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One-chip integrated dual amperometric/field-effect sensor for the detection of dissolved hydrogen
(2011)
Lignocellulosic biorefinery: Process integration of hydrolysis and fermentation (SSF process)
(2011)
The aim of the present work is the process integration and the optimization of the enzymatic hydrolysis of wood and the following fermentation of the products to ethanol. The substrate is a fiber fraction obtained by organosolv pre-treatment of beech wood. For the ethanol production, a co-fermentation by two different yeasts (Saccharomyces cerevisiae and Pachysolen tannophilus) was carried out to convert glucose as well as xylose. Two approaches has been followed: 1. A two step process, in which the hydrolysis of the fiber fraction and the fermentation to product are separated from each other. 2. A process, in which the hydrolysis and the fermentation are carried out in one single process step as simultaneous saccharification and fermentation (SSF). Following the first approach, a yield of about 0.15 g ethanol per gram substrate can be reached. Based on the SSF, one process step can be saved, and additionally, the gained yield can be raised up to 0.3 g ethanol per gram substrate.
Bio-feedstocks
(2011)
The magnetic forces of fringe magnetic fields of MR systems on ferromagnetic components can impose a severe patient, occupational health and safety hazard. MRI accidents are listed as number 9 of the top 10 risks in modern medicine. With the advent of ultrahigh field MR systems including passively shielded magnet versions, this risk, commonly known as the missile or projectile effect is even more pronounced. A strategy employing magnetic field sensors which can be attached to ferromagnetic objects that are commonly used in a clinical environment is conceptually appealing for the pursuit of reducing the risk of ferromagnetic projectile accidents.
Objective
The purpose of this study is to (i) design a small and mobile Magnetic field ALert SEnsor (MALSE), (ii) to carefully evaluate its sensors to their consistency of activation/deactivation and sensitivity to magnetic fields, and (iii) to demonstrate the applicability of MALSE in 1.5 T, 3.0 T and 7.0 T MR fringe field environments.
Methods
MALSE comprises a set of reed sensors, which activate in response to their exposure to a magnetic field. The activation/deactivation of reed sensors was examined by moving them in/out of the fringe field generated by 7TMR.
Results
The consistency with which individual reed sensors would activate at the same field strength was found to be 100% for the setup used. All of the reed switches investigated required a substantial drop in ambient magnetic field strength before they deactivated.
Conclusions
MALSE is a simple concept for alerting MRI staff to a ferromagnetic object being brought into fringe magnetic fields which exceeds MALSEs activation magnetic field. MALSE can easily be attached to ferromagnetic objects within the vicinity of a scanner, thus creating a barrier for hazardous situations induced by ferromagnetic parts which should not enter the vicinity of an MR-system to occur.
ECG is corrupted by magneto-hydrodynamic effects at higher magnetic field strength. Artifacts in the ECG trace and severe T-wave elevation might be mis-interpreted as R-waves. MHD being inherently sensitive to blood flow and blood velocity provides an alternative approach for cardiac gating, even in peripheral target areas far away from the commonly used upper torso positions of ECG electrodes. This feature would be very beneficial to address traveling time induced motion artifacts and trigger latency related issues raised by ECG-gated peripheral MR angiography. For all those reasons, this work proposes the use of MHD-trigger for cardiac gated MR.
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.