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Our world is well ordered in measurement and number : or why natural constants are as they are
(2013)
All the important natural constants can be logically explained with and derived from the first four ordinal numbers, 1, 2, 3 and 4, its addition to ten and finally the standard values for obviously maximal feasibility Ω and the optimum in our world, the Golden Section (GS), i.e. the number sequences 273 and 618. They both are the first three numbers of irrational results by an arithmetical transformation of simple geometrical relationships by creating multiplicity out of singularity. Both of them show that the infinite is inherent in finiteness and explain in a simple way the smallest deviations and fluctuations between the physical AS-IS state and the obvious spiritual ideal behind: Wherever we look in this world, and especially in important key-positions, we regularly find these sequences. All of the above mentioned numbers so seem to be key players in our world, what can be demonstrated by the derivation of natural constants.
Purpose
To design and evaluate a modular transceiver coil array with 32 independent channels for cardiac MRI at 7.0T.
Methods
The modular coil array comprises eight independent building blocks, each containing four transceiver loop elements. Numerical simulations were used for B1+ field homogenization and radiofrequency (RF) safety validation. RF characteristics were examined in a phantom study. The array's suitability for accelerated high spatial resolution two-dimensional (2D) FLASH CINE imaging of the heart was examined in a volunteer study.
Results
Transmission field adjustments and RF characteristics were found to be suitable for the volunteer study. The signal-to-noise intrinsic to 7.0T together with the coil performance afforded a spatial resolution of 1.1 × 1.1 × 2.5 mm3 for 2D CINE FLASH MRI, which is by a factor of 6 superior to standardized CINE protocols used in clinical practice at 1.5T. The 32-channel transceiver array supports one-dimensional acceleration factors of up to R = 4 without impairing image quality significantly.
Conclusion
The modular 32-channel transceiver cardiac array supports accelerated and high spatial resolution cardiac MRI. The array is compatible with multichannel transmission and provides a technological basis for future clinical assessment of parallel transmission techniques at 7.0T.
The semiconductor field-effect platform represents a powerful tool for detecting the adsorption and binding of charged macromolecules with direct electrical readout. In this work, a capacitive electrolyte–insulator–semiconductor (EIS) field-effect sensor consisting of an Al-p-Si-SiO2 structure has been applied for real-time in situ electrical monitoring of the layer-by-layer formation of polyelectrolyte (PE) multilayers (PEM). The PEMs were deposited directly onto the SiO2 surface without any precursor layer or drying procedures. Anionic poly(sodium 4-styrene sulfonate) and cationic weak polyelectrolyte poly(allylamine hydrochloride) have been chosen as a model system. The effect of the ionic strength of the solution, polyelectrolyte concentration, number and polarity of the PE layers on the characteristics of the PEM-modified EIS sensors have been studied by means of capacitance–voltage and constant-capacitance methods. In addition, the thickness, surface morphology, roughness and wettabilityof the PE mono- and multilayers have been characterised by ellipsometry, atomic force microscopy and water contact-angle methods, respectively. To explain potential oscillations on the gate surface and signal behaviour of the capacitive field-effect EIS sensor modified with a PEM, a simplified electrostatic model that takes into account the reduced electrostatic screening of PE charges by mobile ions within the PEM has been proposed and discussed.
A microfluidic chip integrating amperometric enzyme sensors for the detection of glucose, glutamate and glutamine in cell-culture fermentation processes has been developed. The enzymes glucose oxidase, glutamate oxidase and glutaminase were immobilized by means of cross-linking with glutaraldehyde on platinum thin-film electrodes integrated within a microfluidic channel. The biosensor chip was coupled to a flow-injection analysis system for electrochemical characterization of the sensors. The sensors have been characterized in terms of sensitivity, linear working range and detection limit. The sensitivity evaluated from the respective peak areas was 1.47, 3.68 and 0.28 μAs/mM for the glucose, glutamate and glutamine sensor, respectively. The calibration curves were linear up to a concentration of 20 mM glucose and glutamine and up to 10 mM for glutamate. The lower detection limit amounted to be 0.05 mM for the glucose and glutamate sensor, respectively, and 0.1 mM for the glutamine sensor. Experiments in cell-culture medium have demonstrated a good correlation between the glutamate, glutamine and glucose concentrations measured with the chip-based biosensors in a differential-mode and the commercially available instrumentation. The obtained results demonstrate the feasibility of the realized microfluidic biosensor chip for monitoring of bioprocesses.
Learning- and memory-related processes are thought to result from dynamic interactions in large-scale brain networks that include lateral and mesial structures of the temporal lobes. We investigate the impact of incidental and intentional learning of verbal episodic material on functional brain networks that we derive from scalp-EEG recorded continuously from 33 subjects during a neuropsychological test schedule. Analyzing the networks' global statistical properties we observe that intentional but not incidental learning leads to a significantly increased clustering coefficient, and the average shortest path length remains unaffected. Moreover, network modifications correlate with subsequent recall performance: the more pronounced the modifications of the clustering coefficient, the higher the recall performance. Our findings provide novel insights into the relationship between topological aspects of functional brain networks and higher cognitive functions.