Alcohol-initiated ring-opening alternating copolymerization (ROAP) of phthalic anhydride (PA) and a variety of mono-, di-, and trisubstituted epoxides has been performed with a weak phosphazene base ...(t-BuP1) as the catalyst. Each product exhibits a perfectly alternating sequence distribution, controlled molar mass (M n up to 124 kg mol–1), and low dispersity (Đ M < 1.15, mostly). Full conversion of PA can be reached in 0.5–24 h depending on the substituent of the epoxide, the targeted degree of polymerization, and the amount of t-BuP1 used (0.2–5 mol % of PA) when the reactions are conducted under solvent-free conditions at 100 °C with a small excess of the epoxide (0.5 equiv of PA). The glass transition temperature of the polyester ranges from −14 to 135 °C. The living nature of the ROAP allows one-pot construction of well-defined block-alternating copolymers through sequential addition of two epoxides. Statistical-alternating copolymers have also been synthesized by copolymerization of PA and two mixed epoxides. Thus, the structural diversity of aromatic alternating polyesters synthesized by this simple organocatalysis has been largely enriched.
A mild and general visible light photoredox catalysis-induced intermolecular three-component alkene 1,2-diarylation involving aryl C(sp2)-H functionalization is described. The key to controlling the ...chemoselectivity toward alkene 1,2-diarylation is the employment of a 2,2'-bipyridine base, thus allowing the formation of two new C(sp3)-C(sp2) bonds via aryl radical formation from aryldiazonium salts, addition across the Cdouble bond, length as m-dashC bonds, and aryl C(sp2)-H functionalization cascades.
Resolving late failure of dental implant is difficult and costly; however, only few reviews have addressed the risk factors associated with late failure of dental implant. The aim of this literature ...review was to summarize the influences of different potential risk factors on the incidence of late dental implant failure. The protocol of this systematic review was prepared and implemented based on the PRISMA (Preferred reporting items for systematic reviews and meta-analyses) guideline. In December 2018, studies published within the previous 10 years on late dental implant failure were selected by fulfilling the eligibility criteria and the risk factors identified in qualified studies were extracted by using a predefined extraction template. Fourteen eligible studies were assessed. The common risk factors for late failure were divided into three groups according to whether they were related to (1) the patient history (radiation therapy, periodontitis, bruxism and early implant failure), (2) clinical parameters (posterior implant location and bone grade 4) or (3) decisions made by the clinician (low initial stability, more than one implant placed during surgery, inflammation at the surgical site during the first year or using an overdenture with conus-type connection). Clinicians should be cautions throughout the treatment process of dental implant—from the initial examination to the treatment planning, surgical operation and prosthesis selection—in order to minimize the risk of late failure of dental implant.
The ability to make stable water-in-oil and oil-in-water millimeter-size Pickering emulsions is demonstrated using Janus particlesparticles with distinct surface chemistries. The use of a highly ...cross-linked hydrophobic polymer network and the excellent water-wetting nature of a hydrogel as the hydrophobic and hydrophilic sides, respectively, permit distinct wettability on the Janus particle. Glass capillary microfluidics allows the synthesis of Janus particles with controlled sizes between 128 and 440 μm and control over the hydrophilic-to-hydrophobic domain volume ratio of the particle from 0.36 to 12.77 for a given size. It is shown that the Janus particle size controls the size of the emulsion drops, thus providing the ability to tune the structure and stability of the resulting emulsions. Stability investigations using centrifugation reveal that particles with the smallest size and a balanced hydrophilic-to-hydrophobic volume ratio (Janus ratio) form emulsions with the greatest stability against coalescence. Particles eventually jam at the interface to form nonspherical droplets. This effect is more pronounced as the hydrogel volume is increased. The large Janus particles permit facile visualization of particle-stabilized emulsions, which result in a better understanding of particle stabilization mechanisms of formed emulsions.
Post-matching network (PMN) dominates broadband Doherty power amplifier (DPA) design, but at the cost of large footprint. This brief presents a PMN-free, compact and broadband DPA based on dual-mode ...impedance transformer (IT) which can simultaneously realize a complex-to-real conversion at two frequencies. The conversion ratio of the IT is significantly increased while its fluctuation is reduced after collaborating a short drain bias. The dual-mode ITs are used as the output matching networks in the carrier and peaking paths. An out-of-phase 2nd harmonic injection path is constructed based on the inherent structure of the IT without additional bridge, resulting in enhanced saturated efficiency and output power at the upper band edge. A prototype circuit operating from 2.1 to 3.1 GHz is fabricated, and measured results show a 7-8.2 dB gain and 42.2-43.3 dBm output power at saturation. The 6-dB OBO and saturated efficiency is 42.3-52% and 60.4-67.7%, respectively. The area of the whole OMNs is only 19×37 mm2, indicating a significant size reduction, while the DPA's performance is comparable with the PMN types.
•Rock permeability can be evaluated rapidly by the convolutional neural network.•Physical information improves the performance of the convolutional neural network.•Physical information reduces the ...number of samples required.•Physical information is helpful for out-of-range problems.•Transfer learning can be applied in the case of out-of-range problems.
