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1. Structural discrimination from in situ measurement of 1 D CH and 2 D HH residual dipolar coupling constants: In situ measurement of 1 D CH and 2 D HH RDCs

   https://doi.org/10.1002/mrc.4575  

   Marcó, Núria ; Gil, Roberto R. ; Parella, Teodor ( June 2017 , Magnetic Resonance in Chemistry)
2. Encapsulation of tricopper cluster in a synthetic cryptand enables facile redox processes from Cu I Cu I Cu I to Cu II Cu II Cu II states

   https://doi.org/10.1039/D0SC05441K  

   Zhang, Weiyao ; Moore, Curtis E. ; Zhang, Shiyu ( March 2021 , Chemical Science)

   null (Ed.)

   One-pot reaction of tris(2-aminoethyl)amine (TREN), [Cu I (MeCN) 4 ]PF 6 , and paraformaldehyde affords a mixed-valent [ TREN4 Cu II Cu I Cu I (μ 3 -OH)](PF 6 ) 3 complex. The macrocyclic azacryptand TREN4 contains four TREN motifs, three of which provide a bowl-shape binding pocket for the [Cu 3 (μ 3 -OH)] 3+ core. The fourth TREN caps on top of the tricopper cluster to form a cryptand, imposing conformational constraints and preventing solvent interaction. Contrasting the limited redox capability of synthetic tricopper complexes reported so far, [ TREN4 Cu II Cu I Cu I (μ 3 -OH)](PF 6 ) 3 exhibits several reversible single-electron redox events. The distinct electrochemical behaviors of [ TREN4 Cu II Cu I Cu I (μ 3 -OH)](PF 6 ) 3 and its solvent-exposed analog [ TREN3 Cu II Cu II Cu II (μ 3 -O)](PF 6 ) 4 suggest that isolation of tricopper core in a cryptand enables facile electron transfer, allowing potential application of synthetic tricopper complexes as redox catalysts. Indeed, the fully reduced [ TREN4 Cu I Cu I Cu I (μ 3 -OH)](PF 6 ) 2 can reduce O 2 under acidic conditions. The geometric constraints provided by the cryptand are reminiscent of Nature's multicopper oxidases (MCOs). For the first time, a synthetic tricopper cluster was isolated and fully characterized at Cu I Cu I Cu I ( 4a ), Cu II Cu I Cu I ( 4b ), and Cu II Cu II Cu I ( 4c ) states, providing structural and spectroscopic models for many intermediates in MCOs. Fast electron transfer rates (10 5 to 10 6 M −1 s −1 ) were observed for both Cu I Cu I Cu I /Cu II Cu I Cu I and Cu II Cu I Cu I /Cu II Cu II Cu I redox couples, approaching the rapid electron transfer rates of copper sites in MCO. 

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3. Investigation of Pb–B Bonding in PbB 2 (BO) n − ( n = 0–2): Transformation from Aromatic PbB 2 − to Pb[B 2 (BO) 2 ] −/0 Complexes with BB Triple Bonds

   https://doi.org/10.1039/D3CP02800C  

   Chen, Qiang ; Chen, Wei-Jia ; Wu, Xin-Yao ; Chen, Teng-Teng ; Yuan, Rui-Nan ; Lu, Hai-Gang ; Yuan, Dao-Fu ; Li, Si-Dian ; Wang, Lai-Sheng ( February 2024 , Physical Chemistry Chemical Physics)

   Joint photoelectron spectroscopy and first-principles theory investigations indicate that the Pb-doped PbB₂(BO)_n⁻clusters (n= 0−2) undergo a transformation from σ + π doubly aromatic triangle PbB₂⁻to PbB₄(BO)₂^−/0complexes with a B≡B triple bond.

    

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4. N 5 ,N 10 -methylenetetrahydromethanopterin reductase from Methanocaldococcus jannaschii also serves as a methylglyoxal reductase

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5. Penalized high‐dimensional M‐quantile regression: From L 1 to L p optimization

   https://doi.org/10.1002/cjs.11597  

   Hu, Jie ; Chen, Yu ; Zhang, Weiping ; Guo, Xiao ( March 2021 , Canadian Journal of Statistics)

   Quantiles and expectiles have been receiving much attention in many areas such as economics, ecology, and finance. By means ofL^poptimization, both quantiles and expectiles can be embedded in a more general class of M‐quantiles. Inspired by this point of view, we propose a generalized regression calledL^p‐quantile regression to study the whole conditional distribution of a response variable given predictors in a heterogeneous regression setting. In this article, we focus on the variable selection aspect of high‐dimensional penalizedL^p‐quantile regression, which provides a flexible application and makes a complement to penalized quantile and expectile regressions. This generalized penalizedL^p‐quantile regression steers an advantageous middle course between ordinary penalized quantile and expectile regressions without sacrificing their virtues too much when 1 < p < 2, that is, offers versatility and flexibility with these ‘quantile‐like’ and robustness properties. We develop the penalizedL^p‐quantile regression withscadand adaptivelassopenalties. With properly chosen tuning parameters, we show that the proposed estimators display oracle properties. Numerical studies and real data analysis demonstrate the competitive performance of the proposed penalizedL^p‐quantile regression when 1 < p < 2, and they combine the robustness properties of quantile regression with the efficiency of penalized expectile regression. These properties would be helpful for practitioners.

    

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