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In the construction and cement manufacturing sectors, the development of artificial intelligence models has received remarkable progress and attention. This paper investigates the capacity of hybrid models conducted for predicting the compressive strength (CS) of concrete where the cement was partially replaced with ground granulated blast-furnace slag (FS) and fly ash (FA) materials. Accurate estimation of CS can reduce the cost and laboratory tests. Since the traditional method of calculation CS is complicated and requires lots of effort, this article presents new predictive models called SVR−PSO and SVR−GA, that are a hybridization of support vector regression (SVR) with improved particle swarm algorithm (PSO) and genetic algorithm (GA). Furthermore, the hybrid models (i.e., SVR−PSO and SVR−GA) were used for the first time to predict CS of concrete where the cement component is partially replaced. The improved PSO and GA are given essential roles in tuning the hyperparameters of the SVR model, which have a significant influence on model accuracy. The suggested models are evaluated against extreme learning machine (ELM) via quantitative and visual evaluations. The models are evaluated using eight statistical parameters, and then the SVR-PSO has provided the highest accuracy than comparative models. For instance, the SVR−PSO during the testing phase provided fewer root mean square error RMSE with 1.386 MPa, a higher Nash–Sutcliffe model efficiency coefficient (NE) of 0.972, and lower uncertainty at 95% (U95) with 28.776%. On the other hand, the SVR−GA and ELM models provide lower accuracy with RMSE of 2.826 MPa and 2.180, NE with 0.883 and 0.930, and U95 with 518.686 183.182, respectively. Sensitivity analysis is carried out to select the influential parameters that significantly affect CS. Overall, the proposed model showed a good prediction of CS of concrete where cement is partially replaced and outperformed 14 models developed in the previous studies.

Failure modes in composite plates with bolted joint configuration include net-tension, shear-out and bearing failures. Few analytical and numerical approaches in strength prediction frameworks of composite plates with bolted joints were reported in the literatures. Present works are dealing with strength prediction in bearing failure of woven fabric CFRP plates with double lap bolted joint configurations by modeling 3D finite element analysis framework. The pre-processing stage is modeled using commercial ABAQUS CAE package and takes into account all parts interactions, clamping pressure and friction contact. Testing series are following the experimental works found from the literatures with variation of plate width to hole diameter (W/d) ratios and incorporated with finger-tight clamp-up. Hashin failure criterion was implemented as constitutive modeling in current analysis, based on ply-by-ply approaches found to be more appropriate phenomenon in bearing failure. The strength prediction results demonstrated good agreement with all experimental datasets particularly with bearing failures as compared with previously reported work, used stress concentration approach found to be accurate in net-tension failure only.

In this research, a numerical analysis is accomplished aiming to investigate the effects of adding a new design fins arrangement to a vertical triplex tube latent heat storage system during the melting mechanism and evaluate the natural convection effect using Ansys Fluent software. In the triplex tube, phase change material (PCM) is included in the middle tube, while the heat transfer fluid (HTF) flows through the interior and exterior pipes. The proposed fins are triangular fins attached to the pipe inside the PCM domain in two different ways: (1) the base of the triangular fins is connected to the pipe, (2) the tip of the triangular fins is attached to the pipe and the base part is directed to the PCM domain. The height of the fins is calculated to have a volume equal to that of the uniform rectangular fins. Three different cases are considered as the final evaluation toward the best case as follows: (1) the uniform fin case (case 3), (2) the reverse triangular fin case with a constant base (case 12), (3) the reverse triangular fin case with a constant height (case 13). The numerical results show that the total melting times for cases 3 and 12 increase by 4.0 and 10.1%, respectively, compared with that for case 13. Since the PCM at the bottom of the heat storage unit melts slower due to the natural convection effect, a flat fin is added to the bottom of the heat storage unit for the best case compared with the uniform fin cases. Furthermore, the heat storage rates for cases 3 and 12 are reduced by 4.5 and 8.5%, respectively, compared with that for case 13, which is selected as the best case due to having the lowest melting time (1978s) and the highest heat storage rate (81.5 W). The general outcome of this research reveals that utilizing the tringle fins enhances the thermal performance and the phase change rate.

