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.     

Biosynthesized Gold Nanoclusters and Iron Complexes as Scaffolds for Multimodal Cancer Bioimaging

Cancer treatment has a far greater chance of success if the neoplasm is diagnosed before the onset of metastasis to vital organs. Hence, cancer early diagnosis is extremely important and remains a major challenge in modern therapeutics. In this contribution, facile and new method for rapid multimodal tumor bioimaging is reported by using biosynthesized iron complexes and gold nanoclusters via simple introduction of AuCl₄ ^? and Fe²⁺ ions. The observations demonstrate that the biosynthesized Au nanoclusters may act as fluorescent and computed tomography probes for cancer bioimaging while the iron complexes behave as effective contrast agent for magnetic resonance imaging. The biosynthesized iron complexes and gold nanoclusters are found biocompatible in vitro (MTT (3‐(4, 5‐dimethylthiazol‐2‐yl)‐2, 5‐diphenyltetrazolium bromide) assay) and in vivo for all the vital organs of circulatory and excretory system. These observations raise the possibility that the biosynthesized probes may find applications in future clinical diagnosis for deep seated early neoplasms by multimodal imaging.     

Enhancement in Physical Properties of Silver-Doped Fe–Ni Invar Nano-alloy Using Chemical Reduction Method

Journal of Superconductivity and Novel Magnetism - Silver-substituted Fe–Ni nano invar alloy is a new and innovative field of research due to their interesting invar, magnetic and electrical...     

Bioactive-Tissue-Derived Nanocomposite Hydrogel for Permanent Arterial Embolization and Enhanced Vascular Healing

Transcatheter embolization is a minimally invasive procedure that uses embolic agents to intentionally block diseased or injured blood vessels for therapeutic purposes. Embolic agents in clinical practice are limited by recanalization, risk of non-target embolization, failure in coagulopathic patients, high cost, and toxicity. Here, a decellularized cardiac extracellular matrix (ECM)-based nanocomposite hydrogel is developed to provide superior mechanical stability, catheter injectability, retrievability, antibacterial properties, and biological activity to prevent recanalization. The embolic efficacy of the shear-thinning ECM-based hydrogel is shown in a porcine survival model of embolization in the iliac artery and the renal artery. The ECM-based hydrogel promotes arterial vessel wall remodeling and a fibroinflammatory response while undergoing significant biodegradation such that only 25% of the embolic material remains at 14 days. With its unprecedented proregenerative, antibacterial properties coupled with favorable mechanical properties, and its superior performance in anticoagulated blood, the ECM-based hydrogel has the potential to be a next-generation biofunctional embolic agent that can successfully treat a wide range of vascular diseases.     

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.     

Postponement growth and antioxidative response of Brassica nigra on CuO and ZnO nanoparticles exposure under soil conditions

Due to unique physiochemical properties, nanoparticles (NPs) have acquired substantial attention in the field of research. However, threats of ecotoxicity and phytotoxicity have limited their biological applications. In this study in vivo experiments were performed to determine the effect of CuO (12.5, 25 and 50 mg/kg) and ZnO (200, 400 and 600 mg/kg) NPs on growth, and antioxidant activities of Brassica nigra. The results showed that CuO NPs did not affect the seed germination while presence of ZnO NPs in the soil generated an inhibitory effect. Both CuO and ZnO NPs positively influenced the growth of stem and other physiological parameters i.e. stem height increased (23%) at 50 mg/kg CuO while root length decreased (up to 44%) with an increase in the concentration of NPs. Phytochemical screening of apical, middle and basal leaves showed elevated phenolic and flavonoid contents in the range of 15.3–59 μg Gallic Acid Equivalent (GAE)/mg Dry Weight (DW) and 10–35 μg Querceitin Equivalent (QE)/mg DW, respectively, in NPs‐treated plants. Antioxidant activity was higher in CuO NPs‐treated plants as compared to ZnO and control plants. Results conclude that CuO and ZnO NPs at low concentrations can be exploited as nanofertilisers in agriculture fields.Inspec keywords: biochemistry, enzymes, renewable materials, crops, nanoparticles, soil, nanofabrication, zinc compounds, organic compounds, agricultural products, toxicology, nanobiotechnologyOther keywords: antioxidative response, ZnO nanoparticles exposure, soil conditions, unique physiochemical properties, germination, antioxidant activities, brassica nigra plant, antioxidant activity, CuO NP‐treated plants, control plants, ZnO NPs effect, mass 15.3 mug to 59.0 mug, mass 10.0 mug to 35.0 mug, CuO, ZnO     

Textile composite double dome stamping simulation using a non-orthogonal constitutive model

Stamping is one of the most effective ways to form textile composites in industry for providing high-strength, low-weight and cost-effective products. This paper presents a fully continuum mechanics-based approach for stamping simulation of textile fiber reinforced composites by using finite element (FE) method. A previously developed non-orthogonal constitutive model is used to represent the anisotropic mechanical behavior of textile composites under large deformation during stamping. Simulation are performed on a balanced plain weave composite with 0°/90° and ±45° as initial yarn orientation over a benchmark double dome device. Simulation results show good agreement with experimental output in terms of a number of parameters selected for comparison. The effects of meshing and shear moduli obtained from bias extension test and picture frame test on forming simulation results are also investigated.     

Measurement and Analysis of Thermophysical Properties of Diorites in the Temperature Range from 253 to 333 K

Thermal conductivity and thermal diffusivity are simultaneously measured for a collection of diorite samples taken from Shewa-Shahbaz Garhi volcanic complex near Mardan, Pakistan by using the transient plane source (TPS) technique. The temperature dependence of the transport properties of these samples is studied in the temperature range from 253 to 333 K. Different relationships for the temperature dependence of the thermal conductivity and thermal diffusivity are tested. The samples are also characterized by their chemical composition, density, porosity, and specific gravity at room temperature and atmospheric pressure. Theoretical calculation of the specific gravity parameter based on the chemical composition is in good agreement with the experimental observation. No correlation was found for the temperature dependence of the thermal transport behavior on porosity, chemical composition, and density.