Photometric and Monte-Carlo modeling unified approach for the calculation of spatially-resolved correction coefficients linking simulated and experimental diffuse reflectance spectra. | LitMetric
The estimation of skin optical properties by means of inverse problem solving from spatially resolved diffuse reflectance (SR-DR) spectra is one way to exploit the acquired clinical signals. This method requires the comparison between the experimental spectra collected with a medical device, and spectra generated by the photons transport numerical simulations. This comparison is usually limited to spectral shape due to the absence of intensity standardization of the experimental DR spectra. This study proposes to theoretically (using photometric calculation) and experimentally (from experimental spectra acquired on optical phantom) establish a corrective factor to obtain common intensity unit for experimental and simulated signals.
The fact that the photoabsorption spectrum of a material contains information about the atomic structure, commonly understood in terms of multiple scattering theory, is the basis of the popular extended X-ray absorption spectroscopy (EXAFS) technique. How much of the same structural information is present in other complementary spectroscopic signals is not obvious. Here we use a machine learning approach to demonstrate that within theoretical models that accurately predict the EXAFS signal, the extended near-edge region does indeed contain the EXAFS-accessible structural information.
Leaf photosynthesis models are used extensively in photosynthesis research and are embedded in many larger scale models. Typical photosynthesis models simplify light intensity as the integrated intensity over the 400-700 nm waveband (photosynthetic active radiation, PAR). However, far-red light (700-750 nm, FR) also drives photosynthesis when supplied in addition to light within the PAR spectrum.
Many-body interactions in metal-organic frameworks (MOFs) are fundamental for emergent quantum physics. Unlike their solution counterpart, magnetization at surfaces in low-dimensional analogues is strongly influenced by magnetic anisotropy (MA) induced by the substrate and still not well understood. Here, on-surface coordination chemistry is used to synthesize on Ag(111) and superconducting Pb(111) an iron-based spin chain by using pyrene-4,5,9,10-tetraone (PTO) precursors as ligands.
Next-generation shotgun proteomics is one of the most valuable tools for gaining insight into the function of organisms. By providing a list of peptides and abundance information, proteomics enables the identification of proteins, their quantities, posttranslational modifications, and localization. The most refined shotgun proteomics workflow involves protein extraction, trypsin digestion, ultrahigh-performance liquid chromatography coupled to high-resolution tandem mass spectrometry, and confident assignment of resulting spectra to peptide sequences.
Quantum chemical calculations of one-photon absorption, electronic circular dichroism and anisotropy factor spectra for the A-band transition of fenchone, camphor and 3-methylcyclopentanone (3MCP) are reported. While the only weakly allowed nature of the transition leads to comparatively large anisotropies, a proper theoretical description of the absorption for such a transition requires to account for non-Condon effects. We present experimental data for the anisotropy of 3MCP in the liquid phase and show that corresponding Herzberg-Teller corrections are critical to reproduce the main experimental features.
