Concentration polarization model of spiral-wound membrane modules with application to batch-mode RO desalination of brackish water

Batch-mode reverse osmosis (batch-RO) operation is considered a promising desalination method due to its low energy requirement compared to other RO system arrangements. To improve and predict batch-RO performance, studies on concentration polarization (CP) are carried out. The Kimura-Sourirajan mass-transfer model is applied and validated by experimentation with two different spiral-wound RO elements. Explicit analytical Sherwood correlations are derived based on experimental results. For batch-RO operation, a new genetic algorithm method is developed to estimate the Sherwood correlation parameters, taking into account the effects of variation in operating parameters. Analytical procedures are presented, then the mass transfer coefficient models are developed for different operation processes, i.e., batch-RO and continuous RO. The CP related energy loss in batch-RO operation is quantified based on the resulting relationship between feed flow rates and mass transfer coefficients. It is found that CP increases energy consumption in batch-RO by about 25% compared to the ideal case in which CP is absent. For continuous RO process, the derived Sherwood correlation predicted CP accurately. In addition, we determined the optimum feed flow rate of our batch-RO system.

Upconversion assisted self-pulsing in a high-concentration erbium doped fiber laser

We report results on experimental and theoretical characterisation of self-pulsing in high concentration erbium doped fibre laser which is free from erbium clusters. Unlike previous models of self-pulsing accounting for pair-induced quenching (PIQ) on the clustered erbium ions, new model has been developed with accounting for statistical nature of the excitation migration and upconversion and resonance-like pumpto-signal intensity noise transfer. The obtained results are in a good agreement with the experimental data.

A novel concentration dependent amino acid ion pair strategy to mediate drug permeation using indomethacin as a model insoluble drug

Assessment of oral drug bioavailability is an important parameter for new chemical entities (NCEs) in drug development cycle. After evaluating the pharmacological response of these new molecules, the following critical stage is to investigate their in vitro permeability. Despite the great success achieved by prodrugs, covalent linking the drug molecule with a hydrophobic moiety might result in a new entity that might be toxic or ineffective. Therefore, an alternative that would improve the drug uptake without affecting the efficacy of the drug molecule would be advantageous. The aim of the current study is to investigate the effect of ion-pairing on the permeability profile of a model drug: indomethacin (IND) to understand the mechanism behind the permeability improvement across Caco-2 monolayers. Arginine and lysine formed ion-pairs with IND at various molar ratios 1:1, 1:2, 1:4 and 1:8 as reflected by the double reciprocal graphs. The partitioning capacities of the IND were evaluated using octanol/water partitioning studies and the apparent permeabilities (P app) were measured across Caco-2 monolayers for the different formulations. Partitioning studies reflected the high hydrophobicity of IND (Log P = 3) which dropped upon increasing the concentrations of arginine/lysine in the ion pairs. Nevertheless, the prepared ion pairs improved IND permeability especially after 60 min of the start of the experiment. Coupling partitioning and permeability results suggest a decrease in the passive transcellular uptake due to the drop in IND portioning capacities and a possible involvement of active carriers. Future work will investigate which transport gene might be involved in the absorption of the ion paired formulations using molecular biology technologies. © 2014 Elsevier B.V. All rights reserved.

Development of an in-vitro model system to investigate the mechanism of muscle protein catabolism induced by proteolysis-inducing factor

The mechanism of muscle protein catabolism induced by proteolysis-inducing factor, produced by cachexia-inducing murine and human tumours has been studied in vitro using C2C12 myoblasts and myotubes. In both myoblasts and myotubes protein degradation was enhanced by proteolysis-inducing factor after 24 h incubation. In myoblasts this followed a bell-shaped dose-response curve with maximal effects at a proteolysis-inducing factor concentration between 2 and 4 nM, while in myotubes increased protein degradation was seen at all concentrations of proteolysis-inducing factor up to 10 nM, again with a maximum of 4 nM proteolysis-inducing factor. Protein degradation induced by proteolysis-inducing factor was completely attenuated in the presence of cycloheximide (1 μM), suggesting a requirement for new protein synthesis. In both myoblasts and myotubes protein degradation was accompanied by an increased expression of the α-type subunits of the 20S proteasome as well as functional activity of the proteasome, as determined by the 'chymotrypsin-like' enzyme activity. There was also an increased expression of the 19S regulatory complex as well as the ubiquitin-conjugating enzyme (E214k), and in myotubes a decrease in myosin expression was seen with increasing concentrations of proteolysis-inducing factor. These results show that proteolysis-inducing factor co-ordinately upregulates both ubiquitin conjugation and proteasome activity in both myoblasts and myotubes and may play an important role in the muscle wasting seen in cancer cachexia. © 2002 Cancer Research UK.

