In this study, the volatile compounds found in lemon trees infested and uninfested with Planococcus citri (Risso) (Hemiptera: Pseudococcidae) were investigated. In addition, the interest of the predator Cryptolaemus montrouzieri (Coleoptera: Coccinellidae) and the parasitoid Leptomastix dactylopii (Hymenoptera: Encyrtidae) in lemon trees infested and uninfested with P. citri and some volatile compounds was investigated. According to the results obtained, most of the volatile compounds obtained from mealybug-infested lemon trees showed changes compared to healthy lemon trees. Since volatile compounds play an important role in attracting pests and natural enemies, linalyl acetate was selected as the compound showing the highest amount of chan

   The Compressional-wave (Vp) data are useful for reservoir exploration, drilling operations, stimulation, hydraulic fracturing employment, and development plans for a specific reservoir. Due to the different nature and behavior of the influencing parameters, more complex nonlinearity exists for Vp modeling purposes. In this study, a statistical relationship between compressional wave velocity and petrophysical parameters was developed from wireline log data for Jeribe formation in Fauqi oil field south Est Iraq, which is studied using single and multiple linear regressions. The model concentrated on predicting compressional wave velocity from petrophysical parameters and any pair of shear waves velocity, porosity, density, and

   The Compressional-wave (Vp) data are useful for reservoir exploration, drilling operations, stimulation, hydraulic fracturing employment, and development plans for a specific reservoir. Due to the different nature and behavior of the influencing parameters, more complex nonlinearity exists for Vp modeling purposes. In this study, a statistical relationship between compressional wave velocity and petrophysical parameters was developed from wireline log data for Jeribe formation in Fauqi oil field south Est Iraq, which is studied using single and multiple linear regressions. The model concentrated on predicting compressional wave velocity from petrophysical parameters and any pair of shear waves velocity, porosity, density, a

Tetradentate bidentate Schiff base (L1) from 4-amino-1.5-dimethyl-2-phenyl-1.2-dihydropyrazol-3-one and 2-(1H-indol-3-yl)-ethylamine and benzene-1.4-dicarbaldehyde was synthesized and characterized as novel antioxidants. The Schiff base and its metal complexes Mn(II), Co(II),Cu(II), Zn(II), Cd(II) and Re(V) have been characterized by elemental microanalysis, metal content, chloride-containing, molar conductance, FT-IR, 1H-NMR, UVVis spectroscopy, magnetic susceptibility, mass spectra (MS), and thermal analysis (TGA). The structures of the prepared compounds were observed by antioxidant activities of the Schiff bases derivatives were investigated due to the imine group (-C=N-) and promising results were obtained. The results confirmed that c

Semiconductor-based photocatalytic processes are widely applied as ecofriendly technology for degrading organic pollutants. Establishing photocatalytic heterojunctions with Z-type photocarriers transfer pathways is projected to be a superb strategy to enhance photocatalytic behavior. In this paper, novel and stable (0D/2D) heterojunctions of CoS-embedded boron-doped g-C3N4 (CoS/BCN) with a high rate of charges transfer/separation were assembled for degradation of malachite green dye (MG). The CoS/BCN photocatalyst achieves a photodegradation efficiency of 96.9 % within 1 h of LED illumination, which is 2.5 and 1.4-fold enhancement compared with bare g-C3N4 and BCN, respectively. Besides, the results of species-trapping trials exhibited that

Today's smart engineering systems are often faced with situations that are structurally uncertain, informationally incomplete, and non-probabilistically ambiguous, especially for electrical systems. ARDL models are limited in applications in complex computational environments where the uncertainty is due to vagueness, not randomness, and assume the exact parametric representation of the models and the structure of the stochastic uncertainty. This study proposes a new soft-computing paradigm using Fuzzy Autoregressive Distributed Lag (FARDL) models and compares the performance of the Linear Programming (LP) and Quadratic Programming (QP) estimation algorithms using large-scale parallel Monte Carlo simulations to overcome these drawba