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The ideal combination among biomolecules and nanomaterials is the key for reaching biosensing units with high sensitivity. The challenge, however, is to find out a stable and sensitive film architecture that can be incorporated on the sensor’s surface. In this paper, we report on the benefits of incorporating a layer-by-layer (LbL) nanofilm of polyamidoamine (PAMAM) dendrimer and carbon nanotubes (CNTs) on capacitive electrolyte-insulator-semiconductor (EIS) field-effect sensors for detecting urea. Three sensor arrangements were studied in order to investigate the adequate film architecture, involving the LbL film with the enzyme urease: (i) urease immobilized directly onto a bare EIS [EIS-urease] sensor; (ii) urease atop the LbL film over the EIS [EIS-(PAMAM/CNT)-urease] sensor; and (iii) urease sandwiched between the LbL film and another CNT layer [EIS-(PAMAM/CNT)-urease-CNT]. The surface morphology of all three urea-based EIS biosensors was investigated by atomic force microscopy (AFM), while the biosensing abilities were studied by means of capacitance–voltage (C/V) and dynamic constant-capacitance (ConCap) measureaments at urea concentrations ranging from 0.1 mM to 100 mM. The EIS-urease and EIS-(PAMAM/CNT)-urease sensors showed similar sensitivity (∼18 mV/decade) and a nonregular signal behavior as the urea concentration increased. On the other hand, the EIS-(PAMAM/CNT)-urease-CNT sensor exhibited a superior output signal performance and higher sensitivity of about 33 mV/decade. The presence of the additional CNT layer was decisive to achieve a urea based EIS sensor with enhanced properties. Such sensitive architecture demonstrates that the incorporation of an adequate hybrid enzyme-nanofilm as sensing unit opens new prospects for biosensing applications using the field-effect sensor platform.
A microcavity-based deoxyribonucleic acid (DNA) optical biosensor is demonstrated for the first time using synthetic sapphire for the optical cavity. Transmitted and elastic scattering intensity at 1510 nm are analyzed from a sapphire microsphere (radius 500 μm, refractive index 1.77) on an optical fiber half coupler. The 0.43 nm angular mode spacing of the resonances correlates well with the optical size of the sapphire sphere. Probe DNA consisting of a 36-mer fragment was covalently immobilized on a sapphire microsphere and hybridized with a 29-mer target DNA. Whispering gallery modes (WGMs) were monitored before the sapphire was functionalized with DNA and after it was functionalized with single-stranded DNA (ssDNA) and double-stranded DNA (dsDNA). The shift in WGMs from the surface modification with DNA was measured and correlated well with the estimated thickness of the add-on DNA layer. It is shown that ssDNA is more uniformly oriented on the sapphire surface than dsDNA. In addition, it is shown that functionalization of the sapphire spherical surface with DNA does not affect the quality factor (Q≈104) of the sapphire microspheres. The use of sapphire is especially interesting because this material is chemically resilient, biocompatible, and widely used for medical implants.
As a semiconductor-based electrochemical sensor, the light-addressable potentiometric sensor (LAPS) can realize two dimensional visualization of (bio-)chemical reactions at the sensor surface addressed by localized illumination. Thanks to this imaging capability, various applications in biochemical and biomedical fields are expected, for which the spatial resolution is critically significant. In this study, therefore, the spatial resolution of the LAPS was investigated in detail based on the device simulation. By calculating the spatiotemporal change of the distributions of electrons and holes inside the semiconductor layer in response to a modulated illumination, the photocurrent response as well as the spatial resolution was obtained as a function of various parameters such as the thickness of the Si substrate, the doping concentration, the wavelength and the intensity of illumination.
The simulation results verified that both thinning the semiconductor substrate and increasing the doping concentration could improve the spatial resolution, which were in good agreement with known experimental results and theoretical analysis. More importantly, new findings of interests were also obtained. As for the dependence on the wavelength of illumination, it was found that the known dependence was not always the case. When the Si substrate was thick, a longer wavelength resulted in a higher spatial resolution which was known by experiments. When the Si substrate was thin, however, a longer wavelength of light resulted in a lower spatial resolution. This finding was explained as an effect of raised concentration of carriers, which reduced the thickness of the space charge region.
The device simulation was found to be helpful to understand the relationship between the spatial resolution and device parameters, to understand the physics behind it, and to optimize the device structure and measurement conditions for realizing higher performance of chemical imaging systems.
The possibility of using the atomic-force microscopy as a method for detection of the analytical signal from plasticized polymeric sensor membranes was analyzed. The surfaces of cadmium-selective membranes based on two polymeric matrices were examined. The digital images were processed with multivariate image analysis techniques. A correlation was found between the surface profile of an ion-selective membrane and the concentration of the ion in solution.
Validation of a novel method for detecting and stabilizing malfunctioning areas in fuel cell stacks
(2014)
In this paper a setup for detecting malfunctioning areas of MEAs in fuel cell stacks is described. Malfunctioning areas generate electric cross currents inside bipolar plates. To exploit this we suggest bipolar plates consisting not of two but of three layers. The third one is a highly conducting layer and segmented such that the cross currents move along the segments to the surface of the stack where they can be measured by an inductive sensor. With this information a realistic model can be used to detect the malfunctioning area. Furthermore the third layer will prevent any current inhomogeneity of a malfunctioning cell to spread to neighbouring cells in the stack. In this work the results of measurements in a realistic cell setup will be compared with the results obtained in simulation studies with the same configuration. The basis for the comparison is the reliable characterisation of the electrical properties of the cell components and the implication of these results into the simulation model. The experimental studies will also show the limits in the maximum number of segments, which can be used for a reliable detection of cross currents.
