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In this work, a novel isatin-Schiff base L2 had been synthesized through a simple reaction between isatin and 2-amino-5-methylthio-1,3,4-thiadiazole. The produced Schiff base L2 was then subjected to a hydrothermal reaction with cerium chloride to produce the cerium (III)-Schiff base complex C2. Several spectroscopic methods, including mass spectra, FT-IR, elemental analysis, UV–vis, 13 C-NMR, 1 H-NMR, Thermogravimetric Analysis, HR-TEM, and FE-SEM/EDX, were used to completely characterize the produced L2 and C2. A computer simulation was performed using the MOE software program to find out the probable biological resistance of studied compounds against the proteins in some types of bacteria or fungi. To investigate the interaction between the ligand and its complex, we conducted molecular docking simulations using the molecular operating environment (MOE). The docking simulation findings revealed that the complex displayed greater efficacy and demonstrated a stronger affinity for Avr2 effector protein from the fungal plant pathogen Fusarium oxysporum (code 5OD4) than the original ligand. The antibacterial activity of the ligand and its Ce 3+ complex were applied in vitro tests against different microorganism. The study showed that the complex was found to be more effective than the ligand.

The rising demand for sustainable aquaculture necessitates innovative solutions to environmental and operational challenges. Biofloc technology (BFT) has emerged as an effective method, leveraging microbial communities to enhance water quality, reduce feed costs, and improve fish health. However, traditional BFT systems are susceptible to water quality fluctuations, demanding precise monitoring and control. This review explores the integration of Artificial Intelligence (AI) and Internet of Things (IoT) technologies in smart BFT systems, highlighting their capacity to automate processes, optimize resource utilization, and boost system performance. IoT devices facilitate real-time monitoring, while AI-driven analytics provide actionable insights for predictive management. We present a comparative analysis of AI models, such as LSTM, Random Forest, and SVM, for various aquaculture prediction tasks, emphasizing the importance of performance metrics like RMSE and MAE. Furthermore, we discuss the environmental and economic impacts, including quantitative case studies on cost reduction and productivity increases. This paper also addresses critical aspects of AI model reliability, interpretability (SHAP/LIME), uncertainty quantification, and failure mode analysis, advocating for robust testing protocols and human-in-the-loop systems. By addressing these challenges and exploring future opportunities, this article underscores the transformative potential of AI and IoT in advancing BFT for sustainable aquaculture practices, offering a pathway to more resilient and efficient food production.

Vacancy-ordered double perovskites have recently emerged as promising multifunctional materials for energy and spin-based technologies. In this work, we present a comprehensive first-principles investigation of the structural, electronic, magnetic, mechanical, and thermoelectric properties of Cs2MBr6 (M=Mn, Mo, Ta, Ir). The compounds are found to be thermodynamically and mechanically stable, exhibiting ductile mechanical behavior suitable for device fabrication. Electronic structure analysis reveals robust half-metallic ferromagnetism with 100% spin polarization at the Fermi level, classifying Cs2MnBr6 and Cs2TaBr6 as inverted half-metals, while Cs2MoBr6 and Cs2IrBr6 show conventional half-metallic character. Remarkably high thermoelectric performance is predicted over a wide temperature range (300-1000 K). Substantial Seebeck coefficients exceeding 400-1000 μV/K at room temperature, combined with thermally activated electrical conductivity and suppressed electronic thermal conductivity, yield near-unity and thermally stable figures of merit (ZT ≈ 0.83-0.99). The outstanding thermoelectric efficiency is directly correlated with spin-selective transport, large spin-dependent band gaps, and favorable carrier effective masses.Vacancy-ordered double perovskites have recently emerged as promising multifunctional materials for energy and spin-based technologies. In this work, we present a comprehensive first-principles investigation of the structural, electronic, magnetic, mechanical, and thermoelectric properties of Cs2MBr6 (M=Mn, Mo, Ta, Ir). The compounds are found to be thermodynamically and mechanically stable, exhibiting ductile mechanical behavior suitable for device fabrication. Electronic structure analysis reveals robust half-metallic ferromagnetism with 100% spin polarization at the Fermi level, classifying Cs2MnBr6 and Cs2TaBr6 as inverted half-metals, while Cs2MoBr6 and Cs2IrBr6 show conventional half-metallic character. Remarkably high thermoelectric performance is predicted over a wide temperature range (300-1000 K). Substantial Seebeck coefficients exceeding 400-1000 μV/K at room temperature, combined with thermally activated electrical conductivity and suppressed electronic thermal conductivity, yield near-unity and thermally stable figures of merit (ZT ≈ 0.83-0.99). The outstanding thermoelectric efficiency is directly correlated with spin-selective transport, large spin-dependent band gaps, and favorable carrier effective masses.

