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Subject: human × DDC: 530 ×

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Now showing 1 - 4 of 4
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    Switchable magnetic bulk photovoltaic effect in the two-dimensional magnet CrI3
    (London : Nature Publishing Group, 2019) Zhang, Y.; Holder, T.; Ishizuka, H.; de Juan, F.; Nagaosa, N.; Felser, C.; Yan, B.
    The bulk photovoltaic effect (BPVE) rectifies light into the dc current in a single-phase material and attracts the interest to design high-efficiency solar cells beyond the pn junction paradigm. Because it is a hot electron effect, the BPVE surpasses the thermodynamic Shockley–Queisser limit to generate above-band-gap photovoltage. While the guiding principle for BPVE materials is to break the crystal centrosymmetry, here we propose a magnetic photogalvanic effect (MPGE) that introduces the magnetism as a key ingredient and induces a giant BPVE. The MPGE emerges from the magnetism-induced asymmetry of the carrier velocity in the band structure. We demonstrate the MPGE in a layered magnetic insulator CrI3, with much larger photoconductivity than any previously reported results. The photocurrent can be reversed and switched by controllable magnetic transitions. Our work paves a pathway to search for magnetic photovoltaic materials and to design switchable devices combining magnetic, electronic, and optical functionalities.
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    Correlating the ancient Maya and modern european calendars with high-precision AMS 14C dating
    (London : Nature Publishing Group, 2013) Kennett, D.J.; Hajdas, I.; Culleton, B.J.; Belmecheri, S.; Martin, S.; Neff, H.; Awe, J.; Graham, H.V.; Freeman, K.H.; Newsom, L.; Lentz, D.L.; Anselmetti, F.S.; Robinson, M.; Marwan, N.; Southon, J.; Hodell, D.A.; Haug, G.H.
    The reasons for the development and collapse of Maya civilization remain controversial and historical events carved on stone monuments throughout this region provide a remarkable source of data about the rise and fall of these complex polities. Use of these records depends on correlating the Maya and European calendars so that they can be compared with climate and environmental datasets. Correlation constants can vary up to 1000 years and remain controversial.Wereport a series of high-resolution AMS14C dates on a wooden lintel collected from the Classic Period city of Tikal bearing Maya calendar dates. The radiocarbon dates were calibrated using a Bayesian statistical model and indicate that the dates were carved on the lintel betweenAD 658-696. This strongly supports the Goodman-Mart?nez-Thompson (GMT) correlation and the hypothesis that climate change played an important role in the development and demise of this complex civilization.
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    Change in the embedding dimension as an indicator of an approaching transition
    (San Francisco, CA : Public Library of Science (PLoS), 2014) Neuman, Y.; Marwan, N.; Cohen, Y.
    Predicting a transition point in behavioral data should take into account the complexity of the signal being influenced by contextual factors. In this paper, we propose to analyze changes in the embedding dimension as contextual information indicating a proceeding transitive point, called OPtimal Embedding tRANsition Detection (OPERAND). Three texts were processed and translated to time-series of emotional polarity. It was found that changes in the embedding dimension proceeded transition points in the data. These preliminary results encourage further research into changes in the embedding dimension as generic markers of an approaching transition point.
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    Fiber-based SORS-SERDS system and chemometrics for the diagnostics and therapy monitoring of psoriasis inflammatory disease in vivo
    (Washington, DC : Optica, 2021-1-28) Schleusener, Johannes; Guo, Shuxia; Darvin, Maxim E.; Thiede, Gisela; Chernavskaia, Olga; Knorr, Florian; Lademann, Jürgen; Popp, Jürgen; Bocklitz, Thomas W.
    Psoriasis is considered a widespread dermatological disease that can strongly affect the quality of life. Currently, the treatment is continued until the skin surface appears clinically healed. However, lesions appearing normal may contain modifications in deeper layers. To terminate the treatment too early can highly increase the risk of relapses. Therefore, techniques are needed for a better knowledge of the treatment process, especially to detect the lesion modifications in deeper layers. In this study, we developed a fiber-based SORS-SERDS system in combination with machine learning algorithms to non-invasively determine the treatment efficiency of psoriasis. The system was designed to acquire Raman spectra from three different depths into the skin, which provide rich information about the skin modifications in deeper layers. This way, it is expected to prevent the occurrence of relapses in case of a too short treatment. The method was verified with a study of 24 patients upon their two visits: the data is acquired at the beginning of a standard treatment (visit 1) and four months afterwards (visit 2). A mean sensitivity of ≥85% was achieved to distinguish psoriasis from normal skin at visit 1. At visit 2, where the patients were healed according to the clinical appearance, the mean sensitivity was ≈65%.