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- Fachbereich Medizintechnik und Technomathematik (2052) (remove)
Detection of triacetone triperoxide using temperature cycled metal-oxide semiconductor gas sensors
(2015)
Miniaturized setup, compatibility with advanced micro- and nanotechnologies, and ability to detect biomolecules by their intrinsic molecular charge favor the semiconductor field-effect platform as one of the most attractive approaches for the development of label-free DNA chips. In this work, a capacitive field-effect EIS (electrolyte–insulator–semiconductor) sensor covered with a layer-by-layer prepared, positively charged weak polyelectrolyte layer of PAH (poly(allylamine hydrochloride)) was used for the label-free electrical detection of DNA (deoxyribonucleic acid) immobilization and hybridization. The negatively charged probe single-stranded DNA (ssDNA) molecules were electrostatically adsorbed onto the positively charged PAH layer, resulting in a preferentially flat orientation of the ssDNA molecules within the Debye length, thus yielding a reduced charge-screening effect and a higher sensor signal. Each sensor-surface modification step (PAH adsorption, probe ssDNA immobilization, hybridization with complementary target DNA (cDNA), reducing an unspecific adsorption by a blocking agent, incubation with noncomplementary DNA (ncDNA) solution) was monitored by means of capacitance–voltage and constant-capacitance measurements. In addition, the surface morphology of the PAH layer was studied by atomic force microscopy and contact-angle measurements. High hybridization signals of 34 and 43 mV were recorded in low-ionic strength solutions of 10 and 1 mM, respectively. In contrast, a small signal of 4 mV was recorded in the case of unspecific adsorption of fully mismatched ncDNA. The density of probe ssDNA and dsDNA molecules as well as the hybridization efficiency was estimated using the experimentally measured DNA immobilization and hybridization signals and a simplified double-layer capacitor model. The results of field-effect experiments were supported by fluorescence measurements, verifying the DNA-immobilization and hybridization event.
In this work, a sensor to evaluate sterilization processes with hydrogen peroxide vapor has been characterized. Experimental, analytical and numerical methods were applied to evaluate and study the sensor behavior. The sensor set-up is based on planar interdigitated electrodes. The interdigitated electrode structure consists of 614 electrode fingers spanning over a total sensing area of 20 mm2. Sensor measurements were conducted with and without microbiological spores as well as after an industrial sterilization protocol. The measurements were verified using an analytical expression based on a first-order elliptical integral. A model based on the finite element method with periodic boundary conditions in two dimensions was developed and utilized to validate the experimental findings.
Designing novel or optimizing existing biodegradable polymers for biomedical applications requires numerous tests on the effect of substances on the degradation process. In the present work, polymer-modified electrolyte–insulator–semiconductor (PMEIS) sensors have been applied for monitoring an enzymatically catalyzed degradation of polymers for the first time. The thin films of biodegradable polymer poly(d,l-lactic acid) and enzyme lipase were used as a model system. During degradation, the sensors were read-out by means of impedance spectroscopy. In order to interpret the data obtained from impedance measurements, an electrical equivalent circuit model was developed. In addition, morphological investigations of the polymer surface have been performed by means of in situ atomic force microscopy. The sensor signal change, which reflects the progress of degradation, indicates an accelerated degradation in the presence of the enzyme compared to hydrolysis in neutral pH buffer media. The degradation rate increases with increasing enzyme concentration. The obtained results demonstrate the potential of PMEIS sensors as a very promising tool for in situ and real-time monitoring of degradation of polymers.
The chemical imaging sensor was applied to in-situ pH imaging of the solution in the vicinity of a corroding surface of stainless steel under potentiostatic polarization. A test piece of polished stainless steel was placed on the sensing surface leaving a narrow gap filled with artificial seawater and the stainless steel was corroded under polarization. The pH images obtained during polarization showed correspondence between the region of lower pH and the site of corrosion. It was also found that the pH value in the gap became as low as 2 by polarization, which triggered corrosion.
The sterilization of packages in aseptic food processes is highly significant to maintain a consumer-safe product with extended shelf-life. Today, the sterilization of food packages is predominantly accomplished by gaseous hydrogen peroxide (H2O2) in combination with heat. In order to monitor this sterilization process, calorimetric gas sensors as differential set-up of two platinum temperature sensors representing a catalytically active (additionally deposition of MnO2) and a passive segment have been recently developed. The temperature rise of the exothermic decomposition serves as an indicator of the present H2O2 concentration. In the present work, a theoretical approach considering the sensor’s thermochemistry and physical transport phenomena was formulated to evaluate the temperature rise based on the energy content of gaseous H2O2. In a further part of this work, three polymers have been analyzed with respect to their application as passivation materials. The examined polymers are photoresist SU-8, perfluoroalkoxy (PFA) and fluorinated ethylene propylene (FEP). Thermal analyses by means of differential scanning calorimetry (DSC) and thermogravimetric analysis (TGA) have been conducted to determine the operation limits of the polymers. The overall chemical resistance and stability of the polymers against the harsh environmental conditions during the sterilization process have been examined by attenuated total reflection Fourier transform infrared spectroscopy (ATR-FTIR).
