The antioxidant and antibacterial activities of ethanolic extract and phenolic compounds extract of Lemon balm (Melissa officinalis) and Oregano (Oreganum vulgare) plants were studied; the phenolic content and the relationship between these compounds and the above activities were also investigated. The results showed that the Lemon balm had the highest phenolic content (56.5% mg g) and the phenolic content of Oregano was twice lower than Lemon balm. Lemon balm has the highest antioxidant activity which causes lipid peroxidation inhibition activity of linoleic acid (90.5%), this activity was more than ?-tocopherole antioxidant activity (79.3 %). It was found that the main source of antioxidant ac

Functional yogurts enriched with plant-based bioactive compounds have emerged as promising dietary strategies to enhance human health. Objective: This study investigated the fortification of yogurt with Rhamnus alaternus fruit powder and its impact on quality characteristics, sensory attributes, and antioxidant activity. Methods: The current study involved preparing a powder from the fruit of the R. alternus plant, which underwent chemical and antioxidant analysis. Fresh buffalo milk was used to prepare yogurt, and products were fortified with the R. alternus powder. Results: R. alternus powder demonstrated significant improvements in taste, flavor, texture, color, and overall acceptability compared to the control. Conclusion: R. alternus p

A low-cost, effective green porous composite was prepared and used for the sorption of Zn+2 ions from aqueous solutions. The effect of contact time, sorbent dosage, initial ion concentration, solution pH, and temperature on the sorption of Zn+2 ions was investigated. The results showed higher removal efficiency of Zn+2 ions (83%), which was achieved at a contact time of 120 minutes, a normal pH of 6.4, and a temperature of 313 K. The Langmuir isotherm model successfully described the experimental results of the sorption process with a theoretical maximum sorption capacity of 4.819 mg/g. The kinetics of sorption showed that the pseudo-second-order model fitted the experimental results better than the pseudo-first-order model. The int

This research investigates the pre- and post-cracking resistance of steel fiber-reinforced concrete specimens with Glass Fiber Reinforced Polymer (GFRP) bars subjected to flexural loading. The purpose is to modify the ductility and cracking resistance of GFRP-reinforced beams, which are prone to early cracking and excessive deflections instigated by the low modulus of elasticity of GFRP. Six self-compacting concrete specimens (1500×240×200 mm), incorporating steel fibers of two lengths (25 mm and 40 mm) with varying distribution depths, were tested to assess their structural performance. The results indicate significant enhancements in cracking resistance, stiffness, energy absorption, ductility, and flexural strength. Tested beam

This research investigates the pre- and post-cracking resistance of steel fiber-reinforced concrete specimens with Glass Fiber Reinforced Polymer (GFRP) bars subjected to flexural loading. The purpose is to modify the ductility and cracking resistance of GFRP-reinforced beams, which are prone to early cracking and excessive deflections instigated by the low modulus of elasticity of GFRP. Six self-compacting concrete specimens (1500×240×200 mm), incorporating steel fibers of two lengths (25 mm and 40 mm) with varying distribution depths, were tested to assess their structural performance. The results indicate significant enhancements in cracking resistance, stiffness, energy absorption, ductility, and flexural strength. Tested beam

The paper presents a novel method of reinforcing concrete columns using small-diameter steel tubes instead of traditional steel bars. The researchers conducted experimental investigations on twelve mid-scale circular concrete column specimens, which were divided into two groups consisting of six specimens each: short and long columns. Two of the specimens in each group were reinforced with steel bars, while the remaining four were reinforced with steel tubes filled with cementitious grouting material. The study proposed two concepts for cementitious grouted steel-tube reinforcement. The first concept utilized steel tubes with equivalent net areas to the steel bar areas used in the reference column, while the second concept used stee

Dandruff and seborrheic dermatitis (SD) are common skin disorders affecting the scalp and extending to other body sites in the case of SD. They are associated with pruritus and scaling, causing an esthetical disturbance in the population affected.   Treatment of such conditions involves using a variety of drugs for long terms, thus optimizing drug formulation is essential to improve therapeutic efficacy and patient compliance. Conventional topical formulations like shampoos and creams have been widely used but their use is associated with disadvantages. To overcome such effects, novel topical nanotechnology-based formulations are currently under investigation. In the following article, we highlight recently published formulatio

In this work,  an explicit formula for a class of Bi-Bazilevic univalent functions involving differential operator is given, as well as the determination of upper bounds for the general Taylor-Maclaurin coefficient of a functions belong to this class, are established Faber polynomials are used as a coordinated system to study the geometry of the manifold of coefficients for these functions. Also determining bounds for the first two coefficients of such functions.

         In certain cases, our initial estimates improve some of the coefficient bounds and link them to earlier thoughtful results that are published earlier.

Citrus diseases are the main issue for agricultural productivity, which cause a reduction in yield and quality, thus causing economic loss; also, we see that traditional methods of diagnosis, which are very subjective and prone to error, and thus we need to suggest accurate automated detection systems. In this study, we present a hybrid model that integrates conventional machine learning with deep learning models. We used the Gray Level Co-occurrence Matrix (GLCM) for feature extraction, which is classified via machine learning algorithms like k-Nearest Neighbors (KNN), Decision Tree (DT), Linear Discriminant Analysis (LDA), and Random Forest (RF). At the same time, deep convolutional neural networks (DCNNs), GoogLeNet, and ResNet18