A dynamic model for the activated sludge treatment of coke oven effluents

This is an Inter-Disciplinary Higher Degree (IHD) thesis about Water Pollution Control in the Iron and Steel Industry. After examining the compositions, and various treatment methods, for the major effluent streams from a typical Integrated Iron and Steel works, it was decided to concentrate investigative work on the activated-sludge treatment of coke-oven effluents. A mathematical model of this process was developed in an attempt to provide a tool for plant management that would enable improved performance, and enhanced control of Works Units. The model differs from conventional models in that allowance is made for the presence of two genera of microorganisms, each of which utilises a particular type of substrate as its energy source. Allowance is also made for the inhibitive effect of phenol on thiocyanate biodegradation, and for the self-toxicity of the bacteria when present in a high substrate concentration environment. The enumeration of the kinetic characteristics of the two groups of micro-organisms was shown to be of major importance. Laboratory experiments were instigated in an attempt to determine accurate values of these coefficients. The use of the Suspended Solids concentration was found to be too insensitive a measure of viable active mass. Other measures were investigated, and Adenosine Triphosphate concentration was chosen as the most effective measure of bacterial populations. Using this measure, a model was developed for phenol biodegradation from experimental results which implicated the possibility of storage of substate prior to metabolism. A model for thiocyanate biodegradation was also developed, although the experimental results indicate that much work is still required in this area.

Persistence in a random bond ising model of socio-econo dynamics

We study the persistence phenomenon in a socio-econo dynamics model using computer simulations at a nite temperature on hypercubic lattices in dimensions up to ve. The model includes a \social" local eld which contains the magnetization at time t. The nearest neighbour quenched interactions are drawn from a binary distribution which is a function of the bond concentration, p. The decay of the persistence probability in the model depends on both the spatial dimension and p. We nd no evidence of \blocking" in this model. We also discuss the implications of our results for possible applications in the social and economic elds. It is suggested that the absence, or otherwise, of blocking could be used as a criterion to decide on the validity of a given model in dierent scenarios.

The development and stability analysis of a nonlinear growth model for microorganisms

A nonlinear dynamic model of microbial growth is established based on the theories of the diffusion response of thermodynamics and the chemotactic response of biology. Except for the two traditional variables, i.e. the density of bacteria and the concentration of attractant, the pH value, a crucial influencing factor to the microbial growth, is also considered in this model. The pH effect on the microbial growth is taken as a Gaussian function G0e-(f- fc)2/G1, where G0, G1 and fc are constants, f represents the pH value and fc represents the critical pH value that best fits for microbial growth. To study the effects of the reproduction rate of the bacteria and the pH value on the stability of the system, three parameters a, G0 and G1 are studied in detail, where a denotes the reproduction rate of the bacteria, G0 denotes the impacting intensity of the pH value to microbial growth and G1 denotes the bacterial adaptability to the pH value. When the effect of the pH value of the solution which microorganisms live in is ignored in the governing equations of the model, the microbial system is more stable with larger a. When the effect of the bacterial chemotaxis is ignored, the microbial system is more stable with the larger G1 and more unstable with the larger G0 for f0 > fc. However, the stability of the microbial system is almost unaffected by the variation G0 and G1 and it is always stable for f0 < fc under the assumed conditions in this paper. In the whole system model, it is more unstable with larger G1 and more stable with larger G0 for f0 < fc. The system is more stable with larger G1 and more unstable with larger G0 for f0 > fc. However, the system is more unstable with larger a for f0 < fc and the stability of the system is almost unaffected by a for f0 > fc. The results obtained in this study provide a biophysical insight into the understanding of the growth and stability behavior of microorganisms.

An X-ray micro-fluorescence study to investigate the distribution of Al, Si, P and Ca ions in the surrounding soft tissue after implantation of a calcium phosphate-mullite ceramic composite in a rabbit animal model

Synthetic calcium phosphates, despite their bioactivity, are brittle. Calcium phosphate-mullite composites have been suggested as potential dental and bone replacement materials which exhibit increased toughness. Aluminium, present in mullite, has however been linked to bone demineralisation and neurotoxicity: it is therefore important to characterise the materials fully in order to understand their in vivo behaviour. The present work reports the compositional mapping of the interfacial region of a calcium phosphate-20 wt% mullite biocomposite/soft tissue interface, obtained from the samples implanted into the long bones of healthy rabbits according to standard protocols (ISO-10993) for up to 12 weeks. X-ray micro-fluorescence was used to map simultaneously the distribution of Al, P, Si and Ca across the ceramic-soft tissue interface. A well defined and sharp interface region was present between the ceramic and the surrounding soft tissue for each time period examined. The concentration of Al in the surrounding tissue was found to fall by two orders of magnitude, to the background level, within similar to 35 mu m of the implanted ceramic.