The present work is an experimental study and interested in hexaferrite samples preparation of the system Ba0.2Sr0.8Fe12O19 nanoparticle powder by chemical coprecipitation method used to prepare fine nanoparticles. The structural properties of this system have been investigated using scanning electron microscopy-Energy dispersive X-Ray spectroscopy (SEM-EDS) and were found the average grain size to be (33.685)nm. Magnetic properties were calculated by vibrating sample magnetometry (VSM), it was the results proved that the saturation magnetization reaches to (85.633)emu/gr and the residual magnetization is (39.342)emu/gr. The coercivity of (4665.909)Oe is also observed. The hysteresis loop was studied and shown that, this system of hard ferrite materials.

The present work is an experimental study and interested in hexaferrite samples preparation of the system Ba 0.2 Sr 0.8 Fe 12 O 19 nanoparticle powder by chemical coprecipitation method used to prepare fine nanoparticles. The structural properties of this system have been investigated using scanning electron microscopy-Energy dispersive X-Ray spectroscopy (SEM-EDS) and were found the average grain size to be (33.685)nm. Magnetic properties were calculated by vibrating sample magnetometry (VSM), it was the results proved that the saturation magnetization reaches to (85.633)emu/gr and the residual magnetization is (39.342)emu/gr. The coercivity of (4665.909)Oe is also observed. The hysteresis loop was studied and shown that, this system of hard ferrite materials.

Hartree-Fock (HF) method relies in the calculations of nonlinear optical properties (NLO) for benzoic acid molecule. Also, another theoretical study is conducted by using the TD-DFT Density Functional Theory through B3LYP/High Base Set 6-311++G (2d,2p) on Gaussian program09. Moreover, an experimental study has been done to obtain the electrons spectrum for benzoic acid with and without ethanol. While the experimental study is done by using UV/VIS. spectrophotometer. Energy gap values of electronic transition between HOMO and LUMO is obtained from theoretical and experimental results. Consequently, the theoretical result for determining the energy gap calculated from EHOMO-LUMO wasvery close to the results of UV / VIS. spectrum. A theoretical method is considered extremelyvappropriate towards compounds capable of absorbing in vacuum UV.

Acremonium wilt disease affects grain quality and reduces sorghum yield around the globe. The present study aimed to assess the efficacy of humic acid (HA)-coated Fe3O4 (Fe3O4/HA) nanoparticles (NPs) in controlling acremonium wilt disease and improving sorghum growth and yields. During the season 2019, twenty-one sorghum genotypes were screened to assess their response to Acremonium striticum via artificial infection under field conditions and each genotype was assigned to one of six groups, ranging from highly susceptible to highly resistant. Subsequently, over the two successive seasons 2020 and 2021, three different concentrations of 10, 40 and 80 mg L−1 of Fe3O4/HA NPs were tested against A. striticum. The concentrations of 40 and 80 mg L−1 were found to be highly effective in controlling acremonium wilt disease on different sorghum genotypes: LG1 (highly susceptible), Giza-3 (susceptible), and Local 119 (resistant) genotypes. After harvest, the physiological (growth and yield) and biochemical (peroxidase, catalase, and gibberellic acid) attributes of sorghum plants were determined, and the results demonstrated that concentrations of 40 and 80 mg L−1 increased peroxidase and catalase activities in healthy (uninoculated) sorghum genotypes compared to inoculated sorghum genotypes. Additionally, the toxicity of Fe3O4/HA NPs on male albino rats was investigated via hematological (CBC), chemical (ALT and AST) and histopathological analyses. The concentration 80 mg L−1 of Fe3O4/HA NPs caused a marked increase in ALT and creatinine level after 51 days of feeding. Severe pathological alterations were also observed in liver and kidney tissues of rats administered with grain sorghums treated with 80 mg L−1. In comparison with the untreated control plants, a concentration of 40 mg L−1 significantly increased the growth, yield and gibberellic acid levels (p ≤ 0.05) and was found to be safe in male albino rats. Conclusively, a concentration of 40 mg L−1 of Fe3O4/HA NPs showed promising results in curtailing A. striticum infections in sorghum, indicating its great potential to substitute harmful fertilizers and fungicides as a smart agriculture strategy.

