In an aim to harvest UV-near-visible (360-440 nm) photons as well as to increase the morphology in the bulk heterojunction solar cells, we report herein the strategic design, synthesis, and characterization of a novel excited-state intramolecular proton-transfer dye, 3-hydroxy-2-(5-(5-(5-(3-hydroxy-4-oxo-4H-chromen-2-yl)thiophen-2-yl)thiophen-2-yl)thiophen-2-yl)-4H-chromen-4-one (FT), which bears two key functional groups, namely 3-hydroxychromone chromophore and trithiophene backbone and is then exploited into the blends of regioregular poly(3-hexylthiophene) (RR-P3HT) and phenyl-C(61)-butyric acid methyl ester (PCBM). FT acts as an excellent UV-near visible absorber, which then undergoes excited-state intramolecular proton transfer, giving rise to an orange-red proton-transfer emission that was reabsorbed by P3HT via a Forster type of energy transfer. Introduction of FT to P3HT/PCBM blend films also improves the morphology of phase separated structure, in particular, enhances the interaction of P3HT chains and the hole mobility. In this work, under the optimized condition of P3HT: PCBM:FT of 15:9:2 in weight ratio, the best performance of the device B-FT2 revealed consistent enhancements in the efficiency (eta) 4.28% and short-circuit current (J(sc)) 12.53 mAcm(-2), which are higher than that (3.68% and 10.28 mAcm(-2)) of the best performance of the control device B (P3HT:PCBM 15:9 in weight ratio) by 16 and 22%, respectively.
In this paper, we propose WearVis, a generic framework for human-machine hybrid recognition based on wearable visual computing. The chief objective of WearViS is to help human complete the complex recognition task and let user flexibly interact with the visual assistant system. The framework process can be described in four steps. First, the behavior of human’s attention drivers WearVis search region of interest. Second, WearVis selects the most abundant features in image sequence. Then, WearVis detects and localizes task-related interest objects. Finally, WearVis select the natural interaction strategy according to the priority of recognition task. We describe the goals and architecture of WearViS, a prototype implementation that validates its design.
Obesity and dysphagia are of potential and direct serious harm to the human body health. A commonly used method is controlling food intake to avoid obesity or determining if dysphagia exists by monitoring the swallow . This paper proposes a swallow detecting principle based on nanometer materials sensor, and implements a wearable detecting system with advantage of improved DTW algorithm. The system efficiently detects and faithfully identifies swallowing. In addition, it reduces the demand for hardware computing power. The system meets the features of a wearable system, such as soft and comfortable, lightweight, portable, and noninvasive.
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