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•Dynamic recrystallization grains nucleated at 4-, 3- and 2-grain junctions in turn.•Two proposed recrystallization nucleation mechanisms operate well at grain junctions.•The ...nucleation priority of one grain junction can be predicted by Taylor factors.
Despite the important role of grain junctions to the dynamic recrystallization (DRX) of nickel-based superalloys, the nucleation mechanisms operating there and the influence factors besides deformation condition on nucleation priority are still unclear. The microstructure evolution considering grain junction effects has not been explored in depth yet. In this paper, DRX nucleation at the 2-, 3- and 4-grain junctions of a nickel-based superalloy was investigated. A proposed passive grain boundary bulging (PGBB) mechanism operated well at 2-grain junctions, and accounted for the continuity of necklace structure during the early stage of hot deformation. For the 3-grain junctions, a two-step strain-induced bulging of grain boundary fragments, which closely adjoined the junctions, was found to dominate the DRX nucleation. In addition, an increasing nucleation priority from 2-, 3- to 4-grain junctions was confirmed by the established thermodynamic model, while the nucleation priority differences of the same kind grain junctions were quantitatively analyzed by using the Taylor factors of their component grains. Finally, the DRX microstructure evolution of a 4-grain stacking unit during hot deformation was described. The understanding of DRX associated with 2-, 3- to 4-grain junctions made it more effective to tailor the microstructure of nickel-based superalloy forgings.
In this study, the sensitive and selective detection of bisphenol A (BPA) was achieved using a screen-printed carbon electrode (NFO/SPCE) modified with hydrothermally synthesized NiFe2O4 ...nanoparticles. The crystalline structure, surface morphology and electrical conductivity of the nanoparticles were analyzed using X-ray powder diffraction (XRD), Fourier-transform infrared spectroscopy (FT-IR), scanning electron microscopy (SEM), and electrochemical impedance spectroscopy (EIS). The as-prepared NiFe2O4 (NFO) nanoparticles exhibited a cubic crystal structure with an average crystallite size of 16 nm, as calculated using the Scherrer equation. As determined by cyclic voltammetry (CV), NFO/SPCE exhibited excellent electrochemical oxidation towards the detection of BPA. Subsequently, differential pulse voltammetry (DPV) studies revealed a rapid and stable response to the consecutive addition of BPA in a linear range of 0.02–12.5 μM with a lower limit of detection (LOD) of 6 nM, which was superior to previously reported results. In addition, the proposed method showed good stability and excellent repeatability for the determination of BPA in real samples.
The pathogenesis of mucoinfective lung disease in cystic fibrosis (CF) patients likely involves poor mucus clearance. A recent model of mucus clearance predicts that mucus flow depends on the ...relative mucin concentration of the mucus layer compared with that of the periciliary layer; however, mucin concentrations have been difficult to measure in CF secretions. Here, we have shown that the concentration of mucin in CF sputum is low when measured by immunologically based techniques, and mass spectrometric analyses of CF mucins revealed mucin cleavage at antibody recognition sites. Using physical size exclusion chromatography/differential refractometry (SEC/dRI) techniques, we determined that mucin concentrations in CF secretions were higher than those in normal secretions. Measurements of partial osmotic pressures revealed that the partial osmotic pressure of CF sputum and the retained mucus in excised CF lungs were substantially greater than the partial osmotic pressure of normal secretions. Our data reveal that mucin concentration cannot be accurately measured immunologically in proteolytically active CF secretions; mucins are hyperconcentrated in CF secretions; and CF secretion osmotic pressures predict mucus layer-dependent osmotic compression of the periciliary liquid layer in CF lungs. Consequently, mucin hypersecretion likely produces mucus stasis, which contributes to key infectious and inflammatory components of CF lung disease.
Microplastics, as emerging contaminants in the global environment, have become a cause for concern for both academics and the public. The present understanding of microplastic pollution is primarily ...focused on marine environments, and less attention has been given to freshwater environments, in particular, to urban rivers. In this study, microplastics were sampled from surface water and sediments in 14 sites located in the lower course of the Pearl River. These sampling sites are located along Guangzhou of South China, with built-up areas being the dominant land use. The abundances of microplastics in surface water and sediments ranged from 379 to 7924 items·m−3 and 80 to 9597 items·kg−1, respectively. Polyethylene and polypropylene were the common types of microplastics, together accounting for 64.3% and 73.8% of surface water and sediment samples, respectively. Fibers were the dominant microplastic shapes in both water and sediment samples. The abundances of microplastics varied in surface water and sediments with each site, which might be affected by multiple factors. Our results indicated that wastewater treatment plants (WWTP) could reduce microplastics from municipal sewage which was finally discharged into the Pearl River along Guangzhou.
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•Microplastics in the Pearl River along Guangzhou were investigated for the first time.•Fibers were detected in both surface water and sediment samples.•PE and PP were the dominant polymer types in surface water and sediments.•WWTP in Guangzhou could reduce microplastic pollution in the municipal sewage.
