Systematic linearisation of a microfluidic gradient network with unequal solution inlet viscosities demonstrated using glycerol

This paper presents a mathematical and experimental study of the effect of inlet concentration (and therefore viscosity) of glycerol solutions on the performance of a microfluidic network. This was achieved with analytical modelling, implemented in MATLAB, and optical measurement of the entire concentration distribution of the network. A mathematical proposal to improve the linearity of the outlet profile is also implemented and successfully verified experimentally. The concentration gradients of a two inlet–six outlet (2–6) microfluidic network device were obtained with inlet solutions of 10–40 wt% glycerol and flow rates of up to 5 μl/s per inlet. The mathematical model developed gave a good agreement with the experimental results obtained. ‘S’ shaped outlet profiles were obtained for the four glycerol cases studied and the closest results to the model were achieved at an optimised flow rate of 1μl/s for 10 wt% glycerol, 5 μl/s for both 20 and 30 wt% glycerol and 1.5 μl/s for 40 wt% glycerol. The linearity of the outlet profiles for the 20, 30 and 40 wt% inlet glycerol experiments were improved from R ² of 0.977, 0.946 and 0.966, respectively (before linearisation) to their new values of 0.997, 0.995 and 0.974, respectively (after the linearisation). This was performed by application of the mathematical model, at controlled inlet flow rate ratios of 0.77, 0.63 and 0.52 with respect to the viscous inlet, for 20, 30 and 40 wt% glycerol experiments, again with very good agreement of the outlet performance between the experimental and the mathematical results.     

Highly Efficient Water Oxidation Photoanode Made of Surface Modified LaTiO2N Particles

An improved variation of highly active/durable O₂‐evolving LaTiO₂N powder‐based photoelectrode has been fabricated by pre‐cleaning the powder with mild polysulfonic acid and by homogeneous deposition of CoO_x co‐catalyst aided by microwave annealing. The treatment in aqueous solution of poly(4‐styrene sulfonic acid) results in removal of surface LaTiO₂N layers, forming fine pores in the crystallites. The CoO_x co‐catalyst by microwave deposition in Co(NH₃)₆Cl₃/ethylene glycol homogeneously covers the particle surface. The LaTiO₂N powder is fabricated into particle‐transferred electrodes on Ti thin film supported on solid substrate. The modified LaTiO₂N grains on the electrode serve as a highly active O₂‐evolving photoanode achieving 8.9 mA cm^?2 of the photocurrent density at 1.23 V versus reversible hydrogen electrode (RHE) in 0.1 m NaOH (pH 13) under solar‐simulator irradiation Airmass 1.5 Global (AM 1.5G). The activity has been much improved, compared with conventional LaTiO₂N treated in mineral acid or with CoO_x deposited by impregnation. The new electrode also exhibits better durability in fixed‐potential chronoamperometric tests under AM 1.5G irradiation.     

Axotomy reduces the effect of analgesic opioids yet increases the effect of nociceptin on dorsal root ganglion neurons

There is some doubt as to the effectiveness of opioids in the management of neuropathic pain. We therefore examined the actions of morphine and the opioid-like peptide nociceptin (both 1 mu) on dorsal root ganglion (DRG) neurons that were isolated from control or from nerve-injured rats. Both substances reduced omega-conotoxin (CTX) GVIA-sensitive, N-type Ca2+ channel current and small persistent nifedipine/ CTX-insensitive (non-N, non-L type) current. Nifedipine-sensitive L-type current was unaffected. The effect of nociceptin was antagonized by naloxone benzoylhydrazone (nalbzoh) but not by naloxone. Sciatic nerve section (axotomy) profoundly reduced the effects of morphine and the mu-receptor agonist D-ala2, N-Me-Phe4,Gly-ol5 enkephalin (DAMGO). The effect of the kappa-agonist [(+)-(5alpha,7alpha, 8beta)-N-methyl-N-(7-(1-pyrrolidinyl)-1-oxaspiro(4, 5)dec-8-yl)-benzeneacetamide] (U69593) was unchanged, whereas the effect of nociceptin was increased. All agonists produced their strongest effects on the small, putative nociceptive cells and their weakest effects on the largest cells. The delta-receptor agonist, enkephalin D-pen2,5 (DPDPE), was without effect on control or on axotomized cells. These and other data suggest that the functional downregulation of mu-opioid receptors on sensory nerves contributes to the poor efficacy of opioids in neuropathic pain. Also, the increased effectiveness of nociceptin after axotomy supports the hypothesis that its actions are mediated via a "non-opioid" receptor. Pronounced suppression of Ca2+ channel current in axotomized DRG neurons by nociceptin led to a reduction in Ca2+-dependent K+ conductance and a marked increase in excitability. Despite this, the spinal administration of nociceptin or agonists that activate ORL1 (opioid-like orphan receptor) may prove to be of clinical interest in the management of neuropathic pain.     

