ELECTROCHEMICAL AND CHEMOMETRIC DETERMINATION OF DORZOLAMIDE AND TIMOLOL IN EYE DROPS USING MODIFIED MULTIWALL CARBON NANOTUBE ELECTRODE

Objective: This work is focused on the construction of simple and sensitive electrochemical sensor for quantitative determination of dorzolamide (DOR) and timolol maleate (TIM). This method is based on the incorporation of multiwall carbon nanotubes (MWCNT) into the carbon paste electrode which improve the characteristics of the electrode.Methods: The electrochemical response of modified electrode was based on voltammetric oxidation, using cyclic voltammetry (CV) and impedance spectroscopy (EIS). The structural morphology of the surface modified electrode was characterized by scanning electron microscope (SEM). Quantitative analysis for each of the two compounds in a mixture has been examined by using of chemometric tools for resolving overlapping signals. The prediction performance of the chemometric method was analyzed by principal component regression (PCR) and partial least square (PLS).Results: Fractional factorial design was constructed from set of synthetic mixtures of two drugs in concentration ranges of 0.05 to 1.6µg/ml for DOR and 1.5-20 µg/ml for TIM. Under optimum experimental conditions, DOR and TIM gave rectilinear response over the concentration range of 0.072-1.88 µg/ml and 1.16-20.84 µg/ml, respectively. The limit of detection (LOD) was found to be 0.098 and 1.025 µg/ml, for DOR and TIM, respectively. It found that the % of relative prediction error (RPE) was acceptable and satisfactory.Conclusion: In these work, for the first time, a new voltammetric simultaneous method developed for a rapid and efficient determination of DOR and TIM from eye dropper sample at nano modified electrode with satisfactory results. These results indicate that MWCNT holds great promise in practical application

Validated analytical modelling of supercharging centrifugal compressors with vaneless diffusers for H2-biodiesel dual-fuel engines with cooled EGR

The supercharging centrifugal compressor with a vaneless diffuser is a key element in diesel powertrains that has not been comprehensively modelled using explainable mathematical trends. This study thus develops an analytical model for this type of compressors for hybrid H2-Biodiesel dual-fuel engines with cooled EGR. Specifically, for this proposed type of compression ignition system, the study develops an analytical model of the velocities at the exit of impeller of the supercharging compressor. In addition, a sensitivity analysis is conducted on the developed models of the total power required to drive the compressor and its mechanical efficiency. The developed models have been validated using case studies that are based on field data gathered experimentally. Furthermore, a modified model of the Stanitz's slip factor is presented for radial blades accounting for the Coriolis circulation, boundary layer effect, and blade thickness. The modified Stanitz's slip factor provides better accuracy of matching the experimental results with relative error of 1%. The relative error with respect to the parameters of the velocities at the impeller and the analytical model of the power required to drive the rotor of the compressor is 7%. In addition, the relative error with respect to the model of the mechanical efficiency of the compressor is 10%. These relative errors are of an order of magnitude of deviation that is comparable with that of widely recognized models in the field of vehicle powertrain modelling such as the CMEM and GT-Power. These developed models follow from the principles of physics so that they are widely valid models. Having addressed and corrected flaws in corresponding models presented in key references in this research area, these developed models can help more effectively evaluate the power input to this type of compressors and thus the fuel consumption reducing the environmental foot-print thereof

IMPACTS OF CYANOBACTERIA AND BRADYRHIZOBIUM INOCULATION ON LUPINE PLANTS UNDER DIFFERENT NITROGEN RATES IN SANDY SOIL

A field experiment was conducted in sandy soil at Ismailia Agricultural Research Station, (Ismailia Governorate, Egypt, in two successive winter seasons of 2015/2016 and 2016/2017. The experiment aimed to study the response of lupine plants (Lupinus albus L.) variety Giza 2 to cyanobacteria applied with different methods under different nitrogen fertilizer rates and inoculated with rhizobia. Results revealed that application of cyanobacteria generally increased the mean values of nodules number, dry weight of nodules and shoot dry weight of lupine plants, nitrogen uptake, biological activity of the soil rhizosphere lupine plants, yield, yield components and seed protein content as compared to those recorded by the control treatment without cyanobacteria. Increasing nitrogen rates decreased the mean values of both nodules number and dry weight of nodules. On the contrary, increasing nitrogen rate up to 100% of the recommended one increased all the other tested parameters. The highest values of these parameters were recorded when cyanobacteria were applied as dry + soaking combined with 75 % N rate expect for those of number and nodules the dry weight of nodules that gave their highest values when the lupine plants received the treatment of dry + soaking combined with 50 % N rate. In conclusion, the use of cyanobacteria along with rhizobia as renewable nitrogen source for lupine production can save 25% N from that required for lupine

