Zeolites P in sodium (NaP) and potassium (KP) forms were used as adsorbents for the removal of calcium (Ca2+) and zinc (Zn2+) cations from aqueous solutions. Zeolite KP was prepared by ion exchange of K+ with Na+ which neutralizes the negative charge of the zeolite P framework structure. The ion exchange capacity of K+ on zeolite NaP was determined through the Freundlich isotherm equilibrium study. Characterization of zeolite KP was determined using infrared spectroscopy and X-ray diffraction (XRD) techniques. From the characterization, the structure of zeolite KP was found to remain stable after the ion exchange process. Zeolites KP and NaP were used for the removal of Ca and Zn from solution. The amount of Ca2+ and Zn2+ in aqueous solution before and after the adsorption by zeolites was analysed using the flame atomic absorption spectroscopy method. The removal of Ca2+ and Zn2+ followed the Freundlich isotherm rather than the Langmuir isotherm model. This result also revealed that zeolite KP adsorbs Ca2+ and Zn2+ more than zeolite NaP and proved that modification of zeolite NaP with potassium leads to an increase in the adsorption efficiency of the zeolite. Therefore, the zeolites NaP and KP can be used for water softening (Ca removal) and reducing water pollution/toxicity (Zn removal).
This study uses computer simulations to study the impact of a motorcycle with the conventional w-beam guardrail. A three-dimensional computer simulation of a scaled hybrid III 50th-percentile male dummy mounted on a motorcycle and colliding with a w-beam guardrail is carried out. A multi-body model of the motorcycle and finite element model of the guardrail are developed using commercially available software. The simulation model is validated with a physical crash test conducted with same initial impact configurations. Impacts at speeds of 32, 48, and 60 km/h at an impact angle at 45 degrees are considered. The predicted forces and accelerations are compared with the biomechanical limits for each body part and the risk of injury to the rider are evaluated. Speed was found to have a significant influence on the level of injury to the head, neck, chest, and femur. A significant reduction of the severity of injuries was found when the impact speed was reduced from 60 to 32km/h. The accelerations experienced by the head and chest are found to be higher than safe levels for impact speeds of 48 and 60 km/h. The biomechanical limit for the right femur is exceeded at all three considered impact speeds. Neck injuries are also a concern, with the predicted tension values and neck bending extent being higher than the biomechanical limit for the 60 km/h impact speed. In light of these results, it is suggested that the design of guardrails should be reviewed with a focus on the safety of motorcyclists.
The mu rhythm is an electroencephalogram (EEG) signal located at the central region of the brain that is frequently used for studies concerning motor activity. Quite often, the EEG data are contaminated with artifacts and the application of blind source separation (BSS) alone is insufficient to extract the mu rhythm component. We present a new two-stage approach to extract the mu rhythm component. The first stage uses second-order blind identification (SOBI) with stationary wavelet transform (SWT) to automatically remove the artifacts. In the second stage, SOBI is applied again to find the mu rhythm component. Our method is first compared with independent component analysis with discrete wavelet transform (ICA-DWT) as well as SOBI-DWT, ICA-SWT, and regression method for artifact removal using simulated EEG data. The results showed that the regression method is more effective in removing electrooculogram (EOG) artifacts, while SOBI-SWT is more effective in removing electromyogram (EMG) artifacts as compared to the other artifact removal methods. Then, all the methods are compared with the direct application of SOBI in extracting mu rhythm components on simulated and actual EEG data from ten subjects. The results showed that the proposed method of SOBI-SWT artifact removal enhances the extraction of the mu rhythm component.
