This research aimed to identify the main sources of groundwater pollution and assess the non-carcinogenic human health risk resulting from nitrate and fluoride contamination. These goals were achieved by employing unsupervised and supervised machine algorithms, including principal component analysis (PCA) and multilayer perceptron artificial neural networks (MLP-ANN). Thirty-seven groundwater samples were analyzed for twelve physical and chemical parameters, including pH, EC, TDS, TH, Cl, F, SO₄, NO₃, Ca, Mg, Na, and HCO_3, and the initial investigation indicated that except for Cl, F, Ca, and Mg, all the parameters are above the guidelines of the World Health Organization (WHO). PCA indicated that mineral dissolution is the main source of F, while high NO₃ concentration primarily resulted from agricultural operation due to extensive use of nitrogen and calcium-based fertilizers. Consequently, the non-carcinogenic human health risk (HHR) for children and adults is evaluated based on NO₃ and F. The conventional approach for assessing HHR is time-consuming and often associated with errors in calculating hazard quotients (HQ) and hazard indices (HI). In this research, MLP-ANN is suggested to overcome these limitations. In the MLP-ANN modeling, the data were divided into two parts training (80%) and validation (20%), with NO₃ and F concentration as inputs and HQ and HI as outputs. The performance of the resulting models was tested using root mean square error (RMSE) and coefficient of determination (R²). The model provided a satisfactory result with a maximum RMSE of 4% and R² higher than 97% for training and validation. As a result, obtained HIs suggested that 97.3% of the groundwater samples in the study area are suitable for human consumption. The non-carcinogenic HHR is successfully assessed using machine learning algorithms, and the results have led to the conclusion that this approach is highly recommended for effectively managing groundwater resources.

Water scarcity is becoming a growing problem in the Middle East due to urbanization, industrialization, and population growth. Saudi Arabia is one of the region’s largest consumers of water, so it is important to take immediate action to address this issue. This study used data from the Gravity Recovery and Climate Experiment (GRACE) to assess changes in groundwater storage in Wadi Fatimah and its surrounding areas. The results showed that the average annual rainfall (AAR) in Wadi Fatimah was 131 mm, while the AAR for the entire Makah province was 99.3 mm. The AAR in Makah province can be divided into three climatic periods: Period I (April 2002-December 2011): AAR of 92.8 mm; Period II (January 2012-December 2016): AAR of 101.8 mm and Period III (January 2017-December 2021): AAR of 116.4 mm. The GRACE-derived ΔTWS (time-variable gravity) variations were −0.18 ± 0.023 cm/yr in Wadi Fatimah and −0.38 ± 0.018 cm/yr in the entire Makah Province. The soil moisture storage (ΔSMS) variations were +0.039 ± 0.025 mm/yr in Wadi Fatimah and −0.008 ± 0.002 mm/yr in the entire Makah Province. The average groundwater storage (ΔGWS) variation in Wadi Fatimah was −0.18 ± 0.022 cm/yr, which indicates a slight decrease. The ΔGWS variation in the entire Makah region was −0.38 ± 0.017 cm/yr, which indicates a negative trend. The study also found that surface runoff from rainfall in the eastern section of Wadi Fatimah flows westward to join other streams that flow into the Wadi’s central and downstream areas. This runoff replenishes the shallow alluvium deposits and aquifers. Wadi Fatimah is able to partially compensate for the impact of its groundwater extraction with a recharge rate of +0.22 ± 0.22 mm/yr. The integrated method used in this study is a helpful and economical way to evaluate groundwater resource variability over Wadi Fatimah region and its surrounding province.

griculture is considered one of the primary elements for socioeconomic stability in most parts of Sudan. Consequently, the irrigation water should be properly managed to achieve sustainable crop yield and soil fertility. This research aims to predict the irrigation indices of sodium adsorption ratio (SAR), sodium percentage (Na%), permeability index (PI), and potential salinity (PS) using innovative machine learning (ML) techniques, including K-nearest neighbor (KNN), random forest (RF), support vector regression (SVR), and Gaussian process regression (GPR). Thirty-seven groundwater samples are collected and analyzed for twelve physiochemical parameters (TDS, pH, EC, TH, Ca⁺², Mg⁺², Na⁺, HCO₃⁻, Cl, SO₄⁻², and NO₃⁻) to assess the hydrochemical characteristics of groundwater and its suitability for irrigation purposes. The primary investigation indicated that the samples are dominated by Ca-Mg-HCO₃ and Na-HCO₃ water types resulted from groundwater recharge and ion exchange reactions. The observed irrigation indices of SAR, Na%, PI, and PS showed average values of 7, 42.5%, 64.7%, and 0.5, respectively. The ML modeling is based on the ion’s concentration as input and the observed values of the indices as output. The data is divided into two sets for training (70%) and validation (30%), and the models are validated using a 10-fold cross-validation technique. The models are tested with three statistical criteria, including mean square error (MSE), root means square error (RMSE), and correlation coefficient (R²). The SVR algorithm showed the best performance in predicting the irrigation indices, with the lowest RMSE value of 1.45 for SAR. The RMSE values for the other indices, Na%, PI, and PS, were 6.70, 7.10, and 0.55, respectively. The models were applied to digital predictive data in the Nile River area of Khartoum state, and the uncertainty of the maps was estimated by running the models 10 times iteratively. The standard deviation maps were generated to assess the model’s sensitivity to the data, and the uncertainty of the model can be used to identify areas where a denser sampling is needed to improve the accuracy of the irrigation indices estimates.

