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Torrefied biomass is a vital green energy source with applications in circular economies, addressing agricultural residue and rising energy demands. In this study, ML models were used to predict durability (%) and mass loss (%). Firstly, data was collected and preprocessed, and its distribution and correlation were analyzed. Gaussian Process Regression (GPR) and Ensemble Learning Trees (ELT) were then trained and tested on 80 % and 20 % of the data, respectively. Both machine learning models underwent optimization through Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) for feature selection and hyperparameter tuning. GPR-PSO demonstrates excellent accuracy in predicting durability (%), achieving a training R2 score of 0.9469 and an RMSE value of 0.0785. GPR-GA exhibits exceptional performance in predicting mass loss (%), achieving a training R2 value of 1 and an RMSE value of 9.7373e-05. The temperature and duration during torrefaction are crucial variables that are in line with the conclusions drawn from previous studies. GPR and ELT models effectively predict and optimize torrefied biomass quality, leading to enhanced energy density, mechanical properties, grindability, and storage stability. Additionally, they contribute to sustainable agriculture by reducing carbon emissions, improving cost-effectiveness, and aiding in the design and development of pelletizers. This optimization not only increases energy density and grindability but also enhances nutrient delivery efficiency, water retention, and reduces the carbon footprint. Consequently, these outcomes support biodiversity and promote sustainable agricultural, ecosystem, and environmental practices.

Objective: To compare the association of vitamin B12 deficiency and metformin use in patients presenting with type II diabetes mellitus. Study Design: Case control study. Place and Duration of Study: Department of Medicine, Military Hospital Rawalpindi from Apr 2017 to Sep 2017. Methodology: All patients who fulfilled the inclusion criteria and visited OPD of department of Medicine Military Hospital Rawalpindi, were included in the study. After approval from the ethical review committee, informed written consent was taken from patients. The patients were divided into two groups group A (metformin use) & B (without metformin use). Outcome was checked by comparing both the groups for vitamin B12 deficiency. Results: Two hundred and eighty patients with diabetes mellitus were included. One hundred and seventy one (61.07%) were males and 109 (38.93%) were females, with the mean age of 59.52 ± 12.441. Vitamin B12 deficiency in group I was seen in 30 (10.71%) and in 9 patients (3.21%) in group II (OR >1). Conclusion: In conclusion, our study indicates that patients with type 2 diabetes mellitus treated with metformin should be screened for vitamin B12 deficiency, especially with longer durations of treatment.