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Field-effect capacitive electrolyte-insulator-semiconductor (EIS) sensors functionalised with citrate-capped gold nanoparticles (AuNP) have been used for the electrostatic detection of macromolecules by their intrinsic molecular charge. The EIS sensor detects the charge changes in the AuNP/macromolecule hybrids induced by the adsorption or binding events. A feasibility of the proposed detection scheme has been exemplary demonstrated by realising EIS sensors for the detection of poly-D-lysine molecules.
The chemical imaging sensor is a chemical sensor which is capable of visualizing the spatial distribution of chemical species in sample solution. In this study, a novel measurement system based on the chemical imaging sensor was developed to observe the inside of a Y-shaped microfluidic channel while injecting two sample solutions from two branches. From the collected chemical images, it was clearly observed that the injected solutions formed laminar flows in the microfluidic channel. In addition, ion diffusion across the laminar flows was observed. This label-free method can acquire quantitative data of ion distribution and diffusion in microfluidic devices, which can be used to determine the diffusion coefficients, and therefore, the molecular weights of chemical species in the sample solution.
This work describes the novel combination of the light-addressable electrode (LAE) and the light-addressable potentiometric sensor (LAPS) into a microsystem set-up. Both the LAE as well as the LAPS shares the principle of addressing the active spot by means of a light beam. This enables both systems to manipulate resp. to detect an analyte with a high spatial resolution. Hence, combining both principles into a single set-up enables the active stimulation e.g., by means of electrolysis and a simultaneous observation e.g., the response of an entrapped biological cell by detection of extracellular pH changes. The work will describe the principles of both technologies and the necessary steps to integrate them into a single set-up. Furthermore, examples of application and operation of such systems will be presented.
A variety of transition metals, e.g., copper, zinc, cadmium, lead, etc. are widely used in industry as components for wires, coatings, alloys, batteries, paints and so on. The inevitable presence of transition metals in industrial processes implies the ambition of developing a proper analytical technique for their adequate monitoring. Most of these elements, especially lead and cadmium, are acutely toxic for biological organisms. Quantitative determination of these metals at low activity levels in different environmental and industrial samples is therefore a vital task. A promising approach to achieve an at-side or on-line monitoring on a miniaturized and cost efficient way is the combination of a common potentiometric sensor array with heavy metal-sensitive thin-film materials, like chalcogenide glasses and polymeric materials, respectively.
The construction of a statistical test is investigated which is based only on “reliability” and “precision” as quality criteria. The reliability of a statistical test is quantifiedin a straightforward way by the probability that the decision of the test is correct. However, the quantification of the precision of a statistical test is not at all evident. Thereforethe paper presents and discusses several approaches. Moreover the distinction of “nullhypothesis” and “alternative hypothesis” is not necessary any longer.
Real-time and reliable monitoring of the biogas process is crucial for a stable and efficient operation of biogas production in order to avoid digester breakdowns. The concentration of dissolved hydrogen (H₂) represents one of the key parameters for biogas process control. In this work, a one-chip integrated combined amperometric/field-effect sensor for monitoring the dissolved H₂ concentration has been developed for biogas applications. The combination of two different transducer principles might allow a more accurate and reliable measurement of dissolved H₂ as an early warning indicator of digester failures. The feasibility of the approach has been demonstrated by simultaneous amperometric/field-effect measurements of dissolved H₂ concentrations in electrolyte solutions. Both, the amperometric and the field-effect transducer show a linear response behaviour in the H₂ concentration range from 0.1 to 3% (v/v) with a slope of 198.4 ± 13.7 nA/% (v/v) and 14.9 ± 0.5 mV/% (v/v), respectively.
Deoxyribonucleic acid (DNA) and protein recognition are now standard tools in biology. In addition, the special optical properties of microsphere resonators expressed by the high quality factor (Q-factor) of whispering gallery modes (WGMs) or morphology dependent resonances (MDRs) have attracted the attention of the biophotonic community. Microsphere-based biosensors are considered as powerful candidates to achieve label-free recognition of single molecules due to the high sensitivity of their WGMs. When the microsphere surface is modified with biomolecules, the effective refractive index and the effective size of the microsphere change resulting in a resonant wavelength shift. The transverse electric (TE) and the transverse magnetic (TM) elastic light scattering intensity of electromagnetic waves at 600 and 1400 nm are numerically calculated for DNA and unspecific binding of proteins to the microsphere surface. The effect of changing the optical properties was studied for diamond (refractive index 2.34), glass (refractive index 1.50), and sapphire (refractive index 1.75) microspheres with a 50 µm radius. The mode spacing, the linewidth of WGMs, and the shift of resonant wavelength due to the change in radius and refractive index, were analyzed by numerical simulations. Preliminary results of unspecific binding of biomolecules are presented. The calculated shift in WGMs can be used for biomolecules detection.
In this paper we present CAESAR, an intelligent domestic service robot. In domestic settings for service robots complex tasks have to be accomplished. Those tasks benefit from deliberation, from robust action execution and from flexible methods for human–robot interaction that account for qualitative notions used in natural language as well as human fallibility. Our robot CAESAR deploys AI techniques on several levels of its system architecture. On the low-level side, system modules for localization or navigation make, for instance, use of path-planning methods, heuristic search, and Bayesian filters. For face recognition and human–machine interaction, random trees and well-known methods from natural language processing are deployed. For deliberation, we use the robot programming and plan language READYLOG, which was developed for the high-level control of agents and robots; it allows combining programming the behaviour using planning to find a course of action. READYLOG is a variant of the robot programming language Golog. We extended READYLOG to be able to cope with qualitative notions of space frequently used by humans, such as “near” and “far”. This facilitates human–robot interaction by bridging the gap between human natural language and the numerical values needed by the robot. Further, we use READYLOG to increase the flexible interpretation of human commands with decision-theoretic planning. We give an overview of the different methods deployed in CAESAR and show the applicability of a system equipped with these AI techniques in domestic service robotics