A simple, time saving and accurate method for the simultaneous determination of Fe2O3, Al2O3 and TiO2 in Portland cement relies on the use of zero crossing and derivative ratio techniques has been examined. Alizarin Complexone (Alizarin-3-methylamine-N,N-diaceticacid , AC ) was used as a complexing agent. The complexes formed at pH 3.8 allow precise and accurate determination of iron (1.6 – 6.14 mgL-1), aluminum (0.63 – 1.7 mgL-1) and titanium (0.47 – 1.9 mgL-1). The validity of the method was checked by analyzing several synthetic mixtures containing different ratios of metal ions. The reproducibility was checked by analyzing a series of seven solutions each having an Fe(III), Al(III) and Ti(IV) concentration of 2.79,1.35 and 0.47 mgL-1 respectively . The relative standard deviations (RSD) are 0.70 % for iron, 0.98% for aluminum and 0.88% for titanium. The major merit of this method is the absence of matrix effect.

       A spectrophotometric method relies on the use of derivative ratio-zero crossing technique has been developed for simultaneous determination of Fe (III) and Al (III) in the presence of Ti (IV). The method depends on the formation of colored complexes of metal ions with 1,2,4-trihydroxyanthraquinone (purpurin, PURP) in 50% v/v ethanol-water medium at pH 2.5 .The method was successfully applied for the determination of (1.6 – 5.58 mgL^-1 ) iron, and (0.269 – 2.15 mgL^-1) aluminum. The correlation coefficients for the obtained calibration graphs were 0.990 for iron (III), and 0.996 for aluminum (III).  The sandell sensitivities of iron and aluminum were 0.24ng cm^-2 and 0.20ng cm^-2 respectively. The developed method was applied to the simultaneous determination of Fe₂O₃ and Al₂O₃ in Portland cement and was found to give satisfactory results.

The effect of annealing temperature (T_a= 200, 250, and 300 °C) on the structural properties, ac conductivity, and complex dielectric constants ( and ) of indium-doped tin oxide (ITO) thin films (~ 90 nm thick)/0.5 mm boro-float substrates (BFS) synthesized by radio frequency (RF) sputtering is investigated. The X-ray diffraction (XRD) examination demonstrated that indium was successfully substituted with tin atoms to form ITO films and the crystallite size for the cubic phase, as well as particle size, were impacted by T_a. The real part of complex dielectric constants () was significantly reduced for all ITO/BFS from the range of 2.7 × 10⁴–5.1 × 10⁴ to 5.3–19 as the frequency (f) was increased to 0.25 Hz, while it remained constant for further increases in f. The value of for the as-prepared ITO/BFS was increased as T_a increased up to 250 °C, then was decreased at T_a=300 °C. A similar finding was detected for the loss factor with no observation of any relaxation peaks. The Q-factor was increased for all ITO/BFS as f increased to 100 Hz and then was reduced with increasing f up to 20 MHz, while steadily increasing with T_a. The deduced frequency exponent is greater than 0.5 for the ITO/BFS, indicating their electronic conduction nature. The density of the localized states and hopping frequency of the ITO/BFS were increased by annealing at 200 °C, meanwhile was decreased for T_a = 300 °C. The binding energy was decreased from 0.647 eV for the as-prepared ITO/BFS to 0.518 eV by annealing at 200 °C, meanwhile was increased to 0.74 and 0.863 eV for T_a equals 250, and 300 °C, respectively. The Cole-Cole plots revealed a single semicircular arc for all films, and their corresponding equivalent circuit was analyzed. The equivalent bulk resistance was gradually decreased by annealing in the range of 200–300 °C, whereas the equivalent capacitance was increased. The resistance of grains and resistance of grain boundaries of the as-prepared ITO/BFS was gradually decreased by increasing T_a to 250 °C, while it was increased for T_a = 300 °C. These outcomes recommended the RF sputtered ITO/BFS for high-frequency devices, integrated circuits, and supercapacitors.

