Stochastic system for generalized polytropic filtration

In this paper, we study a certain class of stochastic quasilinear parabolic equations describing a generalized polytropic elastic filtration in the framework of variable exponents Lebesgue and Sobolev spaces. We establish an existence result in the infinite dimensional framework of weak probabilistic solutions when the forcing terms do not satisfy Lipschitz conditions, and the governing equations are subjected to cylindrical Wiener processes. We use a Galerkin method, derive crucial a priori estimates for the approximate solutions, and combine profound analytic and probabilistic compactness results in order to pass to the limit. Several difficulties arise in obtaining these uniform bounds and passing to the limit since the nonlinear elliptic part of the leading operator admits nonstandard growth. Apart from adapting the above essential tools, we extend classical methods of monotonicity to the present situation.     

Cone evolution on VUV laser ablated polymers

We report on conical microstructures formed on polycarbonate and polyallyl di-glycol carbonate (CR39) ablated using 157-nm F₂ laser radiation. These are distinguished by having smooth, straight walls and, for CR39, sharp tips, together with interference and diffraction fringes around their base. Etch-rate modelling of a non-planar surface and diffraction-modulated fluence is used to explore how cones may evolve, and an estimate is made of thermal loading on microcones.     

ITO electrode modified with Pt nanodendrites-decorated ZnO nanorods for enzymatic glucose sensor

Journal of Solid State Electrochemistry - This work demonstrated the property enhancement of Pt nanodendrite (PtNDs)-decorated ZnO nanorods (ZnONRs) modified indium tin oxide (ITO) electrode for an...     

On the Performance of Free Radicals Combined Electrocoagulation Treatment Processes

The electrocoagulation (EC) combined treatment processes have shown promising performances in which the removal of pollutants from industrial wastewater was greatly enhanced. The integration of a free radical producing step with EC has been considered as one of these new combinations that show synergy and improvements in the overall cleaning process performance. This review is devoted to discuss and analyze references on free radicals-assisted EC processes. Different combinations of free radical mechanisms were cited in the literature during the last two decades. They included ozone, advanced oxidation and ultrasound energy-assisted EC. It was noted that most of those studies were lab-scale processes that used synthetic wastewaters rather than real wastewaters. In addition the performances of those combined processes were improved compared to the EC process alone. This review considers the main parameters of free radical EC processes such as mechanisms, kinetic models, scale-up and cost estimation. Many concluding remarks were stated to give insights for possible future investigations. It seems from the results that the ozone-assisted EC is the most efficient combination since its removal efficiency is high in most applications. On the other hand, the combination of ultrasonic energy with EC was reported to reduce electrode passivation.     

Non‐interacting single‐impurity Anderson model: solution without using the equation‐of‐motion method

Ground‐state properties of the non‐interacting symmetric single‐impurity Anderson model (SIAM) are derived from the corresponding eigenenergy equation. Explicit formulae are given for the ground‐state energy, the hybridization, and the momentum distribution that are essential quantities for variational approaches to the interacting model. Various spectral functions, e.g., the total density of states, the phase shift function, and the impurity spectral function, are shown to agree with those obtained from the equation‐of‐motion method (see supplementary material). For a constant hybridization strength and a semi‐elliptic host density of states it is seen that the impurity spectral function builds up weight at the band edges.

     

A methoxylated quercetin glycoside harnesses HCC tumor progression in a TP53/miR-15/miR-16 dependent manner

Abstract

This study focused on studying the impact of flavonoids isolated from Cleome droserifolia on HCC cell lines and to further unveil their possible impact on TP53 and its downstream tumor suppressor miRNAs. Three flavonol glycosides were isolated from C. droserifolia namely, Isorhamnetin-3-O-β-D-glucoside (1), Quercetin-3`-methoxy-3-O-(4``-acetylrhamnoside)-7-O-α-rhamnoside (2), and Kaempferol-4`-methoxy-3,7-O-dirhamnoside (3). They showed a concentration and time dependent reduction in cellular viability and anchorage-independent growth of HCC cells. Moreover, they exhibited a decrease in the migrating capacity of HepG2 cells in a pattern similar to positive control cells. (2) Showed the most potent effects in halting HCC tumorigenic activity (IC₅₀=36?±?1.70?µM) and a repression of the cellular proliferation rate of HepG2 cells. Restoration of TP53 and its downstream tumor suppressor miRNAs; miR-15a, miR-16, miR-34a by (2) was observed. Moreover, attenuation of (2) mediated actions was shown upon using anti-miR-15a and anti-miR-16. To conclude, this study crystallizes a novel role of C. droserifolia in harnessing HCC progression in-vitro with a possible contribution of TP53/miR-15a/miR-16.     

Selectivity control in the separation of aromatic amino acid enantiomers with sulphated beta-cyclodextrin

Control of selectivity in the enantiomeric separation of three aromatic amino acids (phenylalanine, tyrosine and tryptophan) is demonstrated by electrokinetic capillary chromatography utilising temperature variations coupled with the use of sulphated-beta-cyclodextrin (s-beta-CD) as a pseudostationary phase. The concentration of s-beta-CD and temperature were used as experimental variables to control the observed selectivity. A double-coated capillary was used and proved very robust with reproducibility of migration times being <2.0% R.S.D. between runs and <2.6% on using a new capillary. The system was modelled successfully using an artificial neural network (ANN) comprising one input layer, two hidden layers and one output layer. The model accurately described the observed separations with a correlation coefficient of 0.999 being observed between predicted and observed migration times. Selectivity optimisation was achieved using the normalised resolution product and minimum resolution criteria, with both providing optima at different experimental conditions. The selectivity changes observed also allowed the estimation of electrolyte temperatures within the capillary at high operating currents (>100 microA). Using a 50 microm i.d. capillary and an electrolyte comprising 20 mM phosphate and 15 mM s-beta-CD, a temperature of 52 degrees C was calculated within the capillary at an applied voltage of +30 kV.     

Mixed-mode electrokinetic chromatography of aromatic bases with two pseudo-stationary phases and pH control

The electrokinetic chromatographic (EKC) separation of a series of aromatic bases was achieved utilising an electrolyte system comprising an anionic soluble polymer (polyvinylsulfonic acid, PVS) and a neutral beta-cyclodextrin (beta-CD) as pseudo-stationary phases. The separation mechanism was based on a combination of electrophoresis, ion-exchange interactions with PVS, and hydrophobic interactions with beta-CD. The extent of each chromatographic interaction was independently variable, allowing for control of the separation selectivity of the system. The ion-exchange and the hydrophobic interactions could be varied by changing the PVS and the beta-CD concentrations, respectively. Additionally, mobilities of the bases could be controlled by varying pH, due to their large range of pKa values. The separation system was very robust with reproducibility of migration times being <2% RSD. The two-dimensional parameter space defined by the two variables, [beta-CD] and %PVS, was modelled using a physical model derived from first principles. This model gave very good correlation between predicted and observed mobilities (r2=0.999) for the 13 aromatic bases and parameters derived from the model agreed with the expected ion-exchange and hydrophobic character of each analyte. The complexity of the mathematical model was increased to include pH and this three-dimensional system was modelled successfully using an artificial neural network (ANN). Optimisation of both the two-dimensional and three-dimensional systems was achieved using the normalised resolution product and minimum resolution criteria. An example of using the ANN to predict conditions needed to obtain a separation with a desired migration order between two of the analytes is also shown.