An electrochemical sensor based on an amino-functionalized iron NH2-MIL-101(Fe) metal-organic framework (MOF)/Pd nanoparticles (NPs) composite-modified screen-printed elec­trode (SPE) is prepared for the simultaneous determination of norepinephrine (NEPI) and acetaminophen (ACP). The NH2-MIL-101(Fe) MOF/Pd NPs/SPE electrochemical sensor shows a significant enhancement in the response peak current of NEPI, as compared to bare SPE. This suggests that the unique features of NH2-MIL-101(Fe) MOF/Pd NPs composite-mo­di­fied SPE improve the electro­catalytic oxidation of NEPI. Such a synergistic effect bet­ween NH2-MIL-101(Fe) MOF and Pd NPs results in a significant enhancement in the res­pon­se, where the MOF's high surface area co

Facial emotion recognition finds many real applications in the daily life like human robot interaction, eLearning, healthcare, customer services etc. The task of facial emotion recognition is not easy due to the difficulty in determining the effective feature set that can recognize the emotion conveyed within the facial expression accurately. Graph mining techniques are exploited in this paper to solve facial emotion recognition problem. After determining positions of facial landmarks in face region, twelve different graphs are constructed using four facial components to serve as a source for sub-graphs mining stage using gSpan algorithm. In each group, the discriminative set of sub-graphs are selected and fed to Deep Belief Network (DBN) f