A poly(vinyl alcohol) (PVA) hydrogel composite scaffold containing N,O-carboxymethylated chitosan (NOCC) was tested to assess its potential as a scaffold for cartilage tissue engineering in a weight-bearing environment. The mechanical properties under unconfined compression for different hydration periods were investigated. The effect of supplementing PVA with NOCC (20wt.% PVA:5vol.% NOCC) produced a porosity of 43.3% and this was compared against a non-porous PVA hydrogel (20g PVA: 100ml of water, control). Under non-hydrated conditions, the porous PVA-NOCC hydrogel behaved in a similar way to the control non-porous PVA hydrogel, with similar non-linear stress-strain response under unconfined compression (0-30% strain). After 7days' hydration, the porous hydrogel demonstrated a reduced stiffness (0.002kPa, at 25% strain), resulting in a more linear stiffness relationship over a range of 0-30% strain. Poisson's ratio for the hydrated non-porous and porous hydrogels ranged between 0.73 and 1.18, and 0.76 and 1.33, respectively, suggesting a greater fluid flow when loaded. The stress relaxation function for the porous hydrogel was affected by the hydration period (from 0 to 600s); however the percentage stress relaxation regained by about 95%, after 1200s for all hydration periods assessed. No significant differences were found between the different hydration periods between the porous hydrogels and control. The calculated aggregate modulus, H(A), for the porous hydrogel reduced drastically from 10.99kPa in its non-hydrated state to about 0.001kPa after 7days' hydration, with the calculated shear modulus reducing from 30.92 to 0.14kPa, respectively. The porous PVA-NOCC hydrogel conformed to a biphasic, viscoelastic model, which has the desired properties required for any scaffold in cartilage tissue engineering.
A new Mn(III) complex, [MnCl(H(2)O)(L)].H(2)O.C(2)H(5)OH, where L=2,2'-[1,2-phenylenebis[nitrilomethylylidene]]bis(6-methoxyphenolate), has been synthesized and characterized by single-crystal X-ray diffraction. There is a good agreement between calculated and experimental structural data. The complex is crystallized in orthorhombic with space group Pbca. The Mn1 atom is coordinated with one Schiff base ligand, one water molecule and one chloride anion, forming a six-coordination number. The electronic and fluorescence spectra of the complex were also studied.
Activated sludge models (ASMs) have been widely used as a basis for further model development in wastewater treatment processes. Values for parameters to be used are vital for the accuracy of the modeling approach. A continuous stirred tank reactor (CSTR), as open respirometer with continuous flow for 20 h is used in ASMs. The dissolved oxygen (DO) profile for 11 days was monitored. It was found the mass transfer coefficient K(La) is 0.3 h(-1) during lag and start feed phase and 0.01 h(-1) during stop feed phase, while the heterotrophic yield coefficient Y(H) is 0.44. Some of the chemical oxygen demand (COD) fractionations of palm oil mill effluent (POME) using respirometric test in ASM models are S(s) 50 mg/L, S(I) 16,600 mg/L, X(S) 25,550 mg/L, and X(I) 2,800 mg/L. The comparison of experimental and ASM1 from OUR concentration is found to fit well.
This study aimed to develop an optimal continuous procedure of lipase-catalyzes transesterification of waste cooking palm oil in a packed bed reactor to investigate the possibility of large scale production further. Response surface methodology (RSM) based on central composite rotatable design (CCRD) was used to optimize the two important reaction variables packed bed height (cm) and substrate flow rate(ml/min) for the transesterification of waste cooking palm oil in a continuous packed bed reactor. The optimum condition for the transesterification of waste cooking palm oil was as follows: 10.53 cm packed bed height and 0.57 ml/min substrate flow rate. The optimum predicted fatty acid methyl ester (FAME) yield was 80.3% and the actual value was 79%. The above results shows that the RSM study based on CCRD is adaptable for FAME yield studied for the current transesterification system. The effect of mass transfer in the packed bed reactor has also been studied. Models for FAME yield have been developed for cases of reaction control and mass transfer control. The results showed very good agreement compatibility between mass transfer model and the experimental results obtained from immobilized lipase packed bed reactor operation, showing that in this case the FAME yield was mass transfer controlled.
Chromatin morphologies in human breast cancer cells treated with an anti-cancer agent are analyzed at their early stage of programmed cell death or apoptosis. The gray-level images of nuclear chromatin are modelled as random fields. We used two-dimensional isotropic generalized Cauchy field to characterize local self-similarity and global long-range dependence behaviors in the image spatial data. Generalized Cauchy field allows the description of fractal behavior inferred from fractal dimension and the long-range dependence inferred from correlation exponent to be carried out independently. We demonstrated the usefulness of locally self-similar random fields with long-range dependence for modelling chromatin condensation.
