. In this article, we consider the problem of approximating the solution of bilevel split variational inequality problem in real Hilbert spaces. The underlying operators in the lower level problem are quasimonotone and Lipschitz continuous. The proposed algorithm is a combination of the modified subgradient extragradient and modified Tseng's extragradient methods. Compared with the existing modified subgragadient extragradient methods for solving bilevel split variational inequality problem, our suggested method does not required computation of the projections onto two half-spaces, containing the feasibility sets. The step sizes employed in our algorithm do not need the prior knowledge of the norm of the bounded linear operator and the the Lipschitz constants of the underlying operators. We obtain the strong convergence results of the new method using some mild conditions on the control parameters. The proposed method involves double inertial terms which permits it to accelerate its convergence speed. To show the advantage and potential of our method over some existing methods, we present some numerical experiments. direction.
Artificial intelligence (AI) is transforming food processing and preservation, offering significant opportunities to improve efficiency, safety, quality, and sustainability. This systematic review examines the application of AI technologies in this field, with particular emphasis on machine learning, deep learning, computer vision, and robotics. Using a PRISMA-based approach, literature published between 2015 and 2025 was analysed to identify major research trends, leading contributors, and emerging thematic areas. The review shows that AI has been widely applied in quality control and inspection, process optimisation, shelf-life prediction, intelligent packaging, predictive maintenance, and cold-chain monitoring. AI-driven systems have demonstrated strong capability in analysing complex datasets, detecting abnormalities, modelling food processes, improving decision-making, and enhancing food safety across the value chain. Bibliometric and thematic evidence further indicates that the field is rapidly expanding and increasingly interdisciplinary. However, most reported applications remain at laboratory or pilot scale, with limited industrial-scale implementation. Key barriers include data quality, model robustness, real-time integration, and limited cross-process deployment. Ultimately, these challenges underscore the need for ongoing research and development in AI technologies to realise their promise within the food business further. Future research directions encompass the amalgamation of AI with biotechnology, advancing more resilient and interpretable AI models, and formulating ethical standards for the appropriate application of AI in food processing and preservation. Therefore, this article serves as a significant resource for scholars, practitioners, and industry experts seeking to leverage the full capabilities of AI to elevate the food processing and preservation industry.
Abstract We investigate static equilibrium configurations of compact stars composed of an admixture of bosonic dark matter and dark energy within the framework of regularized four-dimensional Einstein–Gauss–Bonnet (4DEGB) gravity. The stellar interior is modeled as a two-fluid system in which self-interacting bosonic dark matter and Chaplygin-gas dark energy coexist and interact solely through gravity. Employing a scalar–tensor formulation of 4DEGB gravity, we derive the modified Tolman–Oppenheimer–Volkoff equations governing hydrostatic equilibrium and solve them numerically for a range of central densities. We systematically explore the impact of higher-curvature corrections by varying the Gauss–Bonnet coupling parameter, as well as the role of dark-matter microphysics by changing the bosonic particle mass. Our analysis shows that positive Gauss–Bonnet coupling significantly enhances the maximum supported mass and compactness of the configurations relative to the general relativistic limit, while remaining compatible with current observational constraints from GW170817, PSR J0740+6620, and HESS J1731–347. In contrast, variations in the bosonic dark-matter particle mass within the considered range induce only mild modifications to global stellar properties. The mass-central-density criterion, the relativistic adiabatic index, and the causality condition on the sound speed are all satisfied throughout the stellar interior, and stability is evaluated accordingly. These findings indicate that compact stars with dark-matter-dark-energy admixtures in regularized 4DEGB gravity are stable and feasible astrophysical configurations. They also emphasize the significant influence of higher-curvature effects on the macroscopic structure of these structures.
Octahedral iodo gallium(III) complexes, GaL1-L3(SN)I, incorporating bis-(azaaryl)amine ligands (L1–L3) with varying conformational flexibility, were synthesized and characterized by spectroscopic and elemental analyses to evaluate ligand effects on reactivity and affinity for biological targets. Iodide substitution by biologically relevant nucleophiles (guanine and thiourea), monitored spectrophotometrically, revealed ligand-dependent rates, with the fastest substitution observed for the dicationic GaL1(SN)I bearing the most compact and flexible ligand (L1), compared to the more rigid monocationic L2 and L3 analogues. UV–Visible studies of interactions with bovine serum albumin and calf thymus DNA indicated moderate to strong binding (Kb ≈ 104 M⁻1), with affinities decreasing in the order GaL1(SN)I > GaL2(SN)I > GaL3(SN)I. Competitive binding assays, supported by molecular docking, suggested bimodal binding modes involving moderate groove binding and partial intercalation. Density functional theory calculations demonstrated that trends in structural parameters and electronic reactivity descriptors were consistent with experimentally observed iodide substitution rates and biomolecular binding affinities. Cytotoxicity evaluation of L1–L3 and GaL1-L3(SN)I against selected human cancer and non-malignant cell lines demonstrated moderate antiproliferative activity. Notably, L1 and GaL1(SN)I exhibited enhanced inhibition comparable to cisplatin against HeLa cervical cancer cells, highlighting their therapeutic potential. The data provided insights into the structural-activity relationships governing the reactivity and anticancer activity of Ga(III) complexes bearing N∧N∧N and thiosemicarbazide chelators.
