(R1989) Mixed Convection Slippery Cross Fluid Flow due to a Stratified Sheet under the Effect of Radiation Phenomenon

In view of the meaning of a two dimensional laminar Cross liquid in depicting an exhaustive assortment of experimental information, an assessment is done for a numerical and mathematical arrangement over a stratified extensible sheet. The non-dimensionality technique is brought into the controlling equations within the sight of the slip phenomenon and to make the solution more thorough. The data have been taken at a steady, viscous and laminar ow. Heat transfer across fluid is employed as a non-Newtonian fluid, where the fluid has a affected by radiation. Additionally, thermal radiation and heat generation are considered with the basic influence on the temperature field. The work has been performed to yield a completely new concept of the presence relationship between the governing parameters and the rate of heat transfer. Numerical analysis with the aid of the shooting method of the governing equations of motion is given over a wide range of controlling parameters. A bunch of graph plots both velocity and temperature fields at various upsides of physical parameters. Furthermore, a tabular form of the same parameters exists for the local shear stress and the rate of heat transfer along the sheet

Flavonoid-coated gold nanoparticles as efficient antibiotics against gram-negative bacteria—evidence from in silico-supported in vitro studies

Flavonoids are a class of bioactive plant-derived natural products that exhibit a broad range of biological activities, including antibacterial ones. Their inhibitory activity toward Gram-positive bacterial was found to be superior to that against Gram-negative ones. In the present study, a number of flavonoid-coated gold nanoparticles (GNPs) were designed to enhance the antibacterial effects of chrysin, kaempferol, and quercetin against a number of Gram-negative bacteria. The prepared GNPs were able to conjugate to these three flavonoids with conjugation efficiency ranging from 41% to 80%. Additionally, they were able to exert an enhanced antibacterial activity in comparison with the free flavonoids and the unconjugated GNPs. Quercetin-coated GNPs were the most active nano-conjugates and were able to penetrate the cell wall of E. coli. A number of in silico experiments were carried out to explain the conjugation efficiency and the antibacterial mechanisms of these flavonoids as follows: (i) these flavonoids can efficiently bind to the glutathione linker on the surface of GNPs via H-bonding; (ii) these flavonoids, particularly quercetin, were able to increase the bacterial membrane rigidity, and hence decrease its functionality; (iii) these flavonoids can inhibit E. coli’s DNA gyrase (Gyr-B) with IC(50) values ranging from 0.9 to 3.9 µM. In conclusion, these bioactive flavonoid-based GNPs are considered to be very promising antibiotic candidates for further development and evaluation

An unusual presentation of hemoglobin SD Punjab in a Saudi Arabian adult

HbDPunjab is an uncommon variant hemoglobin that does not result in significant pathology when inherited as a homozygous disorder. When inherited with other hemoglobinopathies, it may result in varying disease phenotypes. HbSDPunjab has been rarely reported in Saudi Arabia, coexisting with alpha or beta thalassemia. In this report, we discuss the case of a 39 years old male who presented with severe anemia and renal injury and was later diagnosed with HbSDPunjab through electropheresis and genetic testing

Accuracy improvement of power transformer faults diagnostic using KNN classifier with decision tree principle

Dissolved gas analysis (DGA) is the standard technique to diagnose the fault types of oil-immersed power transformers. Various traditional DGA methods have been employed to detect the transformer faults, but their accuracies were mostly poor. In this light, the current work aims to improve the diagnostic accuracy of power transformer faults using artificial intelligence. A KNN algorithm is combined with the decision tree principle as an improved DGA diagnostic tool. A total of 501 dataset samples are used to train and test the proposed model. Based on the number of correct detections, the neighbor’s number and distance type of the KNN algorithm are optimized in order to improve the classifier’s accuracy rate. For each fault, indeed, several input vectors are assessed to select the most appropriate one for the classifier’s corresponding layer, increasing the overall diagnostic accuracy. On the basis of the accuracy rate obtained by knots and type of defect, two models are proposed where their results are compared and discussed. It is found that the global accuracy rate exceeds 93% for the power transformer diagnosis, demonstrating the effectiveness of the proposed technique. An independent database is employed as a complimentary validation phase of the proposed research

Enhancement the removal capacity of heavy metals from aqueous solution using different aquatic organisms

151-162The Eichhornia sp had high ability for bioremoval of Pb and Cd (97.15 and 97.48%) during 15 min with some ultrastructure changes of the leaf such as, ruptured or disappeared plasma membrane, swollen mitochondria and malformation chloroplast and some anatomical studies; thickness of upper epidermis and mesophyll decreased with presences number of raphide crystals in treated leaf but it not found in untreated plants. It was noticed that treated with Pb was more effect on histological leaf than treated with Cd. While, Gelidium pectinatum had highest efficiency for removal of Cd but during 0.5 hr. The bioremoval efficiency of lead by Gelidium pectinatum increased with Epichlorohydrin 1 from 28.84 to 90.18 % during 240 min contact time and from 77.34 in raw (untreated) algae to 99.58% in case of cadmium during the same contact time