A sequential optimization based on statistical design and one-factor-at-a-time (OFAT) method was employed to optimize the media constituents for the improvement of citric acid production from oil palm empty fruit bunches (EFB) through solid state bioconversion using Aspergillus niger IBO-103MNB. The results obtained from the Plackett-Burman design indicated that the co-substrate (sucrose), stimulator (methanol) and minerals (Zn, Cu, Mn and Mg) were found to be the major factors for further optimization. Based on the OFAT method, the selected medium constituents and inoculum concentration were optimized by the central composite design (CCD) under the response surface methodology (RSM). The statistical analysis showed that the optimum media containing 6.4% (w/w) of sucrose, 9% (v/w) of minerals and 15.5% (v/w) of inoculum gave the maximum production of citric acid (337.94 g/kg of dry EFB). The analysis showed that sucrose (p<0.0011) and mineral solution (p<0.0061) were more significant compared to inoculum concentration (p<0.0127) for the citric acid production.
This paper describes an image analysis technique that objectively measures skin repigmentation for the assessment of therapeutic response in vitiligo treatments. Skin pigment disorders due to the abnormality of melanin production, such as vitiligo, cause irregular pale patches of skin. The therapeutic response to treatment is repigmentation of the skin. However the repigmentation process is very slow and is only observable after a few months of treatment. Currently, there is no objective method to assess the therapeutic response of skin pigment disorder treatment, particularly for vitiligo treatment. In this work, we apply principal component analysis followed by independent component analysis to represent digital skin images in terms of melanin and haemoglobin composition respectively. Vitiligo skin areas are identified as skin areas that lack melanin (non-melanin areas). Results obtained using the technique have been verified by dermatologists. Based on 20 patients, the proposed technique effectively monitored the progression of repigmentation over a shorter time period of six weeks and can thus be used to evaluate treatment efficacy objectively and more effectively.
The method of lines (MoL) has been developed to study coupling efficiency on hemispherical lens. In this paper, the physical shape of the lens is approximated by cascading a number of straight waveguide segments. The perfectly matched layer (PML) is applied as an absorber for the MoL to reduce numerical reflection in the simulation region. Analysis is done by calculating coupling efficiency at the plane of integration where the coupling efficiency is an overlap integral between laser diode field and fiber field. The result of coupling efficiency in this analysis is compared to the experiment and ABCD matrix. It is found that MoL gives good result accuracy.
We demonstrate an enhanced multiwavelength L-band Brillouin-erbium fiber laser (BEFL), in which the Brillouin pump is pre-amplified before entering the single-mode fiber. The Brillouin pump pre-amplification provided by the Erbium-doped fiber has created higher intensity of Brillouin Stokes line generated in the single-mode fiber that leads to the homogenous gain saturation. Thus the built-up of self-lasing cavity modes is suppressed in a wider wavelength range. In contrary to the conventional linear-cavity BEFL, the number of output channels is enhanced within the same tuning range.
In fetal heart monitoring using Doppler ultrasound signals the cardiac information is commonly extracted from non-directional signals. As a consequence often some of the cardiac events cannot be observed clearly which may lead to the incorrect detection of the valve and wall motions. Here, directional signals were simulated to investigate their enhancement of cardiac events, and hence provide clearer information regarding the cardiac activities. First, fetal Doppler ultrasound signals were simulated with signals encoding forward and reverse motion then obtained using a pilot frequency. The simulation results demonstrate that the model has the ability to produce realistic Doppler ultrasound signals and a pilot frequency can be used in the mixing process to produce directional signals that allow the simulated cardiac events to be distinguished clearly and correctly.
Previously, direct-proportional length-based DNA computing (DPLB-DNAC) for solving weighted graph problems has been reported. The proposed DPLB-DNAC has been successfully applied to solve the shortest path problem, which is an instance of weighted graph problems. The design and development of DPLB-DNAC is important in order to extend the capability of DNA computing for solving numerical optimization problem. According to DPLB-DNAC, after the initial pool generation, the initial solution is subjected to amplification by polymerase chain reaction and, finally, the output of the computation is visualized by gel electrophoresis. In this paper, however, we give more attention to the initial pool generation of DPLB-DNAC. For this purpose, two kinds of initial pool generation methods, which are generally used for solving weighted graph problems, are evaluated. Those methods are hybridization-ligation and parallel overlap assembly (POA). It is found that for DPLB-DNAC, POA is better than that of the hybridization-ligation method, in terms of population size, generation time, material usage, and efficiency, as supported by the results of actual experiments.
