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This study evaluates groundwater quality in the Lower Cretaceous Aquifer (LCA) of Timimoun, Algeria, for drinking and agricultural uses, focusing on geochemical influences on water mineralization and public health risks. A total of 44 groundwater samples were analyzed for physicochemical parameters, including pH, major ions (Ca2+, K+, Na+, Mg2+, SO42−, Cl−, NO3−, HCO3−) total dissolved solids (TDS), and electrical conductivity (EC). The Water Quality Index (WQI) categorized the groundwater as good (54.54 %), poor (31.82 %), very poor (9.09 %), and unsuitable for drinking (4.55 %). Agricultural suitability was assessed using metrics such as Sodium Adsorption Ratio (SAR), Sodium Percentage (Na%), and Permeability Index (PI), revealing a range from permissible to doubtful irrigation quality. Examination of Gibbs and Piper plots and relationships between major elements, alongside the calculations for saturation indices of key minerals, revealed the groundwater was weakly alkaline with dominant Ca-Mg-Cl and Na-Cl hydrogeochemical types in the LCA water. The processes of evaporite and silicate minerals dissolution and cationic exchange were the dominant mechanisms behind the ion generation. Notably, Nitrate concentrations (9–80 mg/L) exceeded safe limits in 29.54 % of samples, posing significant health risks, especially to infants and children, with Hazard Quotient (HQ) values exceeding 1 in 97.73 % of infants, 95.45 % of children, and 45.54 % of adults. The integration of the water quality index, health risk assessments, hydrogeochemical modeling, and GIS mapping provides a comprehensive framework for analyzing groundwater in arid regions under pressure from climate change and human activities. These findings highlight the need for integrated strategies for sustainable groundwater management worldwide.

Abstract Groundwater quality assessment is crucial for the sustainable management of water resources in arid regions, where groundwater is the primary source of water supply and increasing demand raises concerns. The study area in Southwest Algeria relies heavily on groundwater as a source of water supply, and the increasing demand for freshwater raises concerns about the quality of groundwater. To assess the hydrochemical characteristics and water quality of groundwater in the Ain Sefra region, multivariate statistical methods, geochemical modeling and water quality indices were employed. The study revealed that the groundwater samples could be classified into four water groups using hierarchical cluster analysis Q mode (HCA), namely Ca–Mg–HCO3, Ca–Mg–Cl–SO4, Ca–SO4 and Na–Cl. Factor analysis was used to identify the main factors controlling the study area’s hydrochemical processes. The results indicated that water–rock interaction, reverse ion exchange and anthropogenic pollution were the main hydrochemical processes affecting groundwater chemistry. The water quality index indicated that the groundwater was suitable for human consumption, with only 2.32% of the samples being unsuitable. Additionally, the groundwater was suitable for agricultural use, but salinity control was necessary. The saturation index values showed that the groundwater was supersaturated with aragonite, calcite, dolomite, anhydrite and gypsum, and undersaturated with halite. Ca-smectite, Mg-smectite and kaolinite were identified as the primary processes controlling the chemical composition of groundwater. The application of multivariate statistical methods, geochemical modeling and water quality indices provided a comprehensive understanding of the hydrochemical characteristics and water quality of groundwater in the Ain Sefra region. The findings of the study can serve as a useful basis for future studies on groundwater quality assessment in the region.

