Career Point University

In this study of Fe2-xCoxMnAl Heusler alloys, we analysed several key properties such as electronic, magnetic and optical properties including the formation energy, electronic energy band gap, magnetic moment and spin polarization (SP). These properties were studied to understand the half-metallic stability as the lattice parameter changed. The alloys consistently maintained the total magnetic moments (MTotal) predicted by the Slater-Pauling rule (SPR), with values of 2.0 μB for x = 0.0, 2.5 μB for x = 0.5, 3.0 μB for x = 1.0, 3.5 μB for x = 1.5, and 4.0 μB for x = 2.0, across a wide range of lattice variations. Value of SP was observed 100

Due to the exponential growth of data, there is a demand for knowledge that can be utilized derived from massive and massively varied datasets in diverse domains. This paper presents an Optimized Hybrid Framework which combines benefits of data mining techniques and contemporary machine learning algorithms to improve efficiency, effectiveness of information extraction. The methodology is based on two hybrid ensembles of unsupervised learning system. a combination of the Supervised Learning algorithm: Logistig regression; K-nearest Neighbors; Decision tree; Random Forest; Ad boosting; Ligh Gradient Boosting Machine and eXtreme Gradient Boosting. The former is developed with traditional classifiers, while the latter is constructed by gradient boosted automatic learning models. These normalization, feature scaling and encoding are parts of the general preparation pipeline that assures that you correctly prepare your data. Cross-validation and hyperparameter tuning are used to speed up training, avoid its overfitting, aid generalization, and enhance a model’s performance. Standard measures, accuracy, precision, recall, F1 score as well as AUC-ROC are employed to assess the performance and computational efficiency. Experimental Results The experiments show that the hybrid models can significantly improve classification accuracy as well as robustness compared to single classifiers on many datasets. At the single model level, accuracies went from 82.5

This study reports the hydrothermal synthesis of silver-anchored binary (PNBC–Ag/TiO₂, PNBC–Ag/Mg(OH)₂) and ternary (PNBC–Ag/TiO₂/Mg(OH)₂) nanocomposites using activated biochar (PNBC) derived from dead pine needles as a sustainable support. Structural, optical and surface analyses using XRD, FTIR, XPS, FESEM/HRTEM, and UV–Vis DRS confirmed the successful integration of Ag, TiO₂, and Mg(OH)₂ within the biochar matrix, producing nanocrystalline composites with improved light-absorption properties. The ternary nanocomposite demonstrated superior photocatalytic performance, achieving 98.4

Euphorbia royleana (Euphorbiaceae) is an important succulent species and commonly known as Royle's spurge. It is used to treat inflammation, paralysis, and brain-related problems. The literature revealed that E. royleana was not well explored for phytochemical diversity and health benefits. Therefore, the current study was focused on investigating solvent-dependent chemical diversity and bioactive properties across stems, leaves, and reproductive tissue (flowers and seeds). Ethanol, 50% ethanol, and water extracts were prepared, in which the water extract of leaves showed the highest extraction efficiency (16.97%). Total phenolic content was found higher in 50% ethanol extract (112.65 ± 3.27 mg GAE/g), while flavonoid content was found higher in ethanol extract (217.31 ± 13.55 mg RE/g) of reproductive parts. Further, UPLC-PDA-based targeted polyphenol profiling showed gallic acid (23.658 ± mg/g) as the most abundant polyphenol among different parts. UHPLC-QTOF-IMS-based non-targeted metabolite profiling revealed 74 metabolites (terpenoids, flavonoid glycosides, and phenylpropanoids). Multivariate statistical analysis of identified metabolites further suggested clear organ- and solvent-specific variations. Moreover, antioxidant and tyrosinase inhibition activities were performed, and the highest activity was found in the ethanol extract of reproductive tissues. The current study provides new insights into the chemical diversity of E. royleana, highlighting its ecological significance and chemotaxonomic value within Euphorbiaceae.

The present study aimed to prepare and characterize Harmaline-loaded silver nanoparticles (H-AgNPs) using a green synthesis approach. Harmaline, a biologically active β-carboline alkaloid obtained from Peganum harmala, was utilized as both reducing and stabilizing agent for the synthesis of silver nanoparticles. The formation of nanoparticles was initially confirmed by visual color change from pale yellow to dark brown due to surface plasmon resonance. The synthesized nanoparticles were characterized using UV–Visible spectroscopy, Fourier Transform Infrared Spectroscopy (FTIR), X-ray Diffraction (XRD), and Scanning Electron Microscopy (SEM). UV–Visible analysis showed a characteristic surface plasmon resonance peak at 450 nm, confirming nanoparticle formation. FTIR analysis demonstrated the involvement of hydroxyl, amine, and aromatic functional groups of Harmaline in nanoparticle stabilization. XRD studies confirmed the crystalline nature and face-centered cubic structure of silver nanoparticles. SEM analysis revealed predominantly spherical nanoparticles with particle size ranging from 20–60 nm and minimal aggregation. The synthesized H-AgNPs exhibited good stability and controlled morphology. Overall, the study demonstrated that Harmaline-mediated silver nanoparticles may serve as a promising nanocarrier system with potential pharmaceutical and biomedical applications.