This paper presents two novel approaches to determine optimum growing multi-experts network (GMN) structure. The first method called direct method deals with expertise domain and levels in connection with local experts. The growing neural gas (GNG) algorithm is used to cluster the local experts. The concept of error distribution is used to apportion error among the local experts. After reaching the specified size of the network, redundant experts removal algorithm is invoked to prune the size of the network based on the ranking of the experts. However, GMN is not ergonomic due to too many network control parameters. Therefore, a self-regulating GMN (SGMN) algorithm is proposed. SGMN adopts self-adaptive learning rates for gradient-descent learning rules. In addition, SGMN adopts a more rigorous clustering method called fully self-organized simplified adaptive resonance theory in a modified form. Experimental results show SGMN obtains comparative or even better performance than GMN in four benchmark examples, with reduced sensitivity to learning parameters setting. Moreover, both GMN and SGMN outperform the other neural networks and statistical models. The efficacy of SGMN is further justified in three industrial applications and a control problem. It provides consistent results besides holding out a profound potential and promise for building a novel type of nonlinear model consisting of several local linear models.
The effects of curvature and tapering on the flow progression in the aorta were studied using numerical simulations on a realistic geometrical model of the aorta and three different versions of the ideal aorta models. The results showed that tapering increases velocity magnitude and wall shear stress while local curvatures affect the skewness of the velocity profile, the thickness of the boundary layer as well as the recirculation regions. Wall shear stress distribution in the aorta serves as an important determinant in the progression of arterial disease.
Interval-censored data consist of adjacent inspection times that surround an unknown failure time. We have in this paper reviewed the classical approach which is maximum likelihood in estimating the Weibull parameters with interval-censored data. We have also considered the Bayesian approach in estimating the Weibull parameters with interval-censored data under three loss functions. This study became necessary because of the limited discussion in the literature, if at all, with regard to estimating the Weibull parameters with interval-censored data using Bayesian. A simulation study is carried out to compare the performances of the methods. A real data application is also illustrated. It has been observed from the study that the Bayesian estimator is preferred to the classical maximum likelihood estimator for both the scale and shape parameters.
A lipase catalysed enantioselective hydrolysis process under in situ racemization of the remaining (R)-ibuprofen ester substrate with sodium hydroxide as the catalyst was developed for the production of S-ibuprofen from (R,S)-ibuprofen ester in isooctane. Detailed investigations on parameters study indicated that 0.5 M NaOH, addition of 20% (v/v) co-solvent (dimethyl sulphoxide), operating temperature of 45 degrees C, and 40 mmol/L substrate gave 86% conversion and 99.4% optical purity of S-ibuprofen in dynamic kinetic resolution. Meanwhile, in common enzymatic kinetic resolution process, only 42% conversion of the racemate and 93% enantiomeric excess of the product was obtained which are of lower values as compared to dynamic kinetic resolution. The S-ibuprofen produced during each process was evaluated and approximately 50% increment in concentration of S-acid product was produced when dynamic kinetic resolution was applied into the process.
Kinetics of production of biodiesel by enzymatic methanolysis of vegetable oils using lipase has been investigated. A mathematical model taking into account the mechanism of the methanolysis reaction starting from the vegetable oil as substrate, rather than the free fatty acids, has been developed. The kinetic parameters were estimated by fitting the experimental data of the enzymatic reaction of sunflower oil by two types of lipases, namely, Rhizomucor miehei lipase (RM) immobilized on ion-exchange resins and Thermomyces lanuginosa lipase (TL) immobilized on silica gel. There was a good agreement between the experimental results of the initial rate of reaction and those predicted by the proposed model equations, for both enzymes. From the proposed model equations, the regions where the effect of alcohol inhibition fades, at different substrate concentrations, were identified. The proposed model equation can be used to predict the rate of methanolysis of vegetable oils in a batch or a continuous reactor and to determine the optimal conditions for biodiesel production.
Identifying genes that are differentially expressed (DE) between two or more conditions with multiple patterns of expression is one of the primary objectives of gene expression data analysis. Several statistical approaches, including one-way analysis of variance (ANOVA), are used to identify DE genes. However, most of these methods provide misleading results for two or more conditions with multiple patterns of expression in the presence of outlying genes. In this paper, an attempt is made to develop a hybrid one-way ANOVA approach that unifies the robustness and efficiency of estimation using the minimum β-divergence method to overcome some problems that arise in the existing robust methods for both small- and large-sample cases with multiple patterns of expression.