New sequencing technologies promise a new era in the use of DNA sequence. However, some of these technologies produce very short reads, typically of a few tens of base pairs, and to use these reads ...effectively requires new algorithms and software. In particular, there is a major issue in efficiently aligning short reads to a reference genome and handling ambiguity or lack of accuracy in this alignment. Here we introduce the concept of mapping quality, a measure of the confidence that a read actually comes from the position it is aligned to by the mapping algorithm. We describe the software MAQ that can build assemblies by mapping shotgun short reads to a reference genome, using quality scores to derive genotype calls of the consensus sequence of a diploid genome, e.g., from a human sample. MAQ makes full use of mate-pair information and estimates the error probability of each read alignment. Error probabilities are also derived for the final genotype calls, using a Bayesian statistical model that incorporates the mapping qualities, error probabilities from the raw sequence quality scores, sampling of the two haplotypes, and an empirical model for correlated errors at a site. Both read mapping and genotype calling are evaluated on simulated data and real data. MAQ is accurate, efficient, versatile, and user-friendly. It is freely available at http://maq.sourceforge.net.
Enantiopure vicinal amino alcohols and derivatives are essential structural motifs in natural products and pharmaceutically active molecules, and serve as main chiral sources in asymmetric synthesis. ...Currently known asymmetric catalytic protocols for this class of compounds are still rare and often suffer from limited scope of substrates, relatively low regio- or stereoselectivities, thus prompting the development of more effective methodologies. Herein we report a dual catalytic strategy for the convergent enantioselective synthesis of vicinal amino alcohols. The method features a radical-type Zimmerman-Traxler transition state formed from a rare earth metal with a nitrone and an aromatic ketyl radical in the presence of chiral N,N'-dioxide ligands. In addition to high level of enantio- and diastereoselectivities, our synthetic protocol affords advantages of simple operation, mild conditions, high-yielding, and a broad scope of substrates. Furthermore, this protocol has been successfully applied to the concise synthesis of pharmaceutically valuable compounds (e.g., ephedrine and selegiline).
Spectral unmixing is an important technique in hyperspectral image applications. Recently, sparse regression has been widely used in hyperspectral unmixing, but its performance is limited by the high ...mutual coherence of spectral libraries. To address this issue, a new sparse unmixing algorithm, called double reweighted sparse unmixing and total variation (TV), is proposed in this letter. Specifically, the proposed algorithm enhances the sparsity of fractional abundances in both spectral and spatial domains through the use of double weights, where one is used to enhance the sparsity of endmembers in spectral library, and the other is introduced to improve the sparsity of fractional abundances. Moreover, a TV-based regularization is further adopted to explore the spatial-contextual information. As such, the simultaneous utilization of both double reweighted l 1 minimization and TV regularizer can significantly improve the sparse unmixing performance. Experimental results on both synthetic and real hyperspectral data sets demonstrate the effectiveness of the proposed algorithm both visually and quantitatively.
CHoose nickel: The nickel‐catalyzed oxidative arylation of C(sp3)H bonds has been achieved. Several substituted arylboronic acids and various C(sp3)H bonds were found to be suitable substrates for ...this novel transformation, which is likely to proceed through a radical pathway. This method allows the introduction of simple ether derivatives to construct α‐arylated ethers. FG=functional group.
The spatial characteristics of cracks are significant indicators to assess and evaluate the health of existing buildings and infrastructures. However, the current manual crack description method is ...time consuming and labor consuming. To improve the efficiency of crack inspection, advanced computer vision‐based techniques have been utilized to detect cracks automatically at image level and grid‐cell level. But existing crack detections are of (high specificity) low generality and inefficient, in terms that conventional approaches are unable to identify and measure diverse cracks concurrently at pixel level. Therefore, this research implements a novel deep learning technique named fully convolutional network (FCN) to address this problem. First, FCN is trained by feeding multiple types of cracks to semantically identify and segment pixel‐wise cracks at different scales. Then, the predicted crack segmentations are represented by single‐pixel width skeletons to quantitatively measure the morphological features of cracks, providing valuable crack indicators for assessment in practice, such as crack topology, crack length, max width, and mean width. To validate the prediction, the predicted segmentations are compared with recent advanced method for crack recognition and ground truth. For crack segmentation, the accuracy, precision, recall, and F1 score are 97.96%, 81.73%, 78.97%, and 79.95%, respectively. For crack length, the relative measurement error varies from −48.03% to 177.79%, meanwhile that ranges from −13.27% to 24.01% for crack width. The results show that FCN is feasible and sufficient for crack identification and measurement. Although the accuracy is not as high as CrackNet because of three types of errors, the prediction has been increased to pixel level and the training time has been dramatically decreased to several per cents of previous methods due to the novel end‐to‐end structure of FCN, which combines typical convolutional neural networks and deconvolutional layers.
Advancing of the lead halide perovskite solar cells towards photovoltaic market demands large-scale devices of high-power conversion efficiency, high reproducibility and stability via low-cost ...fabrication technology, and in particular resistance to humid environment for long-time operation. Here we achieve uniform perovskite film based on a novel polymer-scaffold architecture via a mild-temperature process. These solar cells exhibit efficiency of up to ∼ 16% with small variation. The unencapsulated devices retain high output for up to 300 h in highly humid environment (70% relative humidity). Moreover, they show strong humidity resistant and self-healing behaviour, recovering rapidly after removing from water vapour. Not only the film can self-heal in this case, but the corresponding devices can present power conversion efficiency recovery after the water vapour is removed. Our work demonstrates the value of cheap, long chain and hygroscopic polymer scaffold in perovskite solar cells towards commercialization.
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