Reduction of circulating soluble Flt-1 alleviates preeclampsia-like symptoms in a mouse model

Preeclampsia (PE) is characterized by widespread endothelial damage with hypertension, proteinuria, glomeruloendotheliosis and elevated soluble Flt-1 (sFlt-1), a natural occurring antagonist of vascular endothelial growth factor (VEGF). Cancer patients receiving anti-VEGF therapy exhibit similar symptoms. We suggested that a decrease in circulating sFlt-1 would alleviate the symptoms associated with PE. Adenoviral (Adv) overexpression of sFlt-1 induced proteinuria, caused glomerular damage and increase in blood pressure in female Balb/c mice. Circulating level of sFlt-1 above 50 ng/ml plasma induced severe vascular damage and glomerular endotheliosis. Albumin concentration in urine was elevated up to 30-fold, compared to control AdvGFP-treated animals. The threshold of kidney damage was in the range of 20-30 ng/ml sFlt-1 in plasma (8-15 ng/ml in urine). Co-administration of AdvsFlt-1 with AdvVEGF to neutralize circulating sFlt-1 resulted in more than a 70% reduction in free sFlt-1 in plasma, more than 80% reduction in urine and rescued the damaging effect of sFlt-1 on the kidneys. This demonstrates that below a critical threshold sFlt-1 fails to elicit damage to the fenestrated endothelium and that co-expression of VEGF is able to rescue effects mediated by sFlt-1 overexpression.

Protein interactions studied by SAXS:effect of ionic strength and protein concentration for BSA in aqueous solutions

We have studied a series of samples of bovine serum albumin (BSA) solutions with protein concentration, c, ranging from 2 to 500 mg/mL and ionic strength, I, from 0 to 2 M by small-angle X-ray scattering (SAXS). The scattering intensity distribution was compared to simulations using an oblate ellipsoid form factor with radii of 17 x 42 x 42 A, combined with either a screened Coulomb, repulsive structure factor, S-SC(q), or an attractive square-well structure factor, S-SW(q). At pH = 7, BSA is negatively charged. At low ionic strength, I <0.3 M, the total interaction exhibits a decrease of the repulsive interaction when compared to the salt-free solution, as the net surface charge is screened, and the data can be fitted by assuming an ellipsoid form factor and screened Coulomb interaction. At moderate ionic strength (0.3-0.5 M), the interaction is rather weak, and a hard-sphere structure factor has been used to simulate the data with a higher volume fraction. Upon further increase of the ionic strength (I >= 1.0 M), the overall interaction potential was dominated by an additional attractive potential, and the data could be successfully fitted by an ellipsoid form factor and a square-well potential model. The fit parameters, well depth and well width, indicate that the attractive potential caused by a high salt concentration is weak and long-ranged. Although the long-range, attractive potential dominated the protein interaction, no gelation or precipitation was observed in any of the samples. This is explained by the increase of a short-range, repulsive interaction between protein molecules by forming a hydration layer with increasing salt concentration. The competition between long-range, attractive and short-range, repulsive interactions accounted for the stability of concentrated BSA solution at high ionic strength.

Total solution of Gibilaro and Rowe model for a segregating fluidised bed

This study re-examines the one-dimensional equilibrium model of Gibilaro and Rowe (1974) for a segregating gas fluidized bed. The model was based on volumetric jetsam concentration and divided the bed contents into bulk and wake phases, taking account of bulk and wake flux, segregation, exchange between the bulk and wake phases, and axial mixing. Due to the complex nature of the model and its unstable solution, the lack of computing power at the time prevented the authors from doing little more than the analytical solutions to specific cases of this model. This paper provides a numerical total solution and allows the effect of the respective parameters to be compared for the first time. There is also a comparison with experimental results, which showed a reasonable agreement.