The green synthesis of nanoparticles using plant extracts has garnered significant interest from scientists worldwide due to its advantages over traditional chemical processes. This method is rapid, eco-friendly, non-toxic, and cost-effective. The current study focuses on preparing silver nanoparticles (AgNPs) using Ferula communis extract as a green reducing agent. During the study, various parameters were evaluated to study their effect on the shape, size, and yield of the AgNPs. The synthesized AgNPs were thoroughly characterized using multiple techniques, confirming the production of crystalline, spherical-shaped NPs, while the plant extract served as the reducing agent. GC-MS analysis was performed to identify the key phytochemicals responsible for reducing silver salts, as well as to characterize the entire phytochemical spectrum present in the F. communis extract. This analysis revealed a total of 67 compounds, with stigmasterol, pentadecanoic acid, (5 E , 9 Z )-farnesyl acetone, and pentyl decanoates being the most predominant, possibly playing crucial roles in the synthesis of AgNPs. Furthermore, the antimicrobial activity of the AgNPs against various bacterial and fungal strains was investigated. The results showed that Staphylococcus aureus exhibited the largest inhibition zone (10.05 ± 0.05 mm), followed by Escherichia coli (9.25 ± 0.05 mm), Candida albicans (8.70 ± 0.05 mm), Pseudomonas aeruginosa (8.50 ± 0.20 mm), Aspergillus niger (8.45 ± 0.00 mm), Klebsiella pneumoniae (8.15 ± 0.50 mm), and Bacillus subtilis (7.55 ± 0.20 mm). The plant extract was also tested against the same microbial pathogens; however, it only displayed an inhibitory effect against E. coli , with an inhibition zone of 6.50 ± 0.10 mm. These results indicate that the synergistic effect between AgNPs and the residual phytoconstituents on the surface of the NPs plays a significant role in enhancing the antimicrobial properties of the resulting material.

The rising demand for sustainable aquaculture necessitates innovative solutions to environmental and operational challenges. Biofloc technology (BFT) has emerged as an effective method, leveraging microbial communities to enhance water quality, reduce feed costs, and improve fish health. However, traditional BFT systems are susceptible to water quality fluctuations, demanding precise monitoring and control. This review explores the integration of Artificial Intelligence (AI) and Internet of Things (IoT) technologies in smart BFT systems, highlighting their capacity to automate processes, optimize resource utilization, and boost system performance. IoT devices facilitate real-time monitoring, while AI-driven analytics provide actionable insights for predictive management. We present a comparative analysis of AI models, such as LSTM, Random Forest, and SVM, for various aquaculture prediction tasks, emphasizing the importance of performance metrics like RMSE and MAE. Furthermore, we discuss the environmental and economic impacts, including quantitative case studies on cost reduction and productivity increases. This paper also addresses critical aspects of AI model reliability, interpretability (SHAP/LIME), uncertainty quantification, and failure mode analysis, advocating for robust testing protocols and human-in-the-loop systems. By addressing these challenges and exploring future opportunities, this article underscores the transformative potential of AI and IoT in advancing BFT for sustainable aquaculture practices, offering a pathway to more resilient and efficient food production.

In this paper, chitosan/Fe 3 O 4 /graphene oxide hydrogel was synthesized then modified with 2,6-pyridinedicarbonyl dichloride to obtain a novel composite hydrogel. The modified hydrogel formed via interfacial polymerization crosslinking of amino groups of chitosan in chitosan/Fe 3 O 4 /graphene oxide hydrogel with acyl groups of 2,6-pyridinedicarbonyl dichloride. The synthesized hydrogels were characterized using different tools such as FT-IR, XRD, TGA, VSM, BET, HR-TEM, and FE-SEM instruments. The successful modification was demonstrated through FE-SEM where sphere and rod shapes were noticed due to the presence of Fe 3 O 4 /graphene oxide. The XRD diffraction peaks of the modified hydrogel were close to that of Fe 3 O 4 without any changes in its structure. Also, there are no distinguishing XRD diffraction peaks due to the graphene oxide owing to the disorders that happen in graphene during the formation of the composite. The modified hydrogel was efficiently utilized for removing eriochrome black T and methylene blue dyes from aqueous media. The optimum pH for removing eriochrome black-T and methylene blue dyes is 2 and 8, respectively. Also, the optimum contact time and temperature for removing eriochrome black-T and methylene blue dyes are 140 min and 318 K, respectively. The maximum adsorption capacity of the modified hydrogel toward eriochrome black T and methylene blue dyes is 289.85 and 261.78 mg/g, respectively. The equilibrium and kinetic results were best fitted to the Langmuir isotherm and pseudo-second-order. The thermodynamic results confirmed that the adsorption process was spontaneous and endothermic.

