Studies were conducted to screen eight sunflower (Helianthus annuus L.) genotypes for their allelopathic potential against weeds and wheat crop, which customarily follows sunflower in Iraq. All sunflower genotypes significantly inhibited the total number and biomass of companion weeds and the magnitude of inhibition was genotype dependent. Among the eight genotypes tested, Sin-Altheeb and Coupon were the most weed-suppressing cultivars, and Euroflor and Shumoos were the least. A subsequent field experiment indicated that sunflower residues incorporated into the field soil significantly inhibited the total number and biomass of weeds growing in the wheat field. Sunflower genotypes Sin-Altheeb and Coupon appeared to inhibit total weed number and biomass more and significantly increased wheat yield compared with the least-suppressive genotypes (Euroflor and Shumoos). Chromatographic analyses by HPLC revealed the presence of 13 secondary metabolites in residues of the tested sunflower genotypes. All the isolated compounds appeared to be phenolic, with the exception of terpinol, which is a terpenoid derivative. The total concentration of Phytotoxins (phenolic compounds) was found to be higher in the most-suppressive potential genotypes compared with the least-suppressive genotypes.
Polycystic ovary syndrome (PCOS) is a common endocrine disorder affecting women of reproductive age, characterized by anovulatory, infertility and metabolic disturbances. This study aimed to assess the diagnostic accuracy of Leucine-rich alpha-2-glycoprotein-1 (LRG1) and xanthine oxidase (XO) activity as novel biomarkers for PCOS, as well as to explore the relationship between LRG1 and XO activity across different groups. A total of 150 married women, aged 18-46 years were enrolled and divided into three groups: 50 with PCOS under treatment, 50 PCOS without treatment conditions shared by women with polycystic ovary conditions, and 50 healthy women. Serum samples were analysed to measure LRG1, xanthine oxidase (XO) activity,
... Show MoreCurcumin (Cur) possesses remarkable pharmacological properties, including cardioprotective, neuroprotective, antimicrobial, and anticancer activities. However, the utilization of Cur in pharmaceuticals faces constraints owing to its inadequate water solubility and limited bioavailability. To overcome these hurdles, there has been notable focus on exploring innovative formulations, with nanobiotechnology emerging as a promising avenue to enhance the therapeutic effectiveness of these complex compounds. We report a novel safe, effective method for improving the incorporation of anticancer curcumin to induce apoptosis by reducing the expression levels of miR20a and miR21. The established
A series of Schiff base-bearing salicylaldehyde moiety compounds (1-4) had been designed, synthesized, subjected to insilico ADMET prediction, molecular docking, characterization by FT-IR, and CHNS analysis techniques, and finally to their Anti-inflammatory profile using cyclooxygenase fluorescence inhibitor screening assay methods along with standard drugs, celecoxib, and diclofenac. The ADMET studies were used to predict which compounds would be suitable for oral administration, as well as absorption sites, bioavailability, TPSA, and drug likeness. According to the results of ADME data, all of the produced chemicals can be absorbed through the GIT and have passed Lipinski’s rule of five. Through molecular docking with PyRx 0.8, these
... Show More3D‐printed scaffolds loaded with healing directed agents could be employed for better treatment outcome in regenerative dentistry. The aim of this study was to fabricate and characterize simple 3D‐printed poly lactic acid (PLA) scaffolds coated with nanoHydroxyapatite (nHA), Naringin (NAR), or their combination, and testing their morphological, chemical, mechanical, antibacterial, biocompatible and bioactive properties. Methodology: Two variants pore sizes, 300 and 700 μm, of 3D‐printed PLA disc scaffolds measuring (10 × 1 mm) were fabricated. These scaffolds were dip‐coated with nHA, NAR, or both (nHA/NAR). Field emission scanning electron microscopy (FeSEM), energy‐dispersive X‐ray spectroscopy (EDX), Fourier transfo
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In this work, a novel technique to obtain an accurate solutions to nonlinear form by multi-step combination with Laplace-variational approach (MSLVIM) is introduced. Compared with the traditional approach for variational it overcome all difficulties and enable to provide us more an accurate solutions with extended of the convergence region as well as covering to larger intervals which providing us a continuous representation of approximate analytic solution and it give more better information of the solution over the whole time interval. This technique is more easier for obtaining the general Lagrange multiplier with reduces the time and calculations. It converges rapidly to exact formula with simply computable terms wit
... Show MoreGundelia, a genus of flowering plants native to the Mediterranean region, particularly in Iraq, holds promise as a sustainable adsorbent for the treatment of dye-polluted water. This study explores the potential of Gundelia seeds (GS) waste as a biobased adsorbent for removing methylene blue dye from synthesized wastewater. Utilizing various analytical techniques, including scanning electron microscopy (SEM), Fourier transform infrared (FTIR) spectroscopy, and X-ray diffraction analysis (XRD), we assessed GS as an active adsorbent with performance comparable to fabricated and expensive composites. Key parameters such as pH (3-11), pH at the point of zero charge, temperature (298-328 K), dose (0.02-0.1 g), dye concentration (10-50 ppm), and
... Show MoreAccurate prediction of river water quality parameters is essential for environmental protection and sustainable agricultural resource management. This study presents a novel framework for estimating potential salinity in river water in arid and semi‐arid regions by integrating a kernel extreme learning machine (KELM) with a boosted salp swarm algorithm based on differential evolution (KELM‐BSSADE). A dataset of 336 samples, including bicarbonate, calcium, pH, total dissolved solids and sodium adsorption ratio, was collected from the Idenak station in Iran and was used for the modelling. Results demonstrated that KELM‐BSSADE outperformed models such as deep random vector funct
This paper presents a comparative study of two learning algorithms for the nonlinear PID neural trajectory tracking controller for mobile robot in order to follow a pre-defined path. As simple and fast tuning technique, genetic and particle swarm optimization algorithms are used to tune the nonlinear PID neural controller's parameters to find the best velocities control actions of the right wheel and left wheel for the real mobile robot. Polywog wavelet activation function is used in the structure of the nonlinear PID neural controller. Simulation results (Matlab) and experimental work (LabVIEW) show that the proposed nonlinear PID controller with PSO
learning algorithm is more effective and robust than genetic learning algorithm; thi
The aim of this article is to solve the Volterra-Fredholm integro-differential equations of fractional order numerically by using the shifted Jacobi polynomial collocation method. The Jacobi polynomial and collocation method properties are presented. This technique is used to convert the problem into the solution of linear algebraic equations. The fractional derivatives are considered in the Caputo sense. Numerical examples are given to show the accuracy and reliability of the proposed technique.