The present study investigates the phytochemical composition and biopesticidal efficacy of bark extracts from four medicinal plants—Terminalia arjuna, Neltuma juliflora, Saraca asoca, and Cinnamomum verum—against the stored-grain pest Tribolium castaneum (Herbst). Bark samples were taxonomically authenticated, extracted using standardized protocols, and subjected to qualitative phytochemical screening, revealing abundant alkaloids, flavonoids, terpenoids, phenolics, and other secondary metabolites. GC–MS profiling, supported by retention time, fragmentation patterns, and library match scores, identified several bioactive constituents, with T. arjuna and N. juliflora displaying the highest diversity and peak abundance. Repellency and toxicity bioassays, conducted with three independent replicates, demonstrated a significant concentration- and time-dependent response. One-way ANOVA followed by LSD post-hoc analysis confirmed statistically significant differences among treatments, while probit analysis provided LC₅₀ values with 95% confidence intervals, establishing T. arjuna as the most potent extract. In-silico molecular docking further highlighted compounds such as ellagic acid, catechin, quercetin, and luteolin as strong binders to key insect enzymatic targets, showing interaction energies comparable to or exceeding those of the synthetic insecticide malathion. Collectively, the integrated chemical, biological, and computational evidence underscores the promise of T. arjuna and N. juliflora bark extracts as effective, biodegradable, and environmentally safe biopesticide candidates. The findings support further purification, SAR-guided optimization, and field-scale validation of the active compounds for sustainable pest-management applications.

A series of novel substituted benzaldehyde derivatives of 4-Amino-7H-pyrrolo[2,3-d]pyrimidine (4A7HPP), designated as compounds 1a–1d, were synthesized under microwave irradiation, providing a safe, cost-effective, and efficient alternative to conventional procedures. The condensation of 4A7HPP with hydroxybenzaldehyde analogues in DMF afforded the corresponding imine derivatives in high yields (71.54–85.02%) with reduced reaction time and solvent consumption. The synthesized compounds were characterized by ¹H NMR, FT-IR, UV–Vis spectroscopy, and elemental analysis, confirming the presence of characteristic azomethine (–CH=N–) and aromatic proton signals. The compounds exhibited significant antibacterial activity against Staphylococcus aureus, Bacillus subtilis, Escherichia coli, and Pseudomonas aeruginosa (MIC: 7.5–28 mm), surpassing the standard drug streptomycin. Notably, antifungal evaluation against Candida albicans and Saccharomyces cerevisiae demonstrated activity up to 2.5 times greater than fluconazole. Molecular docking studies performed against target proteins—S. aureus DHFR (PDB ID: 2W9H), E. coli DHFR (PDB ID: 1RX2), and C. albicans ERG11 (PDB ID: 5TZ1)—revealed stronger binding affinities for compounds 1b and 1d (−8.3 to −9.0 kcal mol⁻¹) compared with reference ligands, supported by low RMSD values (0.655–0.785 Å). Brine shrimp lethality bioassay indicated moderate cytotoxicity (LD₅₀: 3.50–8.50 × 10⁻⁴ M). ADME analysis suggested favorable pharmacokinetic profiles, high gastrointestinal absorption, and compliance with Lipinski’s rule of five. These results highlight compounds 1a–1d as potential lead molecules for the development of new antimicrobial and antifungal agents, warranting further biological and pharmacological investigations.

Girth-regular graphs with equal girth, regular degree and chromatic index are studied for the determination of 1-factorizations with each 1-factor intersecting every girth cycle. Applications to hamiltonian decomposability and to 3-dimensional geometry are given.Applications are suggested for priority assignment and optimization problems.

This paper initiates a study on a new optimization problem with regards to graph completion. A new iterative procedure called Marcello’s completion of a graph is defined. For graph \(G\) of order \(n\) the graphs, \(G_1,G_2,\dots,G_k\) are obtained in accordance to the Marcello rule. If for smallest \(k\) the resultant graph \(G_k \cong K_n\) then the Marcello number of a graph \(G\) denoted by \(\varpi(G)\) is equal to \(\varpi(G) = k\). By convention \(\varpi(K_n) = 0\), \(n \geq 1\). Certain introductory results are presented.