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Zienko S. I. Zhbanova V. L. 《Journal of Communications Technology and Electronics》2022,67(4):395-402
Journal of Communications Technology and Electronics - A quantitative comparison of the spectral characteristics of the human visual system and matrix photodetectors is carried out. Criteria for a... 相似文献
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Leibetseder Andreas Schoeffmann Klaus Keckstein Jörg Keckstein Simon 《Multimedia Tools and Applications》2022,81(5):6191-6215
Multimedia Tools and Applications - Endometriosis is a common gynecologic condition typically treated via laparoscopic surgery. Its visual versatility makes it hard to identify for non-specialized... 相似文献
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Kathleen T. Lauser Amy L. Rueter Michelle A. Calabrese 《American Institute of Chemical Engineers》2022,68(12):e17850
While protein medications are promising for treatment of cancer and autoimmune diseases, challenges persist in terms of development and injection stability of high-concentration formulations. Here, the extensional flow properties of protein-excipient solutions are examined via dripping-onto-substrate extensional rheology, using a model ovalbumin (OVA) protein and biocompatible excipients polysorbate 20 (PS20) and 80 (PS80). Despite similar PS structures, differences in extensional flow are observed based on PS identity in two regimes: at moderate total concentrations where surface tension differences drive changes in extensional flow behavior, and at small PS:OVA ratios, which impact the onset of weakly elastic flow behavior. Undesirable elasticity is observed in ultra-concentrated formulations, independent of PS identity; higher PS contents are required to observe these effects than in analogous polymeric excipient solutions. These studies reveal novel extensional flow behaviors in protein-excipient solutions, and provide a straightforward methodology for assessing the extensional flow stability of new protein-excipient formulations. 相似文献
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Shannon Lee Scott L. Carnahan Georgiy Akopov Philip Yox Lin-Lin Wang Aaron J. Rossini Kui Wu Kirill Kovnir 《Advanced functional materials》2021,31(16):2010293
Noncentrosymmetric (NCS) tetrel pnictides have recently generated interest as nonlinear optical (NLO) materials due to their second harmonic generation (SHG) activity and large laser damage threshold (LDT). Herein nonmetal-rich silicon phosphides RuSi4P4 and IrSi3P3 are synthesized and characterized. Their crystal structures are reinvestigated using single crystal X-ray diffraction and 29Si and 31P magic angle spinning NMR. In agreement with previous report RuSi4P4 crystallizes in NCS space group P1, while IrSi3P3 is found to crystallize in NCS space group Cm, in contrast with the previously reported space group C2. A combination of DFT calculations and diffuse reflectance measurements reveals RuSi4P4 and IrSi3P3 to be wide bandgap (Eg) semiconductors, Eg = 1.9 and 1.8 eV, respectively. RuSi4P4 and IrSi3P3 outperform the current state-of-the-art infrared SHG material, AgGaS2, both in SHG activity and laser inducer damage threshold. Due to the combination of high thermal stabilities (up to 1373 K), wide bandgaps (≈2 eV), NCS crystal structures, strong SHG responses, and large LDT values, RuSi4P4 and IrSi3P3 are promising candidates for longer wavelength NLO materials. 相似文献
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Prof. Andrea Baier Dr. Anne Kokel Dr. William Horton Ewa Gizińska Dr. Garima Pandey Prof. Ryszard Szyszka Prof. Béla Török Prof. Marianna Török 《ChemMedChem》2021,16(12):1927-1932
A set of novel hydrazone derivatives were synthesized and analyzed for their biological activities. The compounds were tested for their inhibitory effect on the phosphorylating activity of the protein kinase CK2, and their antioxidant activity was also determined in three commonly used assays. The hydrazones were evaluated for their radical scavenging against the DPPH, ABTS and peroxyl radicals. Several compounds have been identified as good antioxidants as well as potent protein kinase CK2 inhibitors. Most hydrazones containing a 4-N(CH3)2 residue or perfluorinated phenyl rings showed high activity in the radical-scavenging assays and possess nanomolar IC50 values in the kinase assays. 相似文献
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Seredin P. V. Radam Ali Obaid Goloshchapov D. L. Len’shin A. S. Buylov N. S. Barkov K. A. Nesterov D. N. Mizerov A. M. Timoshnev S. N. Nikitina E. V. Arsentyev I. N. Sharafidinov Sh. Kukushkin S. A. Kasatkin I. A. 《Semiconductors》2022,56(4):253-258
Semiconductors - Abstract—In our work, we carry out a structural-spectroscopic study of AlGaN/GaN epitaxial layers grown by molecular-beam epitaxy with nitrogen-plasma activation on a hybrid... 相似文献
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Alexander Detzner Martin Eigner 《Quality and Reliability Engineering International》2021,37(1):335-351
Manufacturing companies not only strive to deliver flawless products but also monitor product failures in the field to identify potential quality issues. When product failures occur, quality engineers must identify the root cause to improve any affected product and process. This root-cause analysis can be supported by feature selection methods that identify relevant product attributes, such as manufacturing dates with an increased number of product failures. In this paper, we present different methods for feature selection and evaluate their ability to identify relevant product attributes in a root-cause analysis. First, we compile a list of feature selection methods. Then, we summarize the properties of product attributes in warranty case data and discuss these properties regarding the challenges they pose for machine learning algorithms. Next, we simulate datasets of warranty cases, which emulate these product properties. Finally, we compare the feature selection methods based on these simulated datasets. In the end, the univariate filter information gain is determined to be a suitable method for a wide range of applications. The comparison based on simulated data provides a more general result than other publications, which only focus on a single use case. Due to the generic nature of the simulated datasets, the results can be applied to various root-cause analysis processes in different quality management applications and provide a guideline for readers who wish to explore machine learning methods for their analysis of quality data. 相似文献