events, and the manual or automatic detection of interesting situations for subsequent detailed investigation. The concepts of the novel algorithm, its technical realization, and several extensions for avoiding under- and over-segmentation are discussed. As example applications, this thesis covers the setup and the results of the segmentation of upper-tropospheric jet streams and cyclones as full 3D objects. Finally, IWAL is presented, which is a web application for providing an easy interactive access to meteorological data visualizations, primarily aimed at students. As a web application, the needs to retrieve all input data sets and to install and handle complex visualization tools on a local machine are avoided. The main challenge in the provision of customizable visualizations to large numbers of simultaneous users was to find an acceptable trade-off between the available visualization options and the performance of the application. Besides the implementational details, benchmarks and the results of a user survey are presented.

Investigation of petabyte-scale data transfer performances with PhEDEx for the CMS experiment

PhEDEx, the CMS transfer management system, during the first LHC Run has moved about 150 PB and currently it is moving about 2.5 PB of data per week over the Worldwide LHC Computing Grid (WLGC). It was designed to complete each transfer required by users at the expense of the waiting time necessary for its completion. For this reason, after several years of operations, data regarding transfer latencies has been collected and stored into log files containing useful analyzable informations. Then, starting from the analysis of several typical CMS transfer workflows, a categorization of such latencies has been made with a focus on the different factors that contribute to the transfer completion time. The analysis presented in this thesis will provide the necessary information for equipping PhEDEx in the future with a set of new tools in order to proactively identify and fix any latency issues. PhEDEx, il sistema di gestione dei trasferimenti di CMS, durante il primo Run di LHC ha trasferito all’incirca 150 PB ed attualmente trasferisce circa 2.5 PB di dati alla settimana attraverso la Worldwide LHC Computing Grid (WLCG). Questo sistema è stato progettato per completare ogni trasferimento richiesto dall’utente a spese del tempo necessario per il suo completamento. Dopo svariati anni di operazioni con tale strumento, sono stati raccolti dati relativi alle latenze di trasferimento ed immagazzinati in log files contenenti informazioni utili per l’analisi. A questo punto, partendo dall’analisi di una ampia mole di trasferimenti in CMS, è stata effettuata una suddivisione di queste latenze ponendo particolare attenzione nei confronti dei fattori che contribuiscono al tempo di completamento del trasferimento. L’analisi presentata in questa tesi permetterà di equipaggiare PhEDEx con un insieme di utili strumenti in modo tale da identificare proattivamente queste latenze e adottare le opportune tattiche per minimizzare l’impatto sugli utenti finali.

Assessment of smoking behaviour in the dental setting. A study comparing self-reported questionnaire data and exhaled carbon monoxide levels

The present study validated the accuracy of data from a self-reported questionnaire on smoking behaviour with the use of exhaled carbon monoxide (CO) level measurements in two groups of patients. Group 1 included patients referred to an oral medicine unit, whereas group 2 was recruited from the daily outpatient service. All patients filled in a standardized questionnaire regarding their current and former smoking habits. Additionally, exhaled CO levels were measured using a monitor. A total of 121 patients were included in group 1, and 116 patients were included in group 2. The mean value of exhaled CO was 7.6 ppm in the first group and 9.2 ppm in the second group. The mean CO values did not statistically significantly differ between the two groups. The two exhaled CO level measurements taken for each patient exhibited very good correlation (Spearman's coefficient of 0.9857). Smokers had a mean difference of exhaled CO values of 13.95 ppm (p < 0.001) compared to non-smokers adjusted for the first or second group. The consumption of one additional pack year resulted in an increase in CO values of 0.16 ppm (p = 0.003). The consumption of one additional cigarette per day elevated the CO measurements by 0.88 ppm (p < 0.001). Based on these results, the correlations between the self-reported smoking habits and exhaled CO values are robust and highly reproducible. CO monitors may offer a non-invasive method to objectively assess current smoking behaviour and to monitor tobacco use cessation attempts in the dental setting.

