Structure Preserving Algorithm for Fractional Order Mathematical Model of COVID-19

In this article, a brief biological structure and some basic properties of COVID-19 are described. A classical integer order model is modified and converted into a fractional order model with as order of the fractional derivative. Moreover, a valued structure preserving the numerical design, coined as Grunwald–Letnikov non-standard finite difference scheme, is developed for the fractional COVID-19 model. Taking into account the importance of the positivity and boundedness of the state variables, some productive results have been proved to ensure these essential features. Stability of the model at a corona free and a corona existing equilibrium points is investigated on the basis of Eigen values. The Routh–Hurwitz criterion is applied for the local stability analysis. An appropriate example with fitted and estimated set of parametric values is presented for the simulations. Graphical solutions are displayed for the chosen values of (fractional order of the derivatives). The role of quarantined policy is also determined gradually to highlight its significance and relevancy in controlling infectious diseases. In the end, outcomes of the study are presented.     

Evaluating the Efficiency of CBAM-Resnet Using Malaysian Sign Language

The deaf-mutes population is constantly feeling helpless when others do not understand them and vice versa. To fill this gap, this study implements a CNN-based neural network, Convolutional Based Attention Module (CBAM), to recognise Malaysian Sign Language (MSL) in videos recognition. This study has created 2071 videos for 19 dynamic signs. Two different experiments were conducted for dynamic signs, using CBAM-3DResNet implementing ‘Within Blocks’ and ‘Before Classifier’ methods. Various metrics such as the accuracy, loss, precision, recall, F1-score, confusion matrix, and training time were recorded to evaluate the models’ efficiency. Results showed that CBAM-ResNet models had good performances in videos recognition tasks, with recognition rates of over 90% with little variations. CBAM-ResNet ‘Before Classifier’ is more efficient than ‘Within Blocks’ models of CBAM-ResNet. All experiment results indicated the CBAM-ResNet ‘Before Classifier’ efficiency in recognising Malaysian Sign Language and its worth of future research.     

A New Hybrid SARFIMA-ANN Model for Tourism Forecasting

Many countries developed and increased greenery in their country sights to attract international tourists. This planning is now significantly contributing to their economy. The next task is to facilitate the tourists by sufficient arrangements and providing a green and clean environment; it is only possible if an upcoming number of tourists’ arrivals are accurately predicted. But accurate prediction is not easy as empirical evidence shows that the tourists’ arrival data often contains linear, nonlinear, and seasonal patterns. The traditional model, like the seasonal autoregressive fractional integrated moving average (SARFIMA), handles seasonal trends with seasonality. In contrast, the artificial neural network (ANN) model deals better with nonlinear time series. To get a better forecasting result, this study combines the merits of the SARFIMA and the ANN models and the purpose of the hybrid SARFIMA-ANN model. Then, we have used the proposed model to predict the tourists’ arrival in New Zealand, Australia, and London. Empirical results showed that the proposed hybrid model outperforms in predicting tourists’ arrival compared to the traditional SARFIMA and ANN models. Moreover, these results can be generalized to predict tourists’ arrival in any country or region with a complicated data pattern.     

Adaptive Fuzzy Logic Controller for Harmonics Mitigation Using Particle Swarm Optimization

An excessive use of non-linear devices in industry results in current harmonics that degrades the power quality with an unfavorable effect on power system performance. In this research, a novel control technique-based Hybrid-Active Power-Filter (HAPF) is implemented for reactive power compensation and harmonic current component for balanced load by improving the Power-Factor (PF) and Total–Hormonic Distortion (THD) and the performance of a system. This work proposed a soft-computing technique based on Particle Swarm-Optimization (PSO) and Adaptive Fuzzy technique to avoid the phase delays caused by conventional control methods. Moreover, the control algorithms are implemented for an instantaneous reactive and active current (I_d-I_q) and power theory (Pq0) in SIMULINK. To prevent the degradation effect of disturbances on the system's performance, PS0-PI is applied in the inner loop which generate a required dc link-voltage. Additionally, a comparative analysis of both techniques has been presented to evaluate and validate the performance under balanced load conditions. The presented result concludes that the Adaptive Fuzzy PI controller performs better due to the non-linearity and robustness of the system. Therefore, the gains taken from a tuning of the PSO based PI controller optimized with Fuzzy Logic Controller (FLC) are optimal that will detect reactive power and harmonics much faster and accurately. The proposed hybrid technique minimizes distortion by selecting appropriate switching pulses for VSI (Voltage Source Inverter), and thus the simulation has been taken in SIMULINK/MATLAB. The proposed technique gives better tracking performance and robustness for reactive power compensation and harmonics mitigation. As a result of the comparison, it can be concluded that the PSO-based Adaptive Fuzzy PI system produces accurate results with the lower THD and a power factor closer to unity than other techniques.     

Determination of lithium isotopic composition by thermal ionization mass spectrometry

A mass spectrometric method has been proposed for the determination of the isotopic composition of lithium. It is based upon thermal ionization of LiOH loaded onto a single SiO2-coated Re filament. By this method, stable emissions of Li+ ion have been achieved for an extended period of time. The proposed method is capable of analyzing trace quantities (approximately 40 ng) of Li in the presence of sodium with an uncertainty of +/-0.000 25 (two standard deviations of the mean).     

