The beet armyworm (BAW), Spodoptera exigua (Lepidoptera: Noctuidae) is a highly destructive pest of vegetables and field crops. Management of beet armyworm primarily relies on synthetic pesticides, which is threatening the beneficial community and environment. Most importantly, the BAW developed resistance to synthetic pesticides with making it difficult to manage. Therefore, alternative and environment-friendly pest management tactics are urgently required. The use of pesticidal plant extracts provides an effective way for a sustainable pest management program. To evaluate the use of pesticidal plant extracts against BAW, we selected six plant species (Lantana camara, Aloe vera, Azadirachta indica, Cymbopogon citratus, Nicotiana tabacum ,

     In this work, combining acyclovir with ciprofloxacin (CCP), a new Schiff base and its metal complexes with iron (III), manganese (II), copper (II), zinc (II), and calcium (II) ions are synthesized and structurally characterized by XRD, SEM, ¹H NMR, ¹³C NMR, FT-IR, and UV-Visible spectral techniques. Furthermore, molecular docking studies were carried out, and the complexes were tested to resolve any potential hang-ups in opposition to the Herpes virus and DFT calculation studies. In addition, the metal complexes and ligand were screened against antibacterial strains of one gram-positive bacteria (Staphylococcus aureus) and three gram-negative bacteria (

In this research , we study the inverse Gompertz distribution (IG) and estimate the  survival function of the distribution , and the survival function was evaluated using three methods (the Maximum likelihood, least squares, and percentiles estimators) and choosing the best method estimation ,as it was found that the best method for estimating the survival function is the squares-least method because it has the lowest IMSE and for all sample sizes

In this research , we study the inverse Gompertz distribution (IG) and estimate the  survival function of the distribution , and the survival function was evaluated using three methods (the Maximum likelihood, least squares, and percentiles estimators) and choosing the best method estimation ,as it was found that the best method for estimating the survival function is the squares-least method because it has the lowest IMSE and for all sample sizes