Changes in intestinal microflora in rats induced by oral exposure to low lead (II) concentrations
(2015)
Light-stimulated hydrogel actuators with incorporated graphene oxide for microfluidic applications
(2015)
Label-free sensing of biomolecules by their intrinsic molecular charge using field-effect devices
(2015)
Data-driven prediction and prevention of extreme events in a spatially extended excitable system
(2015)
Booster stations can fulfill a varying pressure demand with high energy-efficiency, because individual pumps can be deactivated at smaller loads. Although this is a seemingly simple approach, it is not easy to decide precisely when to activate or deactivate pumps. Contemporary activation controls derive the switching points from the current volume flow through the system. However, it is not measured directly for various reasons. Instead, the controller estimates the flow based on other system properties. This causes further uncertainty for the switching decision. In this paper, we present a method to find a robust, yet energy-efficient activation strategy.
Let X₁,…,Xₙ be independent and identically distributed random variables with distribution F. Assuming that there are measurable functions f:R²→R and g:R²→R characterizing a family F of distributions on the Borel sets of R in the way that the random variables f(X₁,X₂),g(X₁,X₂) are independent, if and only if F∈F, we propose to treat the testing problem H:F∈F,K:F∉F by applying a consistent nonparametric independence test to the bivariate sample variables (f(Xᵢ,Xⱼ),g(Xᵢ,Xⱼ)),1⩽i,j⩽n,i≠j. A parametric bootstrap procedure needed to get critical values is shown to work. The consistency of the test is discussed. The power performance of the procedure is compared with that of the classical tests of Kolmogorov–Smirnov and Cramér–von Mises in the special cases where F is the family of gamma distributions or the family of inverse Gaussian distributions.
Shakedown analysis of Reissner-Mindlin plates using the edge-based smoothed finite element method
(2014)
This paper concerns the development of a primal-dual algorithm for limit and shakedown analysis of Reissner-Mindlin plates made of von Mises material. At each optimization iteration, the lower bound of the shakedown load multiplier is calculated simultaneously with the upper bound using the duality theory. An edge-based smoothed finite element method (ES-FEM) combined with the discrete shear gap (DSG) technique is used to improve the accuracy of the solutions and to avoid the transverse shear locking behaviour. The method not only possesses all inherent features of convergence and accuracy from ES-FEM, but also ensures that the total number of variables in the optimization problem is kept to a minimum compared with the standard finite element formulation. Numerical examples are presented to demonstrate the effectiveness of the present method.
This article describes the fabrication, characterization and application of an epidermal temporary-transfer tattoo-based potentiometric sensor, coupled with a miniaturized wearable wireless transceiver, for real-time monitoring of sodium in the human perspiration. Sodium excreted during perspiration is an excellent marker for electrolyte imbalance and provides valuable information regarding an individual's physical and mental wellbeing. The realization of the new skin-worn non-invasive tattoo-like sensing device has been realized by amalgamating several state-of-the-art thick film, laser printing, solid-state potentiometry, fluidics and wireless technologies. The resulting tattoo-based potentiometric sodium sensor displays a rapid near-Nernstian response with negligible carryover effects, and good resiliency against various mechanical deformations experienced by the human epidermis. On-body testing of the tattoo sensor coupled to a wireless transceiver during exercise activity demonstrated its ability to continuously monitor sweat sodium dynamics. The real-time sweat sodium concentration was transmitted wirelessly via a body-worn transceiver from the sodium tattoo sensor to a notebook while the subjects perspired on a stationary cycle. The favorable analytical performance along with the wearable nature of the wireless transceiver makes the new epidermal potentiometric sensing system attractive for continuous monitoring the sodium dynamics in human perspiration during diverse activities relevant to the healthcare, fitness, military, healthcare and skin-care domains.
We study the estimation of some linear functionals which are based on an unknown lifetime distribution. The observations are assumed to be generated under the semi-parametric random censorship model (SRCM), that is, a random censorship model where the conditional expectation of the censoring indicator given the observation belongs to a parametric family. Under this setup a semi-parametric estimator of the survival function was introduced by the author. If the parametric model assumption is correct, it is known that the estimated functional which is based on this semi-parametric estimator is asymptotically at least as efficient as the corresponding one which rests on the nonparametric Kaplan–Meier estimator.
In this paper we show that the estimated functional which is based on this semi-parametric estimator is asymptotically efficient with respect to the class of all regular estimators under this semi-parametric model.