In light of existing literature of stable ferromagnetic phase, the thermoelectric and optical behavior of the Cd-based spinel chalcogenides i.e. CdCr2X4, (X = S, Se, Te) were inspected and their structural and electronic characteristics were examined in terms of density functional theory calculations. The negative values of formation energy of said spinels were calculated to confirm their ferromagnetic phase stability. Optimization of band structure and calculations of density of states confirmed their ferromagnetic nature. For both channel, the band structure exhibited the semiconducting behavior. The exchange constants (N0α and N0β) were investigated with the help of exchange splitting energies, which were explored from the density of states. The splitting of 3d-states of Cr were explained on the basis of larger value of N0β as compared with N0α. Owing to the strong p-d hybridization indicated by N0β = −0.11, −0.12 and −0.15 and N0α = 0.14, 0.32 and 0.44 for CdCr2S4, CdCr2Se4 and CdCr2Te4, respectively, the necessary condition for ferromagnetic system is satisfied showing that exchange field dominates over the crystal field that induces the ferromagnetism in these spinels. Moreover the p-d hybridization was used to decrease the magnetic moment at Cr ions, by using a fraction of magnetic moment at non-magnetic sites. Further, optical characteristics were investigated in terms of photon energy 0–6 eV showing less dispersion of light and refractive index ranges up to 1–1.5 in visible region, thus suggesting spinels as potential candidates for opto-electronic applications. The thermoelectric performance observed in the temperature range of 200–600K which indicate positive Seebeck coefficients of ∼250 CdCr2S4, CdCr2Se4 while a negative Seebeck coefficients of −112 for CdCr2Te4 at room temperature. Further the power factors increased from S to Te as well as with increase of temperature which shows the potential of these chalcogens for thermoelectric power generators.

The 2,4-Dicholorophenoxyacetic acid (2,4-D) is a herbicide used against broad leave herbs and it is carcinogenic and mutagenic in nature, which need to be remediated to avoid negative impact on the living organisms. In view of promising adsorption efficiency of composite materials, the present investigation is focused on the preparation of polypyrrole (PPY) and sugarcane bagasse (SB) based composites. The composites were characterized for surface properties and thermal stability. The prepared composite was utilized for the sequestration of 2,4-D from aqueous solution in column mode as function of bed height, flow rate and 2,4-D concentration. Thomas model was applied to the rate of adsorption at different 2,4-D concentrations, flow rates and bed heights to predict the breakthrough curves. The BDST (bed depth service time) model was also applied to predict the breakthrough curves as function of bed heights. The biosorption capacities of SB and PPY/SB were 6.1 and 8.63 (mg/g), respectively. The results indicated that sugarcane bagasse composite with PPY is efficient adsorbent for the remediation of 2,4-D and could have potential for the removal of herbicides from effluents.

The spinel ferrites have been manufacturing long time because of their variety of applications in technological and industrial field. In the following study, the samarium doped spinel ferrites were under examination. The prepared compositions were denoted as; SrSmxFe2–xO4, x = 0, 0.025, 0.05, 0.075, 0.10. Sol–gel procedure was employed to make these samples. All the samples were investigated through the X-ray diffraction technique. The phase of prepared product was detected for the first three samples. However, the orthorhombic phase, that is, SmFeO3, was traced when samarium (Sm) composition reached 0.075 and above. The smaller width of the M–H loop confirmed the formation of soft ferrites. Saturation and remanence values were diminished with the substitution of samarium ions. But the anisotropy constant as well as coercivity values was enhanced with the samarium contents. Above mentioned features of spinel ferrites showed their possible usage in high-density recording applications.

The current study is the first to disclose a quick, cost-effective, and environmentally safe phytofabrication of gold nanoparticles (AuNPs) that remained stable for three months utilizing the aqueous extract of T. capensis leaves to uphold the principles of green chemistry such as less hazardous chemical syntheses, safer solvents and auxiliaries, design for energy efficiency, and use of renewable feedstocks. Several approaches were used to describe T. capensis-AuNPs, with the findings revealing the successful phytoformation of crystalline AuNPs with a dark brown color, spherical nanoparticles with a size range of 10–35 nm, a surface plasmon peak at 515 nm, and a surface charge of − 24.5 mV. T. capensis-AuNPs showed 72% photodegradation efficacy against malachite green. The MTT experiment revealed that T. capensis-AuNPs and T. capensis extract had excellent potency in preventing the development and proliferation of human breast cancer cells (MCF7 cell line), with IC50 values of 9.6 g/mL and 23.3 g/mL, respectively. Both T. capensis-AuNPs and T. capensis extract had significant antioxidant efficacies, with DPPH scavenging percentages of 70.73% for T. capensis-AuNPs and 85.62% for T. capensis extract. Consequently, these findings suggest a new and sustainable route for the green synthesis of AuNPs using the aqueous extract of T. capensis.