Chances and risks of publication of quality data - the perspectives of Swiss physicians and nurses

Background The release of quality data from acute care hospitals to the general public is based on the aim to inform the public, to provide transparency and to foster quality-based competition among providers. Due to the expected mechanisms of action and possibly the adverse consequences of public quality comparison, it is a controversial topic. The perspective of physicians and nurses is of particular importance in this context. They are mainly responsible for the collection of quality-control data, and are directly confronted with the results of public comparison. The research focus of this qualitative study was to discover what the views and opinions of the Swiss physicians and nurses were regarding these issues. It was investigated as to how the two professional groups appraised the opportunities as well as the risks of the release of quality data in Switzerland. Methods A qualitative approach was chosen to answer the research question. For data collection, four focus groups were conducted with physicians and nurses who were employed in Swiss acute care hospitals. Qualitative content analysis was applied to the data. Results The results revealed that both occupational groups had a very critical and negative attitude regarding the recent developments. The perceived risks were dominating their view. In summary, their main concerns were: the reduction of complexity, the one-sided focus on measurable quality variables, risk selection, the threat of data manipulation and the abuse of published information by the media. An additional concern was that the impression is given that the complex construct of quality can be reduced to a few key figures, and it that it is constructed from a false message which then influences society and politics. This critical attitude is associated with the different value system and the professional self-concept that both physicians and nurses have, in comparison to the underlying principles of a market-based economy and the economic orientation of health care business. Conclusions The critical and negative attitude of Swiss physicians and nurses must, under all conditions, be heeded to and investigated regarding its impact on work motivation and identification with the profession. At the same time, the two professional groups are obligated to reflect upon their critical attitude and take a proactive role in the development of appropriate quality indicators for the publication of quality data in Switzerland.

Trauma registry record linkage: methodological approach to benefit from complementary data using the example of the German Pelvic Injury Register and the TraumaRegister DGU(®)

In Germany, hospitals can deliver data from patients with pelvic fractures selectively or twofold to two different trauma registries, i.e. the German Pelvic Injury Register (PIR) and the TraumaRegister DGU(®) (TR). Both registers are anonymous and differ in composition and content. We describe the methodological approach of linking these registries and reidentifying twofold documented patients. The aim of the approach is to create an intersection set that benefit from complementary data of each registry, respectively. Furthermore, the concordance of data entry of some clinical variables entered in both registries was evaluated.

Response Bias Using Two-Stage Data Collection: A study of elderly participants in a program.

Researchers examining the effects of programs, in this case a state-level pharmaceutical assistance program for the elderly, sometimes must rely on multiple methods of data collection. Two-stage data collection (e.g., a telephone interview followed by a mail questionnaire) was used to obtain a full range of information. Older age groups were found to participate less frequently in the telephone interview, while certain demographic factors characterized mail questionnaire nonparticipants, all of which supports past research. Results also show that those in the poorest health are less likely to participate in the mail survey. Combining the two methods did not result in high attrition, suggesting that innovation can be successfully employed. Knowledge of the bias associated with each method will aid in targeting special groups.

A Data-Analytic Strategy for Protein-Biomarker Discovery: Profiling of High-Dimensional Proteomic Data for Cancer Detection

With recent advances in mass spectrometry techniques, it is now possible to investigate proteins over a wide range of molecular weights in small biological specimens. This advance has generated data-analytic challenges in proteomics, similar to those created by microarray technologies in genetics, namely, discovery of "signature" protein profiles specific to each pathologic state (e.g., normal vs. cancer) or differential profiles between experimental conditions (e.g., treated by a drug of interest vs. untreated) from high-dimensional data. We propose a data analytic strategy for discovering protein biomarkers based on such high-dimensional mass-spectrometry data. A real biomarker-discovery project on prostate cancer is taken as a concrete example throughout the paper: the project aims to identify proteins in serum that distinguish cancer, benign hyperplasia, and normal states of prostate using the Surface Enhanced Laser Desorption/Ionization (SELDI) technology, a recently developed mass spectrometry technique. Our data analytic strategy takes properties of the SELDI mass-spectrometer into account: the SELDI output of a specimen contains about 48,000 (x, y) points where x is the protein mass divided by the number of charges introduced by ionization and y is the protein intensity of the corresponding mass per charge value, x, in that specimen. Given high coefficients of variation and other characteristics of protein intensity measures (y values), we reduce the measures of protein intensities to a set of binary variables that indicate peaks in the y-axis direction in the nearest neighborhoods of each mass per charge point in the x-axis direction. We then account for a shifting (measurement error) problem of the x-axis in SELDI output. After these pre-analysis processing of data, we combine the binary predictors to generate classification rules for cancer, benign hyperplasia, and normal states of prostate. Our approach is to apply the boosting algorithm to select binary predictors and construct a summary classifier. We empirically evaluate sensitivity and specificity of the resulting summary classifiers with a test dataset that is independent from the training dataset used to construct the summary classifiers. The proposed method performed nearly perfectly in distinguishing cancer and benign hyperplasia from normal. In the classification of cancer vs. benign hyperplasia, however, an appreciable proportion of the benign specimens were classified incorrectly as cancer. We discuss practical issues associated with our proposed approach to the analysis of SELDI output and its application in cancer biomarker discovery.

