In this paper, we propose an effective method for emergent leader detection in meeting environments which is based on nonverbal visual features. Identifying emergent leader is an important issue for organizations. It is also a wellinvestigated topic in social psychology while a relatively new problem in social signal processing (SSP). The effectiveness of nonverbal features have been shown by many previous SSP studies. In general, the nonverbal video-based features were not more effective compared to audio-based features although, their fusion generally improved the overall performance. However, in absence of audio sensors, the accurate detection of social interactions is still crucial. Motivating from that, we propose novel, automatically extracted, nonverbal features to identify the emergent leadership. The extracted nonverbal features were based on automatically estimated visual focus of attention which is based on head pose. The evaluation of the proposed method and the defined features were realized using a new dataset which is firstly introduced in this paper including its design, collection and annotation. The effectiveness of the features and the method were also compared with many state of the art features and methods.

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Photochromic spiropyran-doped silk fibroin poly(ethylene oxide) nanofibers which combine the attractive properties and biocompatibility of silk with the photocontrollable and reversible optical, mechanical, and chemical response of the spiropyran dopants are herein presented. As proved, the reversible variation of the absorption and emission signals of the mats and of their Young's modulus upon alternate UV and visible light irradiation is ascribed to the reversible photoconversion of the spiropyran form to its polar merocyanine counterpart. Most importantly, the interactions of the merocyanine molecules with acidic vapors as well as with heavy metal ions dispersed in solution produce analyte-specific spectral changes in the emission profile of the composite, accompanied by a characteristic chromic variation. Because of the high surface-to-volume ratio of the nanofibrous network, such interactions are fast, thus enabling both an optical and a visual detection in a 30-60 s time scale. The sensing platform can be easily regenerated for more than 20 and 3 cycles upon acid or ion depletion, respectively. Overall, the photocontrolled properties of the silk composites combined with a straightforward preparation method render them suitable as porous materials and scaffolds with tunable compliance and reusable nanoprobes for real time optical detection in biomedical, environmental, and industrial applications.

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Here, the development of highly porous colorimetric indicators that are able to rapidly sense the presence of amine vapors is presented. Specifically, porous, curcumin-loaded polycaprolactone fibers are formed by electrospinning through non-solvent-induced phase separation. In comparison to the non-porous fibers, the developed system shows significantly higher sensitivity and responsivity to the presence of dimethylamine vapors, with a distinct color change at very low vapor concentrations (2.33 ppm compared to 9.26 ppm) within the first 5 s of exposure. Indeed, CIELAB analysis proves that the induced color changes can be easily perceived visually, as the differences between the initial and the final color of the indicator after its interaction with the modified environment are well above the limit for visual perception, even by inexperienced users. Furthermore, the color changes are reversible, enabling the use of the same indicator several times, making it, thus, a sustainable colorimetric indicator system that can be used in applications where the rapid detection of low concentration of alkaline vapors is necessary.

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