(ZnSn)_1-xCu_xO nanocomposites (NCs) with nanorods and nanosheet morphologies were synthesized by a facile hydrothermal technique. (ZnSn)_1-xCu_xO NCs exhibited a gradual band gap redshift from UV to visible spectral region with increasing Cu-content. The room temperature magnetic hysteresis loop indicated the improvement of room temperature ferromagnetic (RTFM) behavior of (ZnSn)_1-xCu_xO NCs compared with nanostructured ZnSnO NCs induced by the exchange interaction of Cu-bound polarons with the localized spins and free carriers. The (ZnSn)₆₀Cu₄₀O NCs exhibited the highest saturation magnetization (M_s) of 0.539 emu·g⁻¹. Further increase in Cu-content resulted in the deterioration of crystalline domains and the reduction of M_s to 0.259 emu·g⁻¹. This behavior revealed that the electronic and magnetic properties of (ZnSn)_1-xCu_xO NCs were so sensitive to the dopant concentration that need to be utilized for improving their performance as good candidate NCs for spintronic applications.

We report here the FTIR, optical, and magnetic properties of Sn_1-x-yZn_xM_yO_z ceramics with various x, y, and M. The pure samples are called S1, S2, and S3 for ZnO, SnO₂, and SnZn. The co-substituted samples are called S4, S5, S6, and S7 for SnZnFe, SnZnCo, SnZnNi, and SnZnMn, with Zn = 0.50, Sn = 0.25, and M = 0.25. The Young's modulus, was decreased from 5.70 (D/cm²) for S3 to 4.59, 3.14, 2.59, and 3.05 (D/cm²) for S4, S5, S6, and S7. The E_g was decreased from 2.13 eV for S3 to 2.16, 2,2, and 1.6 eV for S4, S5, S6, and S7. The pure samples (S1–S3) exhibit ferromagnetic behavior at 300 K, and combination of paramagnetic and ferromagnetic behaviors at 10K. In contrast, the samples (S4–S7) exhibit a combination of paramagnetic and ferromagnetic behaviours at both temperatures. The Curie temperature (T_c) obtained through zero-field cooling (ZFC) and field cooling (FC) is close to 300 K for S1–S3, S5, S6, 200 K for S4, and 20 K for S7. The real saturated magnetization (M_s) of the ZnO sample was decreased by the addition of SnO₂, and then increased by the addition of Mn, Ni, Fe, and Co sequentially. M_s was increased from 12.31 (emu/g) for S3 at 300 to 16.24, 31.04, 27.27, and 10.49 (emu/g) for S4, S5, S6, and S7, and from 16 (emu/g) to 87, 730, 83, and 29 at 10 K. Remnant magnetization (M_r) decreases with the addition of SnO₂ to ZnO and is not affected by the addition of TMs, just in the case of Co, where it increases. The coercive field decreases, but the switching field increases markedly with the addition of Mn and Ni, transforming the system from a hard magnetization to a soft magnetization system.

Binder-free Mn₂O₃–MoS₂ hybrid composites (HCs) were fabricated using a room-temperature kinetic spray process under low-pressure conditions with various weight ratios of Mn₂O₃–MoS₂ (1:1, 1:2, and 1:4). The effect of the composition ratio on the electrocatalytic activity of Mn₂O₃–MoS₂ HCs toward the oxygen evolution reaction (OER) in an alkaline medium was investigated. The deposited MoS2 exhibits microrods (MRs) morphology, while pure Mn2O3 exhibits nanoflakes (NFs) morphology. The Mn₂O₃–MoS₂ HCs exhibited NFs-decorated MR morphology. Multilayer heterostructure morphology significantly improves the interfacial synergy between various electroactive species that were verified using various spectroscopic techniques such as micro-Raman and X-ray photoemission spectra. As the MoS₂ content in the Mn₂O₃–MoS₂ HCs increased, the
interfacial charge transfer kinetics associated with the reduction in the oxidation barrier potential improved. The Mn₂O₃–MoS₂ HCs with a 1:4 ratio demonstrated the optimum combination for OER with the smallest overpotential of 290 mV @10 mA cm⁻² and Tafel slope of 41 mV dec⁻¹. The long-term OER stability of the fabricated electrocatalysts was verified using chronopotentiometry techniques for 50 h at 50 mA cm⁻²