2D perovskite stabilized phase-pure formamidinium perovskite solar cells.

Compositional engineering has been used to overcome difficulties in fabricating high-quality phase-pure formamidinium perovskite films together with its ambient instability. However, this comes alongside an undesirable increase in bandgap that sacrifices the device photocurrent. Here we report the fabrication of phase-pure formamidinium-lead tri-iodide perovskite films with excellent optoelectronic quality and stability. Incorporation of 1.67 mol% of 2D phenylethylammonium lead iodide into the precursor solution enables the formation of phase-pure formamidinium perovskite with an order of magnitude enhanced photoluminescence lifetime. The 2D perovskite spontaneously forms at grain boundaries to protect the formamidinium perovskite from moisture and suppress ion migration. A stabilized power conversion efficiency (PCE) of 20.64% (certified stabilized PCE of 19.77%) is achieved with a short-circuit current density exceeding 24 mA cm-2 and an open-circuit voltage of 1.130 V, corresponding to a loss-in-potential of 0.35 V, and significantly enhanced operational stability

Enhancing momentum profits in the Taiwan Stock Market: The role of extreme absolute strength

Abstract(#br)We show that stocks with extreme absolute strength are highly volatile and thus attenuate the profitability of momentum in Taiwan, a market that has been widely documented as an exception of the momentum phenomenon. An enhanced momentum strategy that removes these stocks from the winner and loser portfolios generates significant profitability in the intermediate term. A major advantage of the enhanced momentum strategy is its robust profitability over time. More importantly, it is free from the momentum crashes. We provide further evidence to show that return dispersion and information uncertainty are closely related to momentum profitability in the cross-section when stocks with extreme absolute strength are removed

Ontology-based Fuzzy Markup Language Agent for Student and Robot Co-Learning

An intelligent robot agent based on domain ontology, machine learning mechanism, and Fuzzy Markup Language (FML) for students and robot co-learning is presented in this paper. The machine-human co-learning model is established to help various students learn the mathematical concepts based on their learning ability and performance. Meanwhile, the robot acts as a teacher's assistant to co-learn with children in the class. The FML-based knowledge base and rule base are embedded in the robot so that the teachers can get feedback from the robot on whether students make progress or not. Next, we inferred students' learning performance based on learning content's difficulty and students' ability, concentration level, as well as teamwork sprit in the class. Experimental results show that learning with the robot is helpful for disadvantaged and below-basic children. Moreover, the accuracy of the intelligent FML-based agent for student learning is increased after machine learning mechanism.Comment: This paper is submitted to IEEE WCCI 2018 Conference for revie

Single-Image HDR Reconstruction by Learning to Reverse the Camera Pipeline

Recovering a high dynamic range (HDR) image from a single low dynamic range (LDR) input image is challenging due to missing details in under-/over-exposed regions caused by quantization and saturation of camera sensors. In contrast to existing learning-based methods, our core idea is to incorporate the domain knowledge of the LDR image formation pipeline into our model. We model the HDRto-LDR image formation pipeline as the (1) dynamic range clipping, (2) non-linear mapping from a camera response function, and (3) quantization. We then propose to learn three specialized CNNs to reverse these steps. By decomposing the problem into specific sub-tasks, we impose effective physical constraints to facilitate the training of individual sub-networks. Finally, we jointly fine-tune the entire model end-to-end to reduce error accumulation. With extensive quantitative and qualitative experiments on diverse image datasets, we demonstrate that the proposed method performs favorably against state-of-the-art single-image HDR reconstruction algorithms.Comment: CVPR 2020. Project page: https://www.cmlab.csie.ntu.edu.tw/~yulunliu/SingleHDR Code: https://github.com/alex04072000/SingleHD

Ellagic Acid, the Active Compound of Phyllanthus urinaria, Exerts In Vivo Anti-Angiogenic Effect and Inhibits MMP-2 Activity

This study aimed to assess the potential anti-angiogenic mechanism of Phyllanthus urinaria (P. urinaria) and characterize the major compound in P. urinaria that exerts anti-angiogenic effect. The water extract of P. urinaria and Ellagic Acid were used to evaluate the anti-angiogenic effect in chorioallantoic membrane (CAM) in chicken embryo and human vascular endothelial cells (HUVECs). The matrix metalloproteinase-2 (MMP-2) activity was determined by gelatin zymography. The mRNA expressions of MMP-2, MMP-14 and tissue inhibitor of metalloproteinase-2 (TIMP-2) were analyzed by reverse transcription polymerase chain reaction (RT-PCR). Level of MMP-2 proteins in conditioned medium or cytosol was determined by western blot analysis. We confirmed that P. urinaria's in vivo anti-angiogenic effect was associated with a reduction in MMP-2 activity. Ellagic acid, one of the major polyphenolic components as identified in P. urinaria by high performance liquid chromatography mass spectrometry (HPLC/MS), exhibited the same anti-angiogenic effect in vivo. Both P. urinaria and Ellagic Acid inhibited MMP-2 activity in HUVECs with unchanged mRNA level. The mRNA expression levels of MMP-14 and TIMP-2 were not altered either. Results from comparing the change of MMP-2 protein levels in conditioned medium and cytosol of HUVECs after the P. urinaria or Ellagic Acid treatment revealed an inhibitory effect on the secretion of MMP-2 protein. This study concluded that Ellagic Acid is the active compound in P. urinaria to exhibit anti-angiogenic activity and to inhibit the secretion of MMP-2 protein from HUVECs