Human Error Management in Aviation Maintenance using Hybrid FMEA with a Novel Fuzzy Approach

Human errors significantly contribute to aviation accidents during aircraft maintenance. Therefore, managing human errors becomes a critical aspect of aviation maintenance. The existing literature has extensively analysed human errors. However, there is a gap in accurately identifying and prioritising critical human errors and effectively managing them to reduce incidents and accidents. This research work proposes a novel fuzzy approach for human error analysis using a hybrid FMEA with Fuzzy AHP-TOPSIS. We identified inadequate maintenance processes, attention/memory, inadequate documentation, inadequate supervision, judgement/decision-making, and knowledge/rule base as some of the critical human errors in aircraft maintenance. Based on these findings, we recommended practically implementable solutions at the organisational, workspace, and individual levels to mitigate human errors in aircraft maintenance

Validated HPTLC Method for Simultaneous Determination of Quinapril Hydrochloride and Hydrochlorothiazide in a Tablet Dosage Form

Quinapril hydrochloride and hydrochlorothiazide were simultaneously determined by HPTLC in pharmaceutical formulations. The drugs were separated on silica gel 60 F254 plates using suitable combination of solvents as mobile phase. The validation parameters, tested in accordance with the requirements of ICH guidelines, prove the suitability of methods

Design, docking, MD simulation and in-silco ADMET prediction studies of novel indole-based benzamides targeting estrogen receptor alfa positive for effective breast cancer therapy

Breast cancer is one of the most common malignancies in women, afflicting millions of lives each year. Our current study suggests that the development of the most promising 7-substituted -1-(4-(piperidine-1-yl methoxy)benzyl)-1H-indole-3-carboxamide derivatives results in potent anticancer agents through in-silico investigations. The molecular docking was performed against estrogen receptor alpha (ER-α) positive (PDB ID: 3UUD) of breast cancer cells to anticipate the binding modes of the designed compounds and the likely mode of action. The interactions between the ligands and amino acid residues were thoroughly elucidated. The stability of the docked protein-ligand complexes was further confirmed by 100 ns molecular simulations methods. From in-silico studies, indole-based benzamides exhibited satisfactory physicochemical, drug-likeness and toxicity properties. To conclude, the most promising substituted benzamide analogs on the indole ring could serve as a possible modulator against ER-α positive breast cancer

Design, docking, MD simulation and in-silco ADMET prediction studies of novel indole-based benzamides targeting estrogen receptor alfa positive for effective breast cancer therapy

Breast cancer is one of the most common malignancies in women, afflicting millions of lives each year. Our current study suggests that the development of the most promising 7-substituted -1-(4-(piperidine-1-yl methoxy)benzyl)-1H-indole-3-carboxamide derivatives results in potent anticancer agents through in-silico investigations. The molecular docking was performed against estrogen receptor alpha (ER-α) positive (PDB ID: 3UUD) of breast cancer cells to anticipate the binding modes of the designed compounds and the likely mode of action. The interactions between the ligands and amino acid residues were thoroughly elucidated. The stability of the docked protein-ligand complexes was further confirmed by 100 ns molecular simulations methods. From in-silico studies, indole-based benzamides exhibited satisfactory physicochemical, drug-likeness and toxicity properties. To conclude, the most promising substituted benzamide analogs on the indole ring could serve as a possible modulator against ER-α positive breast cancer