Artificial intelligence and machine learning algorithms in the detection of heavy metals in water and wastewater: Methodological and ethical challenges.

Heavy metals (HMs) enter waterbodies through various means, which, when exceeding a threshold limit, cause toxic effects both on the environment and in humans upon entering their systems. Recent times have seen an increase in such HM influx incident rates. This requires an instant response in this regard to review the challenges in the available classical methods for HM detection and removal.

Efficient DNA-ligand interaction framework using fuzzy C-means clustering based glowworm swarm optimization (FCMGSO) method.

Assessment of DNA and ligand interaction is a great challenge to the medical researchers and drug industries since the accurate mapping of DNA and ligand plays an important role in associating drugs for suitable diseases. The primary objective of this research work is to develop an efficient model for predicting the best DNA and Ligand mapping. In this research work, 500 instances of DNA and drugs used for cancer and non-cancer diseases from the National Centre for Biotechnology Information (NCBI) were considered for analysis.

Have a Look at the Three Dimensional View of T-Statistics! - Isn't It Cute Ginger?

This article visualizes the three-dimensional view of t-statistics for the lip movement experiment. It also visualizes the t-contrast image. These three dimensional views help the radiologist to understand the volume of activations in the brain.

On experimenting with functional magnetic resonance imaging of lip movement.

The analysis of functional magnetic resonance imaging (fMRI) time-series data can provide information on task-related activities, functional/effective connectivity among regions and the influences of behavioral/physiologic states on connectivity. This paper illustrates the importance of the neurobiological constraints involved in using statistical parametric mapping (SPM) through Matlab simulation and thus helping the radiologist to interpret the results better. This paper also presents the results and inferences from neuroimaging data of the lip movement experiment using statistical parametric mapping (SPM).

On identifying micro level error in realignment phase of statistical parametric mapping.

Statistical parametric map of an fMRI time series is used to identify the sensor, motor and cognitive tasks in the specific regions of the brain. This process of obtaining statistical parametric map includes realignment of the slices in various volume acquired during the scanning. This article presents the identification of micro level (10(-6)) error in the realignment phase.