Presently, biodiesel offers a sustainable and renewable substitute for exhausting fossil fuels such as Petro-diesel. Large scale production of biodiesel could lead to positive outcomes in terms of environmental quality by reducing greenhouse gasses emission and Societal-Economic development. Hence, this research work focused on biodiesel synthesis from novel and non-edible seed oil of Monotheca buxifolia using green nano-particles of calcium oxide synthesized with aqueous leaves extract of Boerhavia procumbens. Advanced techniques like X-Ray Diffraction (XRD), Scanning Electron Microscopy (SEM), and Energy diffraction X-Ray (EDX) were used to characterize calcium oxide nano-particles. High yield of biodiesel (95%) was obtained at optimum reaction conditions such as methanol to oil molar ratio of 9:1, catalyst loading 0.83 (wt.%), reaction time 180 min and temperature 85 °C. Gas Chromatography/Mass spectroscopy (GC/MS) analysis of biodiesel revealed four distinct peaks of methyl esters. Results of Fourier-transform infrared spectroscopy (FTIR) and Nuclear magnetic resonance (NMR) confirmed the formation of methyl esters in biodiesel sample. Fuel properties of biodiesel such as density (0.821 kg/m3), viscosity (5.35 mm2/s), cloud point (-8 ◦C), pour point (-9 ◦C) and flash point (95 ◦C) were found equivalent to international ASTM D-6571, EN 14,214 and China GB/T 20828–2007 standards. It was finally concluded that Monotheca buxifolia is a highly potential, eco-friendly, and cheaper biomass feedstock for biodiesel production.

In this work, for the use of an electrical double-layer capacitor (EDLC) device applications, the fabrication and characterization of solid polymer electrolytes (SPEs) based on chitosan-dextran (CS-DN) blended polymer doped and plasticized with ammonium thiocyanate (NH4SCN) and glycerol are studied, respectively. The Fourier transform infrared (FTIR) spectroscopy method has been used to investigate the structural behavior of electrolytes. It was observed that the FTIR bands are shifted and decreased in their intensities with the increased glycerol plasticizer content and it results in the complex formation. According to the electrical impedance spectra (EIS), the electrolyte incorporated with high contents of plasticizer (42 wt%) revealed the highest ionic conductivity of (3.08 × 10−4 S/cm). The electrical equivalent circuits (EEC) were used to investigate the circuit elements of the electrolytes further. Increasing glycerol plasticizers verified an improvement in ions density number (n), mobility (μ), and diffusion coefficient (D). The transference number measurements (TNM) indicated that the predominant charge carriers in the conduction process are ions where the (tion) is 0.95. According to the linear sweep voltammetry (LSV) study, the uppermost conducting sample was found to have sufficient anode stability with a breakdown voltage of 1.9 V that can be used in electrochemical devices. The absence of peaks in the cyclic voltammetry (CV) demonstrated that the charge storage mechanism within the constructed EDLC is fully capacitive. Based on this finding, the starting specific capacitance (Cs), energy density (Ed), and power density (Pd) have been identified to be 118F/g, 13.2 Wh/kg, and 1560 W/kg, respectively. Throughout its 100 cycles, the equivalence series resistance ESR value was between 53 and 117 Ω.

