A new methodology involving the use of Bovine Serum Albumin (BSA) as a probe and liquid crystal (LC) as a signal reporter for the detection of heavy metal ions in water at neutral pH was developed. BSA acted as a multi-dentate ligand for the detection of multiple metal ions. The LC sensor was fabricated by immobilizing 3 µg mL−1 BSA solution on dimethyloctadecyl-[3-(trimethoxysilyl)propyl]ammonium chloride (DMOAP)-coated glass slides. In the absence of heavy metal ions, a dark optical image was observed, while in their presence, a dark optical image turned to bright. The optical response was characterized by using a polarized optical microscope (POM). The BSA based LC sensor selectively detected toxic metal ions as compared to s block metal ions and ammonium ions in water. Moreover, the limit of detection was found to be very low (i.e., 1 nM) for the developed new biosensor in comparison to reported biosensors.

A new sensing methodology has been developed for the detection of Cu(II) ions in water by using biotinylated oligopeptide as a probe whereas liquid crystal (LC) and fluorophore were used as signal reporters. The multidentate oligopeptide ligand was used to investigate Cu(II) as a model metal ion. The alkyl terminal group of the coated dimethyl octadecyl [3-(trimethoxysilyl) propyl] ammonium chloride (DMOAP) was first activated to aldehydic functional group by UV irridiation for 50 seconds. The activated aldehydic functional group was covalent linked with biotinylated oligopeptide via thiolation reaction. As fabricated oligopeptide probe spotted with metal ions was incubated for 30 minutes and followed by tagging with streptavidin-cyanine-3 as a fluorophore. Polarized optical microscopy (POM) and fluorescence microarray scanner (FMS) were used as characterization techniques. The developed sensing methodology results were reproducible for different concentrations of model Cu (II) ions as confirmed from the characterization techniques. Our methodology highlighted the detection of Cu(II) ions in water as low as 100 nM, and is the lowest concentration so far reported.

The argumentative approach, the probability approach, and the story model are the three normative frameworks to reasoning with judicial evidence. The story model describes that judges reach the final conclusion by going through three different stages. The model also offered certainty principles, including evidential coverage, coherence, consistency, plausibility, and structural completeness to evaluate the stories. Different researchers have criticized the story model by pointing out that the model does not elaborate the meaning of evidential coverage and plausibility. Additionally, the story model has also been charged on the ground that it does not guide how to evaluate evidential coverage or plausibility of a story and how to select the best story when judges make more than one story. The present study demonstrates that these shortcomings may be overcome by using anchored narrative theory, causal abductive reasoning, story schemes, critical questions, and principles of inference to the best explanation.

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