Transition metal-catalyzed decarboxylative cross-coupling reactions have recently emerged as a new and important category of organic transformations that find versatile applications in the ...construction of carbon-carbon and carbon-heteroatom bonds. The use of relatively cheap and stable carboxylic acids to replace organometallic reagents enables the decarboxylative cross-coupling reactions to proceed with good selectivities and functional group tolerance. In the present review we summarize the various types of decarboxylative cross-coupling reactions catalyzed by different transition metal complexes. The scope and applications of these reactions are described. The challenges and opportunities in the field are discussed.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
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•A new framework is proposed for landslide susceptibility analysis.•Bayesian algorithm is used to optimize the proportion of landslide samples.•The framework is validated by a case ...study, and RF and GBDT outperform SVM.
Machine learning models have been widely used for landslide susceptibility assessment (LSA) in recent years. The accuracy of machine learning-based LSA often hinges on the ratio of landslide to non-landslide (or positive/negative, P/N) samples. A proper ratio of the P/N samples will significantly improve the performance of machine learning-based LSA, but an improper ratio can cause inadequate training or data pollution. Conventionally, the determination of the P/N sample ratio is based on experience or by trials and errors, which has substantial uncertainties. This paper proposes a Bayesian optimization method to optimize the P/N sample ratio for machine learning models. Firstly, Anhua County in Hunan province of China is selected as the study area because of numerous landslide disasters that occurred in recent years. Secondly, three representative machine learning models of the support vector machine (SVM), the random forest (RF) and the gradient boost decision tree (GBDT) are adopted to assess the landslide susceptibility. Subsequently, a Bayesian optimization algorithm is used to obtain the optimal P/N sample ratio, considering the effects of various ratios of training/test set. Finally, the improved models and the corresponding landslide susceptibility maps are established using the obtained optimal P/N sample ratio. The results show that the performance of SVM, RF and GBDT are all improved with the optimized P/N sample ratio. The highest AUC value is for the RF model (0.840, improved by 1.3%), followed by GBDT (0.831, improved by 1.3%), and SVM (0.775, improved by 0.7%). However, the RF and GBDT are more suitable than SVM to address sample unbalance issues in LSA. It is suggested to use the Bayesian optimization algorithm to optimize the P/N sample ratio in machine learning-based LSA model.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
The innate immune system has the capacity to detect 'non-self' molecules derived from pathogens, known as pathogen-associated molecular patterns, via pattern recognition receptors. In addition, an ...increasing number of endogenous host-derived molecules, termed damage-associated molecular patterns (DAMPs), have been found to be sensed by various innate immune receptors. The recognition of DAMPs, which are produced or released by damaged and dying cells, promotes sterile inflammation, which is important for tissue repair and regeneration, but can also lead to the development of numerous inflammatory diseases, such as metabolic disorders, neurodegenerative diseases, autoimmune diseases and cancer. Here we examine recent discoveries concerning the roles of DAMP-sensing receptors in sterile inflammation and in diseases resulting from dysregulated sterile inflammation, and then discuss insights into the cross-regulation of these receptors and their ligands.
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FZAB, GEOZS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Two crystalline large‐sized porous organic cages (POCs) based on conical calix4arene (C4A) were designed and synthesized. The four‐jaw C4A unit tends to follow the face‐directed self‐assembly law ...with the planar triangular building blocks such as tris(4‐aminophenyl)amine (TAPA) or 1,3,5‐tris(4‐aminophenyl)benzene (TAPB) to generate a predictable cage with a stoichiometry of 6+8. The formation of the large cages is confirmed through their relative molecular mass measured using MALDI‐TOF/TOF spectra. The protonated molecular ion peaks of C4A‐TAPA and C4A‐TAPB were observed at m/z 5109.0 (calculated for C336H240O24N32: m/z 5109.7) and m/z 5594.2 (calculated for C384H264O24N24: m/z 5598.4). C4A‐POCs exhibit I‐type N2 adsorption‐desorption isotherms with the BET surface areas of 1444.9 m2 ⋅ g−1 and 1014.6 m2 ⋅ g−1. The CO2 uptakes at 273 K are 62.1 cm3 ⋅ g−1 and 52.4 cm3 ⋅ g−1 at a pressure of 100 KPa. The saturated iodine vapor static uptakes at 348 K are 3.9 g ⋅ g−1 and 3.5 g ⋅ g−1. The adsorption capacity of C4A‐TAPA for SO2 reaches to 124.4 cm3 ⋅ g−1 at 298 K and 1.3 bar. Additionally, the adsorption capacities of C4A‐TAPA for C2H2, C2H4, and C2H6 were evaluated.
Two octahedral porous organic cages with a significantly high specific surface area have been synthesized and their potential application in gas adsorption investigated by evaluating their capacity to adsorb SO2, CO2, C2H2, C2H4, and C2H6. They also proved successful in efficiently adsorbing static iodine (I2) vapor.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
In the past few decades, there has been a wide research interest in titanium dioxide (TiO
2
) nanomaterials due to their applications in photocatalytic hydrogen generation and environmental pollution ...removal. Improving the optical absorption properties of TiO
2
nanomaterials has been successfully demonstrated to enhance their photocatalytic activities, especially in the report of black TiO
2
nanoparticles. The recent progress in the investigation of black TiO
2
nanomaterials has been reviewed here, and special emphasis has been given on their fabrication methods along with their various chemical/physical properties and applications.
Recent progress in the preparation, properties and applications of black TiO
2
nanomaterials is reviewed.
Particle swarm optimization (PSO) is a population-based stochastic optimization algorithm motivated by intelligent collective behavior of some animals such as flocks of birds or schools of fish. ...Since presented in 1995, it has experienced a multitude of enhancements. As researchers have learned about the technique, they derived new versions aiming to different demands, developed new applications in a host of areas, published theoretical studies of the effects of the various parameters and proposed many variants of the algorithm. This paper introduces its origin and background and carries out the theory analysis of the PSO. Then, we analyze its present situation of research and application in algorithm structure, parameter selection, topology structure, discrete PSO algorithm and parallel PSO algorithm, multi-objective optimization PSO and its engineering applications. Finally, the existing problems are analyzed and future research directions are presented.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OBVAL, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
The efficient removal of radioactive uranium from aqueous solution is of great significance for the safe and sustainable development of nuclear power. An ultrathin 2D metal–organic framework (MOF) ...nanosheet with cavity structures was elaborately fabricated based on a calix4arene ligand. Incorporating the permanent cavity structures on MOF nanosheet can fully utilize its structural characteristics of largely exposed surface area and accessible adsorption sites in pollutant removal, achieving ultrafast adsorption kinetics, and the functionalized cavity structure would endow the MOF nanosheets with the ability to achieve preconcentration and extraction of uranium from aqueous solution, affording ultrahigh removal efficiency even in ultra‐low concentrations. Thus, more than 97% uranium can be removed from the concentration range of 50–500 µg L−1 within 5 min. Moreover, the 2D nano‐material exhibits ultra‐high anti‐interference ability, which can efficiently remove uranium from groundwater and seawater. The adsorption mechanism was investigated by X‐ray photoelectron spectroscopy (XPS), Fourier transform infrared (FT‐IR) analysis, and