Impact of intelligent transportation systems on vehicle fuel consumption and emission modeling: an overview

Climate change due to greenhouse gas emissions has led to new vehicle emissions standards which in turn have led to a call for vehicle technologies to meet these standards. Modeling of vehicle fuel consumption and emissions emerged as an effective tool to help in developing and assessing such technologies, to help in predicting aggregate vehicle fuel consumption and emissions, and to complement traffic simulation models. The paper identifies the current state of the art on vehicle fuel consumption and emissions modeling and its utilization to test the environmental impact of the Intelligent Transportation Systems (ITS)' measures and to evaluate transportation network improvements. The study presents the relevant models to ITS in the key classifications of models in this research area. It demonstrates that the trends of vehicle fuel consumption and emissions provided by current models generally do satisfactorily replicate field data trends. It shows as well that microscopic modeling is the most accurate type of vehicle fuel consumption and emissions modeling and macroscopic modeling is most helpful in estimating aggregate emissions inventories. In addition, the paper demonstrates that mesoscopic models and empirical models strike a balance between accuracy and simplicity so that they are highly suitable for evaluating the environmental impact of the ITS' measures and transportation network improvements. The study indicates that there is a significant impact of ITS measures on vehicle fuel consumption and emissions rates. It identifies as well the relation among transportation models, cold start excess emission modeling subcategories, and hot-stabilized emission models. The study concludes that no one model as yet fully meets the needs of ITS applications

Supercharged diesel powertrain intake manifold analytical model

Diesel powertrains are some of the most well-established yet promising technologies for their many advantageous features. Although vehicle analytical models accurately describe the physical phenomena associated with vehicle operation following from the principles of physics and with explainable mathematical trends, no analytical microscopic model has been developed as yet of diesel powertrains. The present research paper presents an analytical model of the intake manifold of a supercharged diesel powertrain, equipped with an electronic throttle control (ETC). The present study analytically modelled the intake manifold dynamic pressure, the mass flow rate of air entering the cylinders, the mass flow rate at the throat of the intake manifold, the intake manifold dynamic pressure under both transient choked and nonchoked conditions as well as under steady state condition, and the intake manifold gas speed dynamics. A case study has been conducted in order to experimentally validate the analytical model of the air acceleration in intake manifold with a deviation of 12.7%. The developed models serve to analyse the performance of the supercharged diesel intake manifold with respect to both the transient response and the steady state response. The present analytical models can help as well in developing and assessing diesel powertrain intake manifold technologies

Experimentally validated analytical modeling of diesel exhaust HC emission rate

Supercharged diesel engines are a key source of hazardous regulated emissions that have been extensively modelled, yet without explainable mathematical trends. The present paper demonstrates the analytical modeling of the percentage of unburned Hydrocarbon and the HC emission rate in four-stroke diesel engines for trucks. The study presents as well the analytical modeling of the supercharged air density. A sensitivity analysis has been conducted on these developed models. The study shows that the average percentage of deviation of the simulated results from the corresponding freeway cycles field data on the percentage of unburned Hydrocarbon and the HC emission rate is 10.6% and 4%, respectively. The corresponding coefficient of determination is 70% and 83%, respectively. The relative error of the developed models of the percentage of unburned Hydrocarbon and the HC emission rate is 10.6% and 2%, respectively. The study demonstrates with 99% coefficient of determination that the average percentage of deviation of the simulated results from the corresponding field data under the steady speed operating condition for all freeway cycles on the supercharged air density is 3.7%. The relative error of the developed model of the supercharged air density is 4%. These values of relative error are in an order of magnitude of deviation that is less than that of widely recognized models in the field of vehicle powertrain modeling, such as the CMEM. These developed analytical models serve as widely valid models that follow entirely from the principles of physics and the results of these developed models have explainable mathematical trends. The fact that these developed models are dimensionally correct further supports the validity of these models. The present models can help in better analyzing the performance of diesel engines and in developing and assessing the performance of these engines. © 2014, The Korean Society of Mechanical Engineers and Springer-Verlag Berlin Heidelberg