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We investigate interaction networks that we derive from multivariate time series with methods frequently employed in diverse scientific fields such as biology, quantitative finance, physics, earth and climate sciences, and the neurosciences. Mimicking experimental situations, we generate time series with finite length and varying frequency content but from independent stochastic processes. Using the correlation coefficient and the maximum cross-correlation, we estimate interdependencies between these time series. With clustering coefficient and average shortest path length, we observe unweighted interaction networks, derived via thresholding the values of interdependence, to possess non-trivial topologies as compared to Erdös-Rényi networks, which would indicate small-world characteristics. These topologies reflect the mostly unavoidable finiteness of the data, which limits the reliability of typically used estimators of signal interdependence. We propose random networks that are tailored to the way interaction networks are derived from empirical data. Through an exemplary investigation of multichannel electroencephalographic recordings of epileptic seizures – known for their complex spatial and temporal dynamics – we show that such random networks help to distinguish network properties of interdependence structures related to seizure dynamics from those spuriously induced by the applied methods of analysis.
HisT/PLIER : A Two-Fold Provenance Approach for Grid-Enabled Scientific Workflows Using WS-VLAM
(2011)
Beim Ausbau nachhaltiger, regenerativer Energieversorgung hat die Umwandlung von organischer Biomasse in Biogas ein großes Potential. Der zugrundeliegende, komplexe biologische Prozess wird noch immer unzureichend verstanden und bedarf systematischer Untersuchungen der Prozessparameter, um einen hohen Ertrag bei guter Gasqualität zu ermöglichen. Die Fragestellungen zur Entschlüsselung des Prozesses sind sowohl verfahrenstechnischer als auch mikrobiologischer Natur. Aus mikrobiologischer Sicht ist die Kenntnis der tatsächlich beteiligten prozesstragenden Mikroorganismen von erheblicher Bedeutung, aus verfahrenstechnischer Sicht die Kenntnis der physikalischen und chemischen Faktoren, welche die mikrobiologischen Prozesse und kontrollieren. Im Zusammenspiel aller dieser Parameter wird die Biogasbildung befördert oder behindert, bis zum Abbruch des Prozesses.
Eine mögliche Kontrollmethode ist die Messung der metabolischen Aktivität prozesstragender Organismen.
Diese soll, beruhend auf fundierten Prozessdaten, gewonnen durch eine Parallelanlage, mit einem lichtadressierbaren potentiometrischen Sensor-System (LAPS) realisiert werden. Dieser Sensor ist in der Lage, pH-Wert-änderungen zu detektieren, die durch den Stoffwechsel der auf dem Chip immobilisierten Organismen hervorgerufen werden, um eine Online-Überwachung von Biogasanlagen zu ermöglichen.
One-chip integrated dual amperometric/field-effect sensor for the detection of dissolved hydrogen
(2011)
The purpose of this study was to investigate whether sprint performance is related to lower leg musculoskeletal geometry within a homogeneous group of highly trained 100-m sprinters. Using a cluster analysis, eighteen male sprinters were divided into two groups based on their personal best (fast: N = 11, 10.30 ± 0.07 s; slow: N = 7, 10.70 ± 0.08 s). Calf muscular fascicle arrangement and Achilles tendon moment arms (calculated by the gradient of tendon excursion versus ankle joint angle) were analyzed for each athlete using ultrasonography. Achilles tendon moment arm, foot and ankle skeletal geometry, fascicle arrangement as well as the ratio of fascicle length to Achilles tendon moment arm showed no significant (p > 0.05) correlation with sprint performance, nor were there any differences in the analyzed musculoskeletal parameters between the fast and slow sprinter group. Our findings provide evidence that differences in sprint ability in world-class athletes are not a result of differences in the geometrical design of the lower leg even when considering both skeletal and muscular components.