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- Antarctic Glaciology (1)
- DNA hybridization (1)
- Extraterrestrial Glaciology (1)
- Field-effect sensor (1)
- Glaciological instruments and methods (1)
- LAPS (1)
- Light-addressable Potentiometric Sensor (1)
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- lipopolysaccharide (1)
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Following earlier studies, we present forward and inverse simulations of heat and fluid transport of the upper crust using a local 3-D model of the Kola area. We provide best estimates for palaeotemperatures and permeabilities, their errors and their dependencies. Our results allow discriminating between the two mentioned processes to a certain extent, partly resolving the non-uniqueness of the problem. We find clear indications for a significant contribution of advective heat transport, which, in turn, imply only slightly lower ground surface temperatures during the last glacial maximum relative to the present value. These findings are consistent with the general background knowledge of (i) the fracture zones and the corresponding fluid movements in the bedrock and (ii) the glacial history of the Kola area.
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).
Knowledge-based productivity in “low-tech” industries: evidence from firms in developing countries
(2014)
Using firm-level data from five developing countries—Brazil, Ecuador, South Africa, Tanzania, and Bangladesh—and three industries—food processing, textiles, and the garments and leather products—this article examines the importance of various sources of knowledge for explaining productivity and formally tests whether sector- or country-specific characteristics dominate these relationships. Knowledge sources driving productivity appear mainly sector specific. Also differences in the level of development affect the effectiveness of knowledge sources. In the food processing sector, firms with higher educated managers are more productive, and in least-developed countries, additionally those with technology licenses and imported machinery and equipment. In the capital-intensive textiles sector, productivity is higher in firms that conduct R&D. In the garments and leather products sector, higher education of the managers, licensing, and R&D raise productivity.
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.
Picosecond dynamics in haemoglobin from different species: A quasielastic neutron scattering study
(2014)
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.
Persistent infection with the high-risk Human Papillomavirus type 16 (HPV 16) is the causative event for the development of cervical cancer and other malignant tumors of the anogenital tract and of the head and neck. Despite many attempts to develop therapeutic vaccines no candidate has entered late clinical trials. An interesting approach is a DNA based vaccine encompassing the nucleotide sequence of the E6 and E7 viral oncoproteins. Because both proteins are consistently expressed in HPV infected cells they represent excellent targets for immune therapy. Here we report the development of 8 DNA vaccine candidates consisting of differently rearranged HPV-16 E6 and E7 sequences within one molecule providing all naturally occurring epitopes but supposedly lacking transforming activity. The HPV sequences were fused to the J-domain and the SV40 enhancer in order to increase immune responses. We demonstrate that one out of the 8 vaccine candidates induces very strong cellular E6- and E7- specific cellular immune responses in mice and, as shown in regression experiments, efficiently controls growth of HPV 16 positive syngeneic tumors. This data demonstrates the potential of this vaccine candidate to control persistent HPV 16 infection that may lead to malignant disease. It also suggests that different sequence rearrangements influence the immunogenecity by an as yet unknown mechanism.
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.