Generalizations of Current Status Data With Applications

In estimation of a survival function, current status data arises when the only information available on individuals is their survival status at a single monitoring time. Here we briefly review extensions of this form of data structure in two directions: (i) doubly censored current status data, where there is incomplete information on the origin of the failure time random variable, and (ii) current status information on more complicated stochastic processes. Simple examples of these data forms are presented for motivation.

An integrated approach for reconstructing surface models of the proximal femur from sparse input data for surgical navigation

A patient-specific surface model of the proximal femur plays an important role in planning and supporting various computer-assisted surgical procedures including total hip replacement, hip resurfacing, and osteotomy of the proximal femur. The common approach to derive 3D models of the proximal femur is to use imaging techniques such as computed tomography (CT) or magnetic resonance imaging (MRI). However, the high logistic effort, the extra radiation (CT-imaging), and the large quantity of data to be acquired and processed make them less functional. In this paper, we present an integrated approach using a multi-level point distribution model (ML-PDM) to reconstruct a patient-specific model of the proximal femur from intra-operatively available sparse data. Results of experiments performed on dry cadaveric bones using dozens of 3D points are presented, as well as experiments using a limited number of 2D X-ray images, which demonstrate promising accuracy of the present approach.

The exchange of radiotherapy data as part of an electronic patient-referral system

PURPOSE: To describe the implementation and use of an electronic patient-referral system as an aid to the efficient referral of patients to a remote and specialized treatment center. METHODS AND MATERIALS: A system for the exchange of radiotherapy data between different commercial planning systems and a specially developed planning system for proton therapy has been developed through the use of the PAPYRUS diagnostic image standard as an intermediate format. To ensure the cooperation of the different TPS manufacturers, the number of data sets defined for transfer has been restricted to the three core data sets of CT, VOIs, and three-dimensional dose distributions. As a complement to the exchange of data, network-wide application-sharing (video-conferencing) technologies have been adopted to provide methods for the interactive discussion and assessment of treatments plans with one or more partner clinics. RESULTS: Through the use of evaluation plans based on the exchanged data, referring clinics can accurately assess the advantages offered by proton therapy on a patient-by-patient basis, while the practicality or otherwise of the proposed treatments can simultaneously be assessed by the proton therapy center. Such a system, along with the interactive capabilities provided by video-conferencing methods, has been found to be an efficient solution to the problem of patient assessment and selection at a specialized treatment center, and is a necessary first step toward the full electronic integration of such centers with their remotely situated referral centers.

Investigation of the effect of using data collection technology on students' attitudes to science instruction

The purpose of this project was to investigate the effect of using of data collection technology on student attitudes towards science instruction. The study was conducted over the course of two years at Madison High School in Adrian, Michigan, primarily in college preparatory physics classes, but also in one college preparatory chemistry class and one environmental science class. A preliminary study was conducted at a Lenawee County Intermediate Schools student summer environmental science day camp. The data collection technology used was a combination of Texas Instruments TI-84 Silver Plus graphing calculators and Vernier LabPro data collection sleds with various probeware attachments, including motion sensors, pH probes and accelerometers. Students were given written procedures for most laboratory activities and were provided with data tables and analysis questions to answer about the activities. The first year of the study included a pretest and posttest measuring student attitudes towards the class they were enrolled in. Pre-test and post-test data were analyzed to determine effect size, which was found to be very small (Coe, 2002). The second year of the study focused only on a physics class and used Keller’s ARCS model for measuring student motivation based on the four aspects of motivation: Attention, Relevance, Confidence and Satisfaction (Keller, 2010). According to this model, it was found that there were two distinct groups in the class, one of which was motivated to learn and the other that was not. The data suggest that the use of data collection technology in science classes should be started early in a student’s career, possibly in early middle school or late elementary. This would build familiarity with the equipment and allow for greater exploration by the student as they progress through high school and into upper level science courses.