Mass spectrometric determination of 234U/238U ratio with improved precision

A new mass spectrometric method is proposed for measurement of 234U/238U ratio with a single Daly electron multiplier detector using the general peak jump method. The method is based on precise measurement of the 235U/238U ratio and 234U/235U ratio, which are used to calculate the 234U/238U ratio using the equation 234U/238U = 235U/238U x 234U/235U. The results show a significant improvement, i.e., more than 35 times better precision in measuring the (234)U/(238)U ratio with this method (sigma = 2.9 x 10(-8)) as compared to direct measurement of 234U/238U (sigma = 1.1 x 10(-6)). The method widens the applicability of the single collector system, and it will potentially be helpful to improve the precision in the case of the static multicollector system also.     

Indoor radon levels and lung cancer risk estimates in seven cities of the Bahawalpur Division, Pakistan

Indoor radon concentration levels were measured in seven major cities of the Bahawalpur Division, Pakistan. These included Fort Abbas, Minchin Abad, Hasilpur, Bahawalpur, Liaqatpur, Rahimyar Khan and Sadiq Abad. In order to select houses for this survey, the inhabitants were approached through their school-registered children. Due to several constraints, only those 100 houses were chosen in each city that were relatively the best representatives of the built-up area. The selected houses were then divided into live categories according to the house locations and building characteristics. CR-39 detectors, placed in polyethylene bags. were installed at head height in bedrooms and sitting rooms of all the selected houses and were exposed to radon and its daughter products for 90 days. Four such measurements were performed over a year in order to average out the seasonal variation in radon levels. After exposure, all the detectors were etched and counted under an optical microscope. The track densities of four measurements were averaged out and related to radon concentration levels. The radon levels were found to be 20, 20, 26, 28, 34, 42, 47 Bq m(-3) in the bedrooms and 24, 26, 27, 26, 37, 40, 43 Bq m(-3) in sitting rooms of Hasilpur, Rahimyar Khan, Minchin Abad, Fort Abbas, Sadiq Abad, Bahawalpur and Liaqatpur respectively. The observed variation in the radon level may be attributed to the geological variation in the area. Based on the observed data, excess lung cancer risk was assessed using the risk factors recommended by the USEPA, UNSCEAR and the ICRP. According to the EPA model, the lifetime excess lung cancer risk due to the lifetime exposure is found to vary from 12-102 per million per year in the houses surveyed. This variation is from 16-114 and 26-62 per million per year if UNSCEAR and ICRP limits are applied respectively.     

Influence of omega fatty acids on skin permeation of a coenzyme Q10 nanoemulsion cream formulation: characterization,in silico and ex vivo determination

Objective: The aim of this study was to develop a coenzyme Q10 nanoemulsion cream, characterize and to determine the influence of omega fatty acids on the delivery of coenzyme Q10 across model skin membrane via ex vivo and in silico techniques.

Methods: Coenzyme Q10 nanoemulsion creams were prepared using natural edible oils such as linseed, evening primrose, and olive oil. Their mechanical features and ability to deliver CoQ10 across rat skin were characterized. Computational docking analysis was performed for in silico evaluation of CoQ10 and omega fatty acid interactions.

Results: Linseed, evening primrose, and olive oils each produced nano-sized emulsion creams (343.93–409.86?nm) and exhibited excellent rheological features. The computerized docking studies showed favorable interactions between CoQ10 and omega fatty acids that could improve skin permeation. The three edible-oil nanoemulsion creams displayed higher ex vivo skin permeation and drug flux compared to the liquid-paraffin control cream. The linseed oil formulation displayed the highest skin permeation (3.97?±?0.91?mg/cm²) and drug flux (0.19?±?0.05?mg/cm²/h).

Conclusion: CoQ10 loaded-linseed oil nanoemulsion cream displayed the highest skin permeation. The highest permeation showed by linseed oil nanoemulsion cream may be due to the presence of omega-3, -6, and -9 fatty acids which might serve as permeation enhancers. This indicated that the edible oil nanoemulsion creams have potential as drug vehicles that enhance CoQ10 delivery across skin.     

Rapid and multimodal <Emphasis Type="Italic">in vivo</Emphasis> bioimaging of cancer cells through <Emphasis Type="Italic">in situ</Emphasis> biosynthesis of Zn&;Fe nanoclusters

Early diagnosis remains highly important for efficient cancer treatment,and hence,there is significant interest in the development of effective imaging strategies.This work reports a new multimodal bioimaging method for accurate and rapid diagnosis of cancer cells by introducing aqueous Fe2+ and Zn2+ ions into cancer cells (i.e.,HeLa,U87,and HepG2 cancer cells).We found that the biocompatible metal ions Fe2+ and Zn2+ forced the cancer cells to spontaneously synthesize fluorescent ZnO nanoclusters and magnetic Fe3O4 nanoclusters.These clusters could then be used for multimodal cancer imaging by combining fluorescence imaging with magnetic resonance imaging and computed tomography imaging.Meanwhile,for normal cells (i.e.,L02) and tissues,neither fluorescence nor any other obvious difference could be detected between preand post-injection.This multimodal bioimaging strategy based on the in situ biosynthesized Zn&Fe oxide nanoclusters might therefore be useful for early cancer diagnosis and therapy.