Developing a multi-criteria sustainable credit score system using fuzzy BWM and fuzzy TOPSIS

Environment, Development and Sustainability - Sustainability has emerged as a dominating paradigm across global institutions as a critical component for their prospects. Organisations all across...     

Biodegradation of pretreated polyethylene film by Pseudomonas aeruginosa AMB-CD-1

A comparative study evaluated the acid, alkali, and heat-treated polyethylene biodegradation efficiency of Pseudomonas aeruginosa AMB-CD-1. The polyethylene (PE) pieces were separately treated with heat (50°C), acid (1N HCl), and alkali (1N NaOH) and then washed with water before use. All the treated samples were analyzed through thermogravimetric analysis. In addition, weight and temperature changes during the decomposition reactions were also measured and determined. In these treatments, the PE films of heat-treated and acid-treated low-density polyethylene (LDPE) indicated more significant weight loss at 120°C (48.99% and 40.75%, respectively) as compared to their control or untreated PE and alkali-treated LDPE (21.84% and 24.68%, respectively). A biodegradation assay was then conducted with treated and untreated LDPE films with P. aeruginosa AMB-CD-1 strain. Fourier transform infrared spectroscopy analysis revealed that the heat or acid-pretreated samples with isolate AMB-CD-1 displayed peaks at 2922.84, 2923.97, and 1450.31, 874.22 cm⁻¹ for C–H stretching deformation vibration, CH₂ scissoring vibration, –CHO stretching, and strong alkyl structure, respectively. Furthermore, the new peaks with a significant difference at 2500–2000 cm⁻¹ (O═C═O, O–H stretching vibration: carboxylic acid) and 1500–1000 cm⁻¹ (–CHO and C═O stretching) were noticed in the infrared spectral range of LDPE degradation. Modifications in the functional group provided evidence that biodegradation had impacted the chemical structure of the LDPE film. Additionally, it was demonstrated that pretreating LDPE films with heat or acid could speed up their biodegradation.     

Markov regression model for analyzing big data to predict trajectories of repeated categorical outcomes: an application to $$\hbox {PM}_{2.5}$$ PM 2.5 air pollution data

Environmental and Ecological Statistics - Fine particulate matter ( $$\text{ PM}_{2.5}$$ ), tiny particles in the air, is air contamination that negatively impacts the environment and human health...