Permeability is one of the most important properties in subsurface flow problems, which measures the ability of rocks to transmit fluid. Normally, permeability is determined through experiments and numerical simulations, both of which are time-consuming. In this paper, we propose a new effective method based on convolutional neural networks with physical information (CNNphys) to rapidly evaluate rock permeability from its three-dimensional (3D) image. In order to obtain sufficient reliable labeled data, rock image reconstruction is utilized to generate sufficient samples based on the Joshi-Quiblier-Adler method. Next, the corresponding permeability is calculated using the Lattice Boltzmann method. We compare the prediction performance of CNNphys and convolutional neural networks (CNNs). The results demonstrate that CNNphys achieves superior performance, especially in the case of a small dataset and an out-of-range problem. Moreover, the performance of both CNN and CNNphys is greatly improved combined with transfer learning in the case of an out-of-range problem. This opens novel pathways for rapidly predicting permeability in subsurface applications.
We report a microfluidic approach for one‐step fabrication of polyelectrolyte microcapsules in aqueous conditions. Using two immiscible aqueous polymer solutions, we generate transient ...water‐in‐water‐in‐water double emulsion droplets and use them as templates to fabricate polyelectrolyte microcapsules. The capsule shell is formed by the complexation of oppositely charged polyelectrolytes at the immiscible interface. We find that attractive electrostatic interactions can significantly prolong the release of charged molecules. Moreover, we demonstrate the application of these microcapsules in encapsulation and release of proteins without impairing their biological activities. Our platform should benefit a wide range of applications that require encapsulation and sustained release of molecules in aqueous environments.
Polyelectrolyte (PE) capsules: Using two immiscible aqueous solutions, dextran and PEG, transient double emulsions were created in a microfluidic system and used as templates to fabricate PE capsules. The capsule shell was formed by complexation of oppositely charged PEs, PE+ and PE−, at the interface of the two aqueous phases. This platform enables encapsulation and release of proteins without impairing their activity.
An efficient method for uncertainty analysis of flow in random porous media is explored in this study, on the basis of combination of Karhunen‐Loeve expansion and probabilistic collocation method ...(PCM). The random log transformed hydraulic conductivity field is represented by the Karhunen‐Loeve expansion and the hydraulic head is expressed by the polynomial chaos expansion. Probabilistic collocation method is used to determine the coefficients of the polynomial chaos expansion by solving for the hydraulic head fields for different sets of collocation points. The procedure is straightforward and analogous to the Monte Carlo method, but the number of simulations required in PCM is significantly reduced. Steady state flows in saturated random porous media are simulated with the probabilistic collocation method, and comparisons are made with other stochastic methods: Monte Carlo method, the traditional polynomial chaos expansion (PCE) approach based on Galerkin scheme, and the moment‐equation approach based on Karhunen‐Loeve expansion (KLME). This study reveals that PCM and KLME are more efficient than the Galerkin PCE approach. While the computational efforts are greatly reduced compared to the direct sampling Monte Carlo method, the PCM and KLME approaches are able to accurately estimate the statistical moments and probability density function of the hydraulic head.
Radical‐initiated difunctionalization of alkenes is one of the most important methods in organic synthesis and medicinal chemistry, which can be applied to synthesize value complex compounds as well ...as structural motifs that found in bioactive natural products and pharmaceuticals. In recent years, impressive progress have been made in this area with ideal silver catalysis. Here, we summarize recent advances in silver‐mediated radical difunctionalization of alkenes for the formation of diverse bonds, including 1) two‐component radical difunctionalization reactions enabled by an intramolecular cyclization process toward various cyclic compounds and 2) three‐component radical difunctionalization reactions leading to complex linear compounds. These silver‐mediated radical alkene difunctionalization transformations are general initiated by different radicals, such as carbon‐, oxygen‐, sulfur‐, phosphinyl‐, and halogen‐center radicals, followed by terminated with nucleophiles to form two new bonds in a single reaction.
Ag catalysis: Recent advances in the silver‐mediated intermolecular radical 1,2‐difunctionalization of alkenes are summarized. These reaction are classified by the substrate type and radical regents. Two new C−C/C−C bonds, C−C/C−X bonds (X=F, O, S…) and C−X/C−X bonds (X=O, Br, I…) could be constructed in a single reaction.
Manual construction tasks are physically demanding, requiring prolonged awkward postures that can cause pain and injury. Person posture recognition (PPR) is essential in postural ergonomic hazard ...assessment. This paper proposed an ergonomic posture recognition method using 3D view-invariant features from a single 2D camera that is non-intrusive and widely installed on construction sites. Based on the detected 2D skeletons, view-invariant relative 3D joint position (R3DJP) and joint angle are extracted as classification features by employing a multi-stage convolutional nerual network (CNN) architecture, so that the learned classifier is not sensitive to camera viewpoints. Three posture classifiers regarding arms, back, and legs are trained, so that they can be simultaneously classified in one video frame. The posture recognition accuracies of three body parts are 98.6%, 99.5%, 99.8%, respectively. For generalization ability, the relevant accuracies are 94.9%, 93.9%, 94.6%, respectively. Both the classification accuracy and generalization ability of the method outperform previous vision-based methods in construction. The proposed method enables reliable and accurate postural ergonomic assessment for improving construction workers' safety and healthy.
•View-invariant 3D ergonomic postures recognition in single 2D camera•Simultaneous classification of arms, back, and legs postures in one video frame•View-invariant R3DJP and joint angle features extraction in single 2D image•Deep CNN-based learning is applied in 3D ergonomic postures recognition•The posture recognition accuracies of three body parts are 98.7%, 99.5%, 99.8%
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