Efficient brain tumor grade classification using ensemble deep learning models.

Detecting brain tumors early on is critical for effective treatment and life-saving efforts. The analysis of the brain with MRI scans is fundamental to the diagnosis because it contains detailed structural views of the brain, which is vital in identifying any of its abnormalities. The other option of performing an invasive biopsy is very painful and uncomfortable, which is not the case with MRI as it is free from surgically invasive margins and pieces of equipment.

Deep learning infused SIRVD model for COVID-19 prediction: XGBoost-SIRVD-LSTM approach.

The global impact of the ongoing COVID-19 pandemic, while somewhat contained, remains a critical challenge that has tested the resilience of humanity. Accurate and timely prediction of COVID-19 transmission dynamics and future trends is essential for informed decision-making in public health. Deep learning and mathematical models have emerged as promising tools, yet concerns regarding accuracy persist.

Robust brain tumor classification by fusion of deep learning and channel-wise attention mode approach.

Diagnosing brain tumors is a complex and time-consuming process that relies heavily on radiologists' expertise and interpretive skills. However, the advent of deep learning methodologies has revolutionized the field, offering more accurate and efficient assessments. Attention-based models have emerged as promising tools, focusing on salient features within complex medical imaging data.

Antimicrobial effect of herbal and conventional root canal endodontic irrigants against persistent pathogens.

Evaluation and comparison of natural products like triphala, eucalyptus and carvacol with conventional root canal irrigant such as sodium hypochlorite (NaOCL) and Chlorhexidine against persistent root canal pathogens like is of interest. Samples were taken both before irrigation as well as after irrigation. CFU was counted after the plates had been incubated overnight at temperature of 37°C overnight.

Mixed polyaromatic hydrocarbon degradation by halotolerant bacterial strains from marine environment and its metabolic pathway.

Accidents involving diesel oil spills are prevalent in sea- and coastal regions. Polycyclic aromatic hydrocarbons (PAHs) can be adsorbed in soil and constitute a persistent contaminant due to their poor water solubility and complex breakdown. PAHs pollution is a pervasive environmental concern that poses serious risks to human life and ecosystems.

Molecular dynamics study of in silico mutations in the auto-inhibitory loop of human endothelial nitric oxide synthase FMN sub-domain.

Structural flexibility of the peptide linker connecting two domains is essential for the functioning of multi-domain complex. Nitric oxide synthase (NOS) isoforms contain the oxygenase and the reductase domains connected by calmodulin binding linker (CBL) region. Additionally, the endothelial NOS (eNOS) isoform contain an auto-inhibitory loop (AI) in the FMN reductase sub-domain which represses the inter-domain electron transfer process.

Study of poroscopy among South Indian population.

Poroscopy is the term applied to a specialized study of pore structure found on papillary ridges of skin as a means of identification. It comes under level 3 detail of identification and hence is more reliable and accurate. The goal of this study is to estimate the importance of poroscopy for identification of individuals and to determine the gender based on frequency, type, and shape of pores.

Gender differentiation by finger ridge count among South Indian population.

The goal of this study is to determine the gender based on finger ridge count within a well-defined area. Rolled fingerprints were taken from 550 subjects (275 men and 275 women) belonging to South Indian population all within the age range of 18-65 years. Results show that women have a significantly higher ridge count than men.