A novel photoexcitation method for the light-addressable potentiometric sensor (LAPS) realized a higher spatial resolution of chemical imaging. In this method, a modulated light probe, which generates the alternating photocurrent signal, is surrounded by a ring of constant light, which suppresses the lateral diffusion of photocarriers by enhancing recombination. A device simulation verified that a higher spatial resolution could be obtained by adjusting the gap between the modulated and constant light. It was also found that a higher intensity and a longer wavelength of constant light was more effective. However, there exists a tradeoff between the spatial resolution and the amplitude of the photocurrent, and thus, the signal-to-noise ratio. A tilted incidence of constant light was applied, which could achieve even higher resolution with a smaller loss of photocurrent.
The chemical imaging sensor, which is based on the principle of the light-addressable potentiometric sensor (LAPS), is a powerful tool to visualize the spatial distribution of chemical species on the sensor surface. The spatial resolution of this sensor depends on the diffusion of photocarriers excited by a modulated light. In this study, a novel hybrid fiber-optic illumination was developed to enhance the spatial resolution. It consists of a modulated light probe to generate a photocurrent signal and a ring of constant light, which suppresses the lateral diffusion of minority carriers excited by the modulated light. It is demonstrated that the spatial resolution was improved from 92 μm to 68 μm.
Molecular-genetic identification of emerged novel invasive pathogens of Asiatic Elm Ulmus pumila L
(2014)
The dwarf elm Ulmus pumila L. (Ulmaceae) is one of indigenous species of flora in Kazakhstan and forms a basis of dendroflora in virtually all settlements of the region. In the past decade, multiple outbreaks of previously unknown diseases of the small-leaved elm have been registered. In our study, by the molecular-genetic analysis it was found that the pathogens responsible for the outbreaks are microfungi belonging to the genus Fusarium – F. solani and F. oxysporum. The nucleotide sequences (ITS regions) isolated from the diseased trees showed very high similarity with the GenBank control numbers EU625403.1 and FJ478128.1 (100.0 and 99.0 % respectively). Oncoming research will focus on the search of natural microbial antagonists of the discovered phytopathogens.
Network theory provides novel concepts that promise an improved characterization of interacting dynamical systems. Within this framework, evolving networks can be considered as being composed of nodes, representing systems, and of time-varying edges, representing interactions between these systems. This approach is highly attractive to further our understanding of the physiological and pathophysiological dynamics in human brain networks. Indeed, there is growing evidence that the epileptic process can be regarded as a large-scale network phenomenon. We here review methodologies for inferring networks from empirical time series and for a characterization of these evolving networks. We summarize recent findings derived from studies that investigate human epileptic brain networks evolving on timescales ranging from few seconds to weeks. We point to possible pitfalls and open issues, and discuss future perspectives.
The scope of this study is the measurement of endotoxin adsorption rate for carbonized rice husk. It showed good adsorption properties for LPS. During the batch experiments, several techniques were used and optimized for improving the material’s adsorption behavior. Also, with the results obtained it was possible to differentiate the materials according to their adsorption capacity and kinetic characteristics.
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.
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.
Two single-incision mini-slings used for treating urinary incontinence in women are compared with respect to the stresses they produce in their surrounding tissue. In an earlier paper we experimentally observed that these implants produce considerably different stress distributions in a muscle tissue equivalent. Here we perform 2D finite element analyses to compare the shear stresses and normal stresses in the tissue equivalent for the two meshes and to investigate their failure behavior. The results clearly show that the Gynecare TVT fails for increasing loads in a zipper-like manner because it gradually debonds from the surrounding tissue. Contrary to that, the tissue at the ends of the DynaMesh-SIS direct may rupture but only at higher loads. The simulation results are in good agreement with the experimental observations thus the computational model helps to interpret the experimental results and provides a tool for qualitative evaluation of mesh implants.
Successful bone sawing requires a high level of skill and experience, which could be gained by the use of Virtual Reality-based simulators. A key aspect of these medical simulators is realistic force feedback. The aim of this paper is to model the bone sawing process in order to develop a valid training simulator for the bilateral sagittal split osteotomy, the most often applied corrective surgery in case of a malposition of the mandible. Bone samples from a human cadaveric mandible were tested using a designed experimental system. Image processing and statistical analysis were used for the selection of four models for the bone sawing process. The results revealed a polynomial dependency between the material removal rate and the applied force. Differences between the three segments of the osteotomy line and between the cortical and cancellous bone were highlighted.
This paper develops a new finite element method (FEM)-based upper bound algorithm for limit and shakedown analysis of hardening structures by a direct plasticity method. The hardening model is a simple two-surface model of plasticity with a fixed bounding surface. The initial yield surface can translate inside the bounding surface, and it is bounded by one of the two equivalent conditions: (1) it always stays inside the bounding surface or (2) its centre cannot move outside the back-stress surface. The algorithm gives an effective tool to analyze the problems with a very high number of degree of freedom. Our numerical results are very close to the analytical solutions and numerical solutions in literature.