An application of the neural network to quantitative structure-activity relationship (QSAR) analysis has been studied. The new method was compared with the linear multiregression analysis in various ways. It was found that the neural network can be a potential tool in the routine work of QSAR analysis. The mathematical relationship of operation between the neural network and the multiregression analysis was described. It was shown that the neural network can exceed the level of the linear multiregression analysis.

Lithium-ion conductive solid oxide electrolytes are receiving increasing attention for the development of highperformance all-solid state rechargeable Li-ion batteries. In this study, we report an effective search method that uses a combination of ab initio calculations and multivariate analysis to find potential solid oxide electrolyte materials with low Li-ion hopping energies (EAs) among 66 olivine-type oxides with an ordered structure LiMXO 4 (main group M 2+ −X 5+ , M 3+ −X 4+ ). The ionic size of M, with its associated octahedral distortion leading to the appreciable local lattice distortion during the actual Li ion hop, made the most significant contribution to the variation in EA values. Promising M−X pairs (<0.30 eV) with experimental data in the Inorganic Crystal Structure Database include Mg−As (0.17 eV), Sc−Ge (0.22 eV), In−Ge (0.28 eV), and Mg−P (0.30 eV); Mg−As and Sc−Ge are reported here for the first time as battery materials. Promising theoretical compositions are also determined for Group 13 Al−X, Ga−X, and In−X pairs, and for Ca−X pairs.

Pretreatment intensity-modulated radiotherapy quality assurance is performed using simple rectangular or cylindrical phantoms; thus, the dosimetric errors caused by complex patient-specific anatomy are absent in the evaluation objects. In this study, we construct a system for generating patient-specific three-dimensional (3D)-printed phantoms for radiotherapy dosimetry. An anthropomorphic head phantom containing the bone and hollow of the paranasal sinus is scanned by computed tomography (CT). Based on surface rendering data, a patient-specific phantom is formed using a fused-deposition-modeling-based 3D printer, with a polylactic acid filament as the printing material. Radiophotoluminescence glass dosimeters can be inserted in the 3D-printed phantom. The phantom shape, CT value, and absorbed doses are compared between the actual and 3D-printed phantoms. The shape difference between the actual and printed phantoms is less than 1 mm except in the bottom surface region. The average CT value of the infill region in the 3D-printed phantom is -6 ± 18 Hounsfield units (HU) and that of the vertical shell region is 126 ± 18 HU. When the same plans were irradiated, the dose differences were generally less than 2%. These results demonstrate the feasibility of the 3D-printed phantom for artificial in vivo dosimetry in radiotherapy quality assurance.

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A radiophotoluminescent glass dosimeter (RGD) is widely used in postal audit system for photon beams in Japan. However, proton dosimetry in RGDs is scarcely used owing to a lack of clarity in their response to beam quality. In this study, we investigated RGD response to beam quality for establishing a suitable linear energy transfer (LET)-corrected dosimetry protocol in a therapeutic proton beam.The RGD response was compared with ionization chamber measurement for a 100-225 MeV passive proton beam. LET of the measurement points was calculated by the Monte Carlo method. An LET-correction factor, defined as a ratio between the non-corrected RGD dose and ionization chamber dose, of 1.226 × (LET) − 0.171 was derived for the RGD response. The magnitude of the LET-dependence of RGD increased with LET; for an LET of 8.2 keV/μm, the RGD under-response was up to 16%. The coefficient of determination, mean difference ± SD of non-corrected RGD dose, residual range-corrected RGD dose, and LET-corrected RGD dose to the ionization chamber are 0.923, 3.7 ± 4.2%, − 2.4 ± 7.5%, and 0.04 ± 2.1%, respectively. The LET-corrected RGD dose was within 5% of the corresponding ionization chamber dose at all energies until 200 MeV, where it was 5.3% lower than the ionization chamber dose.A corrected LET-dependence of RGD using a correction factor based on a power function of LET and precise dosimetric verification close to the maximum LET were realized here. We further confirmed establishment of an accurate postal audit under various irradiation conditions.

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