In this study, a high-speed chemical imaging system was developed for visualization of the interior of a microfluidic channel. A microfluidic channel was constructed on the sensor surface of the light-addressable potentiometric sensor (LAPS), on which the ion concentrations could be measured in parallel at up to 64 points illuminated by optical fibers. The temporal change of pH distribution inside the microfluidic channel was recorded at a maximum rate of 100 frames per second (fps). The high frame rate allowed visualization of moving interfaces and plugs in the channel even at a flow velocity of 111 mm/s, which suggests the feasibility of plug-based microfluidic devices for flow-injection analysis (FIA).
In any books about genetics it can still today be read that our genetic code is called “degenerate” because it is still believed that 43 = 64 triplets encode the 20 essential amino acids. Indeed we have to assume the inverse law, what means that 34 = 81 exact code positions are really effective for our genetic code and encode the amino acids, compiled to proteins. This very important discovery leads to two completely new results that are limits-overlooking: 1) 34 (=81) genetic code positions mean exactly the same number as there are stable and naturally existing chemical elements in our universe. This famous argument should now lead to some alternative, as well as new fundamental conclusions about our existence. 2) A genetic code positioning system shows that nature is much smarter than expected: mutations are made less dangerous than believed, because they won't be that easily able any more to cause severe damages in the protein-synthesis. This should also lead to some alternative views upon evolution of life.
An enzyme system organized in a flow device was used to mimic a reversible Controlled NOT (CNOT) gate with two input and two output signals. Reversible conversion of NAD⁺ and NADH cofactors was used to perform a XOR logic operation, while biocatalytic hydrolysis of p-nitrophenyl phosphate resulted in an Identity operation working in parallel. The first biomolecular realization of a CNOT gate is promising for integration into complex biomolecular networks and future biosensor/biomedical applications.
Background
True date palms (Phoenix dactylifera L.) are impressive trees and have served as an indispensable source of food for mankind in tropical and subtropical countries for centuries. The aim of this study is to differentiate date palm tree varieties by analysing leaflet cross sections with technical/optical methods and artificial neural networks (ANN).
Results
Fluorescence microscopy images of leaflet cross sections have been taken from a set of five date palm tree cultivars (Hewlat al Jouf, Khlas, Nabot Soltan, Shishi, Um Raheem). After features extraction from images, the obtained data have been fed in a multilayer perceptron ANN with backpropagation learning algorithm.
Conclusions
Overall, an accurate result in prediction and differentiation of date palm tree cultivars was achieved with average prediction in tenfold cross-validation is 89.1% and reached 100% in one of the best ANN.
Multimodal bioimage sensor
(2014)
To visualize the biochemical distribution two-dimensionally, we invented a solid-state-type ion image sensor that indicates the chemical activity of solutions and cells. The device, which consists of a CCD array covered with a functionalized membrane to detect charge accumulation, is highly sensitive to changes in the concentration and two-dimensional distribution of ions and biomaterials.
It is well known that the degradation environment can strongly influence the biodegradability and kinetics of biodegradation processes of polymers. Therefore, besides the monitoring of the degradation process, it is also necessary to control the medium in which the degradation takes place. In this work, a micromachined multi-parameter sensor chip for the control of the polymer-degradation medium has been developed. The chip combines a capacitive field-effect pH sensor, a four-electrode electrolyte-conductivity sensor and a thin-film Pt-temperature sensor. The results of characterization of individual sensors are presented. In addition, the multi-parameter sensor chip together with an impedimetric polymer-degradation sensor was simultaneously characterized in degradation solutions with different pH and electrolyte conductivity. The obtained results demonstrate the feasibility of the multi-parameter sensor chip for the control of the polymer-degradation medium.
It is well known that biochemical and biotechnological processes are strongly dependent and affected by a variety of physico-chemical parameters such as pH value, temperature, pressure and electrolyte conductivity. Therefore, these quantities have to be monitored or controlled in order to guarantee a stable process operation, optimization and high yield. In this work, a sensor chip for the multiparameter detection of three physico-chemical parameters such as electrolyte conductivity, pH and temperature is realized using barium strontium titanate (BST) as multipurpose material. The chip integrates a capacitively coupled four-electrode electrolyte-conductivity sensor, a capacitive field-effect pH sensor and a thin-film Pt-temperature sensor. Due to the multifunctional properties of BST, it is utilized as final outermost coating layer of the processed sensor chip and serves as passivation and protection layer as well as pH-sensitive transducer material at the same time. The results of testing of the individual sensors of the developed multiparameter sensor chip are presented. In addition, a quasi-simultaneous multiparameter characterization of the sensor chip in buffer solutions with different pH value and electrolyte conductivity is performed. To study the sensor behavior and the suitability of BST as multifunctional material under harsh environmental conditions, the sensor chip was exemplarily tested in a biogas digestate.