An energy efficient modified passive power filter for power quality enhancement in electric drives

In most industrial applications, AC drives are used. These drives require power electronic modules to convert AC to DC and also DC to AC. The power modules used for power conversion consist of power semiconductor switches. There is distortion in the voltage and current obtained from the power modules due to non-linear behaviors of semiconductor switches. To reduce the distortion in the input current, inductors are used along with the line impedance. A high value of inductance is required to maintain the percentage of THD within limits set by the latest standards. Along with the increased size and cost, it also reduces the power factor and output DC voltage at higher loads. The use of a passive power filter (PPF) is the conventional method followed for the reduction of percentage THD and promotion of the power factor. PPFs comprise passive elements such as the resistor, inductor, and capacitor. These passive elements are connected at the point of common coupling (PCC) in shunt to compensate for the harmonics present in the input current. In this study, a modified multi-tuned passive filter is considered to reduce the source current harmonics. A bridge rectifier with resistive load, three-phase induction motor drive, and linear resistive–inductive load is connected at the point of common coupling to analyze the harmonics present in the source current, and also unbalanced created in one phase. To achieve proper selection of the resistance value for the passive filter, the class topper optimization technique is used. To validate the simulation results obtained for the multi-tuned passive filter, the hardware is implemented with a three-phase AC induction motor drive load, in which the speed of the motor is controlled with voltage by a frequency control algorithm using an FPGA controller; The 50% THD is reduced by using the fifth-order filter alone, 75% by combining the fifth- and seventh-order filters, 85% by combining the 5th-, 7th-, 11th-, 13th-, and higher-order filters, and 90% for varying loads. For single-phase AC induction motor load, THD % is reduced to 4%, and for three-phase AC induction motor drive, THD % is reduced to 10% with the same value of the filter

Lipid nanocarriers overlaid with chitosan for brain delivery of berberine via the nasal route

This research aimed to design, optimize, and evaluate berberine-laden nanostructured lipid carriers overlaid with chitosan (BER-CTS-NLCs) for efficient brain delivery via the intranasal route. The nanostructured lipid carriers containing berberine (BER-NLCs) were formulated via hot homogenization and ultrasonication strategy and optimized for the influence of a variety of causal variables, including the amount of glycerol monostearate (solid lipid), poloxamer 407 (surfactant) concentration, and oleic acid (liquid lipid) amount, on size of the particles, entrapment, and the total drug release after 24 h. The optimal BER-NLCs formulation was then coated with chitosan. Their diameter, in vitro release, surface charge, morphology, ex vivo permeability, pH, histological, and in vivo (pharmacokinetics and brain uptake) parameters were estimated. BER-CTS-NLCs had a size of 180.9 ± 4.3 nm, sustained-release properties, positive surface charge of 36.8 mV, and augmented ex-vivo permeation via nasal mucosa. The histopathological assessment revealed that the BER-CTS-NLCs system is safe for nasal delivery. Pharmacokinetic and brain accumulation experiments showed that animals treated intranasally with BER-CTS-NLCs had substantially greater drug levels in the brain. The ratios of BER brain/blood levels at 30 min, AUCbrain/AUCblood, drug transport percentage, and drug targeting efficiency for BER-CTS-NLCs (IN) were higher compared to BER solution (IN), suggesting enhanced brain targeting. The optimized nanoparticulate system is speculated to be a successful approach for boosting the effect of BER in treating CNS diseases, such as Alzheimer’s disease, through intranasal therapy

Exogenously applied ZnO nanoparticles induced salt tolerance in potentially high yielding modern wheat (Triticum aestivum L.) cultivars

Salinity stress is one of the potential threats that adversely affect the productivity of many cereal crops worldwide. Spraying plants with nano-Zn particles may lessen effectively such negative impacts on plants; yet its mode of action is still not well explored. This study was performed to evaluate the effects of spraying nano-Zn particles with varying concentrations (0, 20, 50 and 80 mg L-1) on two wheat cultivars irrigated with saline water (EC = 6.3 dS m-1) versus a non-saline one. The key results revealed that root and shoot weights decreased significantly under salinity stress conditions, while improved considerably with nano-Zn-particles foliar application up to 50 mg nanoZn L-1; thereafter significant reductions occurred. Also, shoot and root lengths as well as plant leaf area index improved considerably owing to this foliar application. Clearly, roots and shoots weights of wheat plants sprayed with nano-Zn particles under salinity stress conditions exhibited higher values than the corresponding ones that was grown under non-saline conditions without nano-Zn-particles applications. Unexpectedly, this foliar spray led to significant reductions in plant pigments and also in enzymatic and non-enzymatic antioxidants in plants. Yet, this foliar spray enhanced formation of total soluble sugars and proline, and raised significantly Ca contents in wheat roots and shoots, and to some extent K contents. In conclusion, the foliar application of nano-Zn particles increased plant growth under salty stress conditions via two parallel processes, i.e., stimulating formation of osmolytes and stimulating nutrient uptake which may, in turn, increase plant metabolism. (c) 2022 The Author(s). Published by Elsevier B.V. This is an open access article under the CCPeer reviewe