Abstract There are some sources of pollution of the groundwater such as the industrial, agriculture, domestic activities and the oxidation ponds that are considered collection points for waste disposal plants. The motivations to do this work were: (1) investigating the concentrations of pollutants in the oxidation ponds and well surrounding the 10th Ramadan city and (2) predicting the groundwater flow and the pollutant transport to the groundwater from the pollution source using a numerical simulation (MODFLOW-2000 with MT3D code). The samples of groundwater were collected from the wells that spread around the studied area as well as many samples were collected from the oxidation ponds to investigate the concentrations of pollutants in these samples and predict the pollutant transport to the groundwater over 30 years. The results illustrated that the ion concentration of most samples from the oxidation ponds resources contained Al3+, Fe2+, Sr2+, Ni2+, and Cr2+ which were exceeding the acceptable limit of WHO (International standards for drinking water, WHO, Geneva, 1996) standards. The results also demonstrated that most of the analyzed groundwater samples are polluted with strontium (Sr2+), aluminum (Al3+), and iron (Fe2+). The simulation predicted that the pollutants movements toward the northeast of the study zone over a long-term period (30 years).

This paper presents the operational modal analysis of a 90-m-high RC minaret of an iconic mosque considered as a landmark of the city. The minaret was monitored for three days with 11 tri-axial MEMS accelerometers. The purpose of the study was to observe the behavior, develop a representative finite element (FE) model, and establish baseline data for health monitoring studies. The modal properties were extracted using three operational modal analysis techniques (OMA): Enhanced Frequency Domain Decomposition (EFDD), Stochastic Subspace Identification (SSI), and Natural Excitation Technique with Eigensystem Realization Algorithm (NExT-ERA). The first 10 identified modes were below 7 Hz. Eight modes out of the ten were bending-dominant, while the remaining two were torsion-dominant. A FE model was also developed in ETABS to ascertain and compare the response of the structure with the identified results. From the FE model, the modes corresponding to the first ten identified modes were considered for comparison with the identified frequencies from ambient monitoring. The maximum 7.71% error was observed between the experimental and numerical frequencies. The error was minimized by using the manual updating the material properties and adding the weight of nonstructural elements. The variation of identified modal frequencies with ambient temperature was observed to be linearly dependent to a reasonable degree. A general trend of decreasing identified frequencies was observed with the rise in temperature.

The investigation of travel mode choice is an essential task in transport planning and policymaking for predicting travel demands. Typically, mode choice datasets are imbalanced and learning from such datasets is challenging. This study deals with imbalanced mode choice data by developing an algorithm (SVMAK) based on a support vector machine model and the theory of adjusting kernel scaling. The kernel function’s choice was evaluated by applying the likelihood-ratio chi-square and weighting measures. The empirical assessment was performed on the 2017 National Household Travel Survey–California dataset. The performance of the SVMAK model was compared with several other models, including neural networks, XGBoost, Bayesian Network, standard support vector machine model, and some SVM-based models that were previously developed to handle the imbalanced datasets. The SVMAK model outperformed these models, and in some cases improved the accuracy of the minority class classification. For the majority class, the accuracy improvement was substantial. This algorithm can be applied to other tasks in the transport planning domain that deal with uneven data distribution.

Precise quantification of evaporation has a vital role in effective crop modelling, irrigation scheduling, and agricultural water management. In recent years, the data-driven models using meta-heuristics algorithms have attracted the attention of researchers worldwide. In this investigation, we have examined the performance of models employing four meta-heuristic algorithms, namely, support vector machine (SVM), random tree (RT), reduced error pruning tree (REPTree), and random subspace (RSS) for simulating daily pan evaporation (EPd) at two different locations in north India representing semi-arid climate (New Delhi) and sub-humid climate (Ludhiana). The most suitable combinations of meteorological input variables as covariates to estimate EPd were ascertained through the subset regression technique followed by sensitivity analyses. The statistical indicators such as root mean square error (RMSE), mean absolute error (MAE), Nash–Sutcliffe efficiency (NSE), Willmott index (WI), and correlation coefficient (r) followed by graphical interpretations, were utilized for model evaluation. The SVM algorithm successfully performed in reconstructing the EPd time series with acceptable statistical criteria (i.e., NSE = 0.937, 0.795; WI = 0.984, 0.943; r = 0.968, 0.902; MAE = 0.055, 0.993 mm/day; and RMSE = 0.092, 1.317 mm/day) compared with the other applied algorithms during the testing phase at the New Delhi and Ludhiana stations, respectively. This study also demonstrated and discussed the potential of meta-heuristic algorithms for producing reasonable estimates of daily evaporation using minimal meteorological input variables with applicability of the best candidate model vetted in two diverse agro-climatic settings.