Optimization of anterior eye fluorescein viewing

Purpose: To optimize anterior eye fluorescein viewing and image capture. Design: Prospective experimental investigation. Methods: The spectral radiance of ten different models of slit-lamp blue luminance and the spectral transmission of three barrier filters were measured. Optimal clinical instillation of fluorescein was evaluated by a comparison of four different instillation methods of fluorescein into 10 subjects. Two methods used a floret, and two used minims of different concentration. The resulting fluorescence was evaluated for quenching effects and efficiency over time. Results: Spectral radiance of the blue illumination typically had an average peak at 460 nm. Comparison between three slit-lamps of the same model showed a similar spectral radiance distribution. Of the slit-lamps examined, 8.3% to 50.6% of the illumination output was optimized for >80% fluorescein excitation, and 1.2% to 23.5% of the illumination overlapped with that emitted by the fluorophore. The barrier filters had an average cut-off at 510 to 520 nm. Quenching was observed for all methods of fluorescein instillation. The moistened floret and the 1% minim reached a useful level of fluorescence in on average ∼20s (∼2.5× faster than the saturated floret and 2% minim) and this lasted for ∼160 seconds. Conclusions: Most slit-lamps' blue light and yellow barrier filters are not optimal for fluorescein viewing and capture. Instillation of fluorescein using a moistened floret or 1% minim seems most clinically appropriate as lower quantities and concentrations of fluorescein improve the efficiency of clinical examination. © 2006 Elsevier Inc. All rights reserved.

Laser-induced breakdown spectroscopy quantitative analysis method via adaptive analytical line selection and relevance vector machine regression model

Abstract A new LIBS quantitative analysis method based on analytical line adaptive selection and Relevance Vector Machine (RVM) regression model is proposed. First, a scheme of adaptively selecting analytical line is put forward in order to overcome the drawback of high dependency on a priori knowledge. The candidate analytical lines are automatically selected based on the built-in characteristics of spectral lines, such as spectral intensity, wavelength and width at half height. The analytical lines which will be used as input variables of regression model are determined adaptively according to the samples for both training and testing. Second, an LIBS quantitative analysis method based on RVM is presented. The intensities of analytical lines and the elemental concentrations of certified standard samples are used to train the RVM regression model. The predicted elemental concentration analysis results will be given with a form of confidence interval of probabilistic distribution, which is helpful for evaluating the uncertainness contained in the measured spectra. Chromium concentration analysis experiments of 23 certified standard high-alloy steel samples have been carried out. The multiple correlation coefficient of the prediction was up to 98.85%, and the average relative error of the prediction was 4.01%. The experiment results showed that the proposed LIBS quantitative analysis method achieved better prediction accuracy and better modeling robustness compared with the methods based on partial least squares regression, artificial neural network and standard support vector machine.

A laser induced breakdown spectroscopy quantitative analysis method based on the robust least squares support vector machine regression model

Data fluctuation in multiple measurements of Laser Induced Breakdown Spectroscopy (LIBS) greatly affects the accuracy of quantitative analysis. A new LIBS quantitative analysis method based on the Robust Least Squares Support Vector Machine (RLS-SVM) regression model is proposed. The usual way to enhance the analysis accuracy is to improve the quality and consistency of the emission signal, such as by averaging the spectral signals or spectrum standardization over a number of laser shots. The proposed method focuses more on how to enhance the robustness of the quantitative analysis regression model. The proposed RLS-SVM regression model originates from the Weighted Least Squares Support Vector Machine (WLS-SVM) but has an improved segmented weighting function and residual error calculation according to the statistical distribution of measured spectral data. Through the improved segmented weighting function, the information on the spectral data in the normal distribution will be retained in the regression model while the information on the outliers will be restrained or removed. Copper elemental concentration analysis experiments of 16 certified standard brass samples were carried out. The average value of relative standard deviation obtained from the RLS-SVM model was 3.06% and the root mean square error was 1.537%. The experimental results showed that the proposed method achieved better prediction accuracy and better modeling robustness compared with the quantitative analysis methods based on Partial Least Squares (PLS) regression, standard Support Vector Machine (SVM) and WLS-SVM. It was also demonstrated that the improved weighting function had better comprehensive performance in model robustness and convergence speed, compared with the four known weighting functions.

A compartmental CFD-PBM model of high shear wet granulation

The conventional, geometrically lumped description of the physical processes inside a high shear granulator is not reliable for process design and scale-up. In this study, a compartmental Population Balance Model (PBM) with spatial dependence is developed and validated in two lab-scale high shear granulation processes using a 1.9L MiPro granulator and 4L DIOSNA granulator. The compartmental structure is built using a heuristic approach based on computational fluid dynamics (CFD) analysis, which includes the overall flow pattern, velocity and solids concentration. The constant volume Monte Carlo approach is implemented to solve the multi-compartment population balance equations. Different spatial dependent mechanisms are included in the compartmental PBM to describe granule growth. It is concluded that for both cases (low and high liquid content), the adjustment of parameters (e.g. layering, coalescence and breakage rate) can provide a quantitative prediction of the granulation process.