Ambient intelligence platform using multi-agent system and mobile ubiquitous hardware

In this paper, a novel ambient intelligence (AmI) platform is proposed to facilitate fast integration of different control algorithms, device networks and user interfaces. This platform defines the overall hardware/software architecture and communication standards. It consists of four layers, namely the ubiquitous environment, middleware, multi-agent system and application layer. The multi-agent system is implemented using Java Agent DEvelopment (JADE) framework and allows users to incorporate multiple control algorithms as agents for managing different tasks. The Universal Plug and Play (UPnP) device discovery protocol is used as a middleware, which isolates the multi-agent system and physical ubiquitous environment while providing a standard communication channel between the two. An XML content language has been designed to provide standard communication between various user interfaces and the multi-agent system. A mobile ubiquitous setup box is designed to allow fast construction of ubiquitous environments in any physical space. The real time performance analysis shows the potential of the proposed AmI platform to be used in real-life AmI applications. A case study has also been carried out to demonstrate the possibility of integrating multiple control algorithms in the multi-agent system and achieving a significant improvement on the overall offline learning performance.     

Evaluation of in vitro cytotoxicity,biocompatibility, and changes in the expression of apoptosis regulatory proteins induced by cerium oxide nanocrystals

Abstract

Cerium oxide nanocrystals (CeO₂-NCs) exhibit superoxide dismutase and catalase mimetic activities. Based on these catalytic activities, CeO₂-NCs have been suggested to have the potential to treat various diseases. The crystalline size of these materials is an important factor that influences the performance of CeO₂-NCs. Previous reports have shown that several metal-based nanocrystals, including CeO₂-NCs, can induce cytotoxicity in cancer cells. However, the underlying mechanisms have remained unclear. To characterize the anticancer activities of CeO₂-NCs, several assays related to the mechanism of cytotoxicity and induction of apoptosis has been performed. Here, we have carried out a systematic study to characterize CeO₂-NCs phase purity (X-ray diffraction), morphology (electron microscopy), and optical features (optical absorption, Raman scattering, and photoluminescence) to better establish their potential as anticancer drugs. Our study revealed anticancer effects of CeO₂-NCs in HT29 and SW620 colorectal cancer cell lines with half-maximal inhibitory concentration (IC₅₀) values of 2.26 and 121.18 μg ml^–1, respectively. Reductions in cell viability indicated the cytotoxic potential of CeO₂-NCs in HT29 cells based on inverted and florescence microscopy assessments. The mechanism of cytotoxicity confirmed by estimating possible changes in the expression levels of Bcl2, BclxL, Bax, PARP, cytochrome c, and β-actin (control) proteins in HT29 cells. Down-regulation of Bcl2 and BclxL and up-regulation of Bax, PARP, and cytochrome c proteins suggested the significant involvement of CeO₂-NCs exposure in the induction of apoptosis. Furthermore, biocompatibility assay showed minimum effect of CeO₂-NCs on human red blood cells.     

DC electrical conductivity of polyazomethinethiosemicarbazone metal complexes

Polyazomethinethiosemicarbazone (PATS) metal complexes of Ni(II), Co(II), Cu(II), Zn(II), Cd(II) and Hg(II) metal ions were prepared by reacting the polymer ligand (PATS) with the appropriate metal salt in refluxing DMSO. Elemental analyzes as well as FTIR and electronic spectral data are presented to confirm the formulation of the isolated materials. The spectral data show that the ligand polymer is bonded to the metal ions via the thiol sulfur atom and coordinated through the nitrogen of azomethine group. The DC electrical conductivity measurements of PATS and its metal complexes were measured in the range 300–500 K in the annealed and 5% iodine doped forms. The products gave electrical conductivity in the semiconducting region that increased by heat. The DC electrical conductivity is interpreted using the band gap theory using solitons, polarons and bipolarons. © 2010 Wiley Periodicals, Inc. J Appl Polym Sci, 2010     

A model for the determination of residential water demand by the use of tracers

A model that determines nodal demands by making tracer concentration measurements at specific nodes is developed. The model minimizes the difference between calculated and measured tracer concentrations to determine the unknown demands. Even-, over-, and under-determined cases are considered. For the purpose of verifying the model, tracer concentrations obtained by the model for known demands are considered as measurements. Results showed that the model made very accurate prediction of the unknown demands for both the even-, and the over-determined cases. The under-determined case made less accurate but still good estimates of the unknown demands for the scenarios considered here. The relationship between the sensitivity of the measurement location to the unknown demand and the accuracy of the determined demand is verified. Results showed that the model makes accurate estimation of the unknown demands if measurements are made at sensitive nodes while errors are introduced to the determined demand as a result of assuming measurements at nodes of low sensitivity.