This study presents the performance of quarry rock dust (QRD) incorporated fly ash (FA) and slag (SG) based geopolymer concretes (QFS-GPC) exposed to ambient and elevated temperatures. A total of five QFS-GPC mix types were prepared. The quantity of FA (50%) was kept constant in all the mixes, and SG was replaced by 5%, 10%, 15%, and 20% of QRD. The fresh, hardened properties of the QFS-GPC mixes, viz., workability, compressive strength, splitting tensile strength, and flexural strengths, and XRD for identification of reaction phases were evaluated. The prepared mixes were also heated up to 800 °C to evaluate the residual compressive strength and weight loss. The workability of the QFS-GPC mixes was observed to be reduced by increasing the dosage (0 to 20%) of QRD. Superplasticizer (SP) was used to maintain the medium standard of workability. The compressive, tensile, and flexural strengths were increased by replacing SG with QRD up to 15%, whereas a further higher dosage (20%) of QRD reduced the mechanical strengths of the QFS-GPC mixes. The strength of the QFS-GPC specimens, heated to elevated temperatures up to 800 °C, was reduced persistently with the increased contents of QRD from 0 to 20%. It was concluded from the study that QFS-GPC can be used to achieve 30 MPa strength of concrete.

The adsorption of dyes using 39 adsorbents (16 kinds of agro-wastes) were modeled using random forest (RF), decision tree (DT), and gradient boosting (GB) models based on 350 sets of adsorption experimental data. In addition, the correlation between variables and their importance was applied. After comprehensive feature selection analysis, five important variables were selected from nine variables. The RF with the highest accuracy (R2 = 0.9) was selected as the best model for prediction of adsorption capacity of agro-waste using the five selected variables. The results suggested that agro-waste characteristics (pore volume, surface area, agro-waste pH, and particle size) accounted for 50.7% contribution for adsorption efficiency. The pore volume and surface area are the most important influencing variables among the agro-waste characteristics, while the role of particle size was inconspicuous. The accurate ability of the developed models’ prediction could significantly reduce experimental screening efforts, such as predicting the dye removal efficiency of agro-waste activated carbon according to agro-waste characteristics. The relative importance of variables could provide a right direction for better treatments of dyes in the real wastewater.

Titanium dioxide (TiO2) has been widely applied as a photocatalyst for wastewater treatment due to its high photocatalytic activity and it can remove various harmful organic pollutants effectively. Under heated system, however, TiO2 is prone to agglomeration that decrease its abilities as a photocatalyst. In order to overcome the agglomeration and increase its thermal resistance, addition of silica (SiO2) as supporting material is proposed in this research. Silica or silicon dioxide can be extracted from natural resources such as beach sand. Here, we report the application of a composite photocatalyst of TiO2/SiO2 to remove phenolic compounds in wastewater. The photocatalyst was synthesized by adding SiO2 from beach sand onto TiO2 through impregnation methods. The results of the X-ray diffraction (XRD) showed that TiO2 was present in the anatase phase. The highest crystallinity was obtained by TiO2/SiO2 ratios of 7:1. SEM results showed that the shape of the particles was spherical. Further characterizations were conducted using Fourier-transform infrared spectroscopy (FTIR), Brunauer–Emmett–Teller (BET) analysis, and a particle size analyzer (PSA). By using the optimized condition, 96.05% phenol was degraded by the synthesized photocatalyst of TiO2/SiO2, under UV irradiation for 120 min. The efficiency of the TiO2/SiO2 is 3.5 times better than commercial TiO2 P25 for the Langmuir–Hinshelwood first-order kinetic model.