To date, existing studies on the relationship between online learning and engagement during the COVID-19 pandemic have been limited to students. This paper therefore discusses the impact of children’s online learning on parents’ stress. In addition, this study also investigates parents’ demographics in relation to their stress and engagement during the COVID-19 pandemic. To do so, the study adopts a quantitative research approach using a survey questionnaire on a sample of 422 parents residing in Gulf Cooperation Council countries (GCC). The hypothesized links between components were tested and evaluated using path analysis. The study found that parents’ academic stress is a significant predictor of engagement with their children’s online learning. Furthermore, technical stress was a significant predictor of parents’ cognitive engagement but was not a significant predictor of behavioral and emotional engagement. Personal stress was only a significant predictor of behavioral engagement; financial stress was an insignificant predictor of all types of parental engagement. Finally, parents’ gender and academic qualifications were found to have a significant impact on stress. This study has added new knowledge and understanding of online learning during the COVID-19 pandemic, being the first to investigate the impact of parents’ stress on parents’ engagement with online learning during COVID-19. In conclusion, the purpose of this study was to investigate: (a) the impact of the academic, technical, financial, and personal stress parents experience in the context of children’s online learning on parents’ behavioral, emotional, and cognitive engagement with their children’s online learning; (b) whether parents’ demographic characteristics as well as the number of enrolled students in school and type of school are related to parents’ stress (four types of stress) and engagement (three types of engagement).

Our investigation explores the exclusion of two health‐risk cationic dyes (e.g., Methylene Blue (MB) and Malachite Green (MG)) using a novel hydrazone‐modified cellulose (HMC) adsorbent synthesized via a Schiff base reaction. The HMC is fully characterized by XRD, FT‐IR, SEM/EDX, BET, and TGA, confirming successful functionalization with enhanced surface area (2.489 m2 g−1) and mesoporous structure. Batch adsorption experiments optimized the key parameters, including the pH suitable for the adsorption process, the amount of adsorbent, the contact time needed for complete adsorption, and temperature. The results revealed maximum removal efficiencies of 97.5% for MG (pH 5) and 92.3% for MB (pH 8) at equilibrium (120 min). Adsorption followed the Langmuir isotherm, indicating monolayer coverage with capacities of 160.86 mg g−1 (MG) and 137.88 mg g−1 (MB). Thermodynamic analysis confirmed spontaneous, exothermic adsorption (ΔG < 0, ΔH < 0), with decreased disorder (ΔS < 0). The HMC exhibited excellent reusability, retaining high efficiency over multiple cycles. These findings highlight HMC as a low‐cost, eco‐friendly adsorbent for dye‐laden petroleum treatment, offering high selectivity and scalability for industrial applications. The porous HMC selectively captures cationic dyes (MB and MG) from contaminated water, transforming dark, dye‐laden effluent into clean water.

The Saoura Valley (southwestern Algeria) hosts14 oases that primarily depend on groundwater in an endorheic basin. The hydrogeological system is bisected by the Saoura Wadi into two distinct compartments: an active, interconnected eastern compartment (Mio–Plio–Quaternary alluvial aquifer and terraces of the Great Western Erg) and a passive, fossil western compartment (Guir Hamada and Cambro–Ordovician aquifers). In September 2024, 51 groundwater samples were collected from nine oases. Temperature ranged from 16.2 to 31.4 °C and pH ranged from 7.1 to 7.85. Total dissolved solids (TDS) varied widely (179–4480 mg/L; median of 454 mg/L), with electrical conductivity between 280 and 7000 µS/cm. Three main hydrochemical facies were identified: Ca–Mg–SO4–Cl (30%), Na–Cl–SO4 (55%), and hypersaline types in the terminal inferoflux zone. Nitrate concentrations exceeded the WHO guideline (50 mg/L) in 22% of samples, attributed to localized agricultural and domestic inputs. Geochemical evolution is controlled by evaporite dissolution (gypsum, halite), cation exchange, and evaporative concentration, with a downstream salinity gradient from freshwaters near the Great Western Erg toward hypersaline inferoflux. Comparison with historical data (1941, 1963, and earlier studies) indicates a trend of increasing salinization since the 1990s, associated with intensive borehole pumping and irrigation return flow. These findings suggest risks to the long-term sustainability of the Saoura oases.

Two novel, simple, and sensitive methods for the assay of Gliquidone (GLI) were developed and validated in various matrices, including raw material, Glurenor®® tablets, and spiked human plasma (spectrofluorometric approach only). The first method employs spectrofluorimetry to measure GLI fluorescence emission at 404 nm upon excitation at 311 nm, using a solvent mixture of phosphate buffer (pH 4), β-cyclodextrin, and methanol. The second one was colorimetric, based on GLI’s reaction with 7,7,8,8-tetracyanoquinodimethane (TCNQ) in acetone, forming a stable colored product whose absorbance was quantitatively measured at 745.5 nm. The spectrofluorometric approach showed a linear range of 0.05–0.45 µg·mL−1 with a mean recovery of 100.43 ± 0.88%, while the colorimetric method demonstrated a broader linear range (20–200 µg·mL−1) and mean recovery of 101.10 ± 1.27%. GLI and TCNQ react in a 1:1 ratio at 1.7 × 10−2 M concentrations. Both methods were successfully applied without excipient interference. Sustainability, practicality, and performance (validation) assessments (AGREE, BAGI, and RAPI) favored the spectrofluorometric method due to higher sensitivity, a broader working range, lower detection limits, and better overall practical and environmental performance. In conclusion, the spectrofluorometric approach offers high sensitivity and precision, while the colorimetric one provides a wider linear range and greater complex stability.