The estimation of soil wet bulk density (ρn) and dry bulk density (ρb) using the novel digital electromechanical system (DES) has provided information about important parameters for the assessment of soil quality and health with a direct application for agronomists. The evaluation of the DES performance is particularly appropriate for different tillage methods, mulching systems, and fertilizers used to increase soil fertility and productivity, but currently, there is a lack of information, particularly in the arid areas in underdeveloped countries. Therefore, the main aim of this study was the application of a novel digital electromechanical system (DES) to evaluate bulk density, wet (ρn) and dry (ρb), under different soil treatments according to the variations in thermal efficiencies (ηth), microwave penetration depths (MDP), and specific energy consumption (Qcon) in an experimental area close to Baghdad (Iraq). The experimental design consisted of 72 plots, each 4 m2. The agronomic practices included two different tillage systems (disc plough followed by a spring disk and mouldboard plough followed by a spring disk) and twelve treatments involving mulching plastic sheeting combined with fertilizers, to determine their effect on the measured soil ρn and ρb and the DES performance in different soils. The results indicated that soil ρn and ρb varied significantly with both the tillage systems and the mulching systems. As expected, the soil ρn and ρb, MDP, and Qcon increased with an increase in the soil depth. Moreover, the tillage, soil mulching, and soil depth value significantly affected ηth and Qcon. A strong relationship was identified between the soil tillage and MDP for different soil treatments, leading to the changes in soil ρb and the soil dielectric constant (ε’).

Acremonium wilt disease affects grain quality and reduces sorghum yield around the globe. The present study aimed to assess the efficacy of humic acid (HA)-coated Fe O (Fe O /HA) nanoparticles (NPs) in controlling acremonium wilt disease and improving sorghum growth and yields. During the season 2019, twenty-one sorghum genotypes were screened to assess their response to via artificial infection under field conditions and each genotype was assigned to one of six groups, ranging from highly susceptible to highly resistant. Subsequently, over the two successive seasons 2020 and 2021, three different concentrations of 10, 40 and 80 mg L of Fe O /HA NPs were tested against . The concentrations of 40 and 80 mg L were found to be highly effective in controlling acremonium wilt disease on different sorghum genotypes: LG1 (highly susceptible), Giza-3 (susceptible), and Local 119 (resistant) genotypes. After harvest, the physiological (growth and yield) and biochemical (peroxidase, catalase, and gibberellic acid) attributes of sorghum plants were determined, and the results demonstrated that concentrations of 40 and 80 mg L increased peroxidase and catalase activities in healthy (uninoculated) sorghum genotypes compared to inoculated sorghum genotypes. Additionally, the toxicity of Fe O /HA NPs on male albino rats was investigated via hematological (CBC), chemical (ALT and AST) and histopathological analyses. The concentration 80 mg L of Fe O /HA NPs caused a marked increase in ALT and creatinine level after 51 days of feeding. Severe pathological alterations were also observed in liver and kidney tissues of rats administered with grain sorghums treated with 80 mg L . In comparison with the untreated control plants, a concentration of 40 mg L significantly increased the growth, yield and gibberellic acid levels ( ≤ 0.05) and was found to be safe in male albino rats. Conclusively, a concentration of 40 mg L of Fe O /HA NPs showed promising results in curtailing infections in sorghum, indicating its great potential to substitute harmful fertilizers and fungicides as a smart agriculture strategy.