To discriminate among the 14 trivalent lanthanide ions, curcumin, a naturally occurring, nontoxic, off-the-shelf, commercially available compound containing a single fluorophore, was chosen as a probe in the water media at pH 6.8 and pH 8.2. By measuring the emission and absorption spectra of the probe, under the different pH conditions, and by performing linear discriminant analysis on the data, 14 Ln 3+ ions were discriminated. Additionally, an easy tool for the nonspecialists was developed with easily available household substances, using a smartphone app, which added an extra advantage to this single probe. This probe possesses advantageous features in terms of low-cost and instant on-site detection of the lanthanide ions.

Decades of research on collective decision making has claimed that aggregated judgment of multiple individuals is more accurate than expert individual judgement. A longstanding problem in this regard has been to determine how decisions of individuals can be combined to form intelligent group decisions. Our study consisted of a random target detection task in natural scenes, where human subjects (18 subjects, 7 female) detected the presence or absence of a random target as indicated by the cue word displayed prior to stimulus display. Concurrently the neural activities (EEG signals) were recorded. A separate behavioural experiment was performed by different subjects (20 subjects, 11 female) on the same set of images to categorize the tasks according to their difficulty levels. We demonstrate that the weighted average of individual decision confidence/neural decision variables produces significantly better performance than the frequently used majority pooling algorithm. Further, the classification error rates from individual judgement were found to increase with increasing task difficulty. This error could be significantly reduced upon combining the individual decisions using group aggregation rules. Using statistical tests, we show that combining all available participants is unnecessary to achieve minimum classification error rate. We also try to explore if group aggregation benefits depend on the correlation between the individual judgements of the group and our results seem to suggest that reduced inter-subject correlation can improve collective decision making for a fixed difficulty level.

Understanding how individuals utilize social information while making perceptual decisions and how it affects their decision confidence is crucial in a society. To date, very little has been known about perceptual decision-making in humans and the associated neural mediators under social influence. The present study provides empirical evidence of how individuals are manipulated by others' decisions while performing a face/car identification task. Subjects were significantly influenced by what they perceived as the decisions of other subjects, while the cues, in reality, were manipulated independently from the stimulus. Subjects, in general, tend to increase their decision confidence when their individual decision and the cues coincide, while their confidence decreases when cues conflict with their individual judgments, often leading to reversal of decision. Using a novel statistical model, it was possible to rank subjects based on their propensity to be influenced by cues. This was subsequently corroborated by an analysis of their neural data. Neural time series analysis revealed no significant difference in decision-making using social cues in the early stages, unlike neural expectation studies with predictive cues. Multivariate pattern analysis of neural data alludes to a potential role of the frontal cortex in the later stages of visual processing, which appeared to code the effect of cues on perceptual decision-making. Specifically, the medial frontal cortex seems to play a role in facilitating perceptual decision preceded by conflicting cues.

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