Room temperature suzuki cross‐coupling polymerizations of aryl dihalides and aryldiboronic acid/acid esters with t‐Bu3P‐coordinated 2‐phenylaniline‐based palladacycle complex as the precatalyst

Room temperature Suzuki cross‐coupling polymerization of aryl dibromides/diiodides with aryldiboronic acids/acid esters with t‐Bu₃P‐coordinated 2‐phenylaniline‐based palladacycle complex, [2′‐(amino‐kN)[1,1′‐biphenyl]‐2‐yl‐kC]chloro(tri‐t‐butylphosphine)palladium, as a general precatalyst is described. Such room temperature Suzuki cross‐coupling polymerization is achieved by employing six equivalents or more of the base and affords polymers within an hour, with the yields and the molecular weights in general comparable to or higher than reported results that required higher reaction temperature and/or longer polymerization time. Our study provides a general catalyst system for the room temperature Suzuki cross‐coupling polymerization of aryl dibromides/diiodides with aryldiboronic acids/acid esters and paves the road for the investigation of employing other monodentate ligand‐coordinated palladacycle complexes including other electron‐rich monophosphine‐coordinated ones for room temperature cross‐coupling polymerizations. © 2019 Wiley Periodicals, Inc. J. Polym. Sci., Part A: Polym. Chem. 2019, 57, 1606–1611     

Cephalotanins A–D,Four Norditerpenoids Represent Three Highly Rigid Carbon Skeletons from Cephalotaxus sinensis

Four polycyclic norditerpenoids, cephalotanins A–D ( 1 – 4 ) representing three unprecedented carbon skeletons with highly rigid ring systems, were isolated from Cephalotaxus sinensis and structurally characterized by a combination of various methods. Compounds 1 and 2 are new skeletal norditerpenoid trilactones, while 3 and 4 are two norditerpenoids featuring different new carbon skeletons. Biosynthetic pathways for 1 – 4 were proposed by involving diverse and very fascinating chemical events with the coexisting cephalotane troponoids as the precursors. Compound 1 exhibited good NF‐κB inhibition with an IC₅₀ value of 4.12±0.61 μΜ.     

Estimating Individual Treatment Effect in Observational Data Using Random Forest Methods

Estimation of individual treatment effect in observational data is complicated due to the challenges of confounding and selection bias. A useful inferential framework to address this is the counterfactual (potential outcomes) model, which takes the hypothetical stance of asking what if an individual had received both treatments. Making use of random forests (RF) within the counterfactual framework we estimate individual treatment effects by directly modeling the response. We find that accurate estimation of individual treatment effects is possible even in complex heterogenous settings but that the type of RF approach plays an important role in accuracy. Methods designed to be adaptive to confounding, when used in parallel with out-of-sample estimation, do best. One method found to be especially promising is counterfactual synthetic forests. We illustrate this new methodology by applying it to a large comparative effectiveness trial, Project Aware, to explore the role drug use plays in sexual risk. The analysis reveals important connections between risky behavior, drug usage, and sexual risk. Supplementary material for this article is available online.     

Polyvinyl pyrrolidone-assisted synthesis of flower-like nickel-cobalt layered double hydroxide on Ni foam for high-performance hybrid supercapacitor

Nickel-cobalt layered double hydroxides (NiCo-LDH) were successfully deposited on nickel foam by a facile hydrothermal method using polyvinyl pyrrolidone (PVP) as the structure-directing reagent. The effect of PVP on the morphology and electrochemical performance of binder-free NiCo-LDH electrode for supercapacitor were investigated in detail. The prepared NiCo-LDH presented good dispersivity and appeared different flower-like structure via the addition of PVP. Specially, the NiCo-LDH electrode using 1 g of PVP exhibited a superior performance with a high-specific capacity of 724.9 C g^?1 at a current density of 1 A g^?1 and 577.1 C g^?1 at 10 A g^?1. In addition, a hybrid supercapacitor (HSC) based on the optimized NiCo-LDH as positive electrode and activated carbon as negative electrode was assembled with 6 M KOH as the electrolyte. The HSC device can deliver an energy density of 32.3 Wh kg^?1 at the power density of 387.1 W kg^?1. Moreover, the HSC device exhibited a good cycling stability with a retention rate of 94.0% after 2000-cycle charge-discharge test at 3 A g^?1.     

Green Tea Versus Traditional Korean Teas: Antibacterial/Antifungal or Both?

The feasibility of utilizing the antimicrobial activity of naturally available teas was studied. Eleven teas including 2 green teas and 9 other traditional Korean mixed teas were tested for their antimicrobial properties. Antibacterial and antifungal properties were assessed. The results showed that green teas possessed significant antifungal and antibacterial properties, while most of the mixed teas showed some amount of antifungal activity and almost insignificant antibacterial properties. Confocal microscopic imaging revealed mycelial damage as well as attack on sporophores rather than spores/spore germination to be the reason behind the antifungal activity. EGCG was identified as the crucial catechin for antimicrobial activity. The study confirmed that green tea had a clear edge over the traditional mixed teas when it comes to antimicrobial activity.     

Joint L1/Lp-regularized minimization in video recovery of remote sensing based on compressed sensing

L₁ regularization and L_p regularization are proposed for processing recovered images based on compressed sensing (CS). L₁ regularization can be solved as a convex optimization problem but is less sparse than L_p (0 < p < 1). L_p regularization is sparser than L₁ regularization but is more difficult to solve. This paper proposes joint L₁/L_p (0 < p < 1) regularization, which combines L_p regularization and L₁ regularization. This joint regularization is applied to recover video of remote sensing based on CS. Joint regularization is sparser than L₁ regularization but is as easy to solve as L₁ regularization. A linearized Bregman reweighted iteration algorithm is proposed to solve the joint L₁/L_p regularization problem. The performance and capabilities of the linearized Bregman algorithm and linearized Bregman reweighted algorithm for solving the joint L₁/L_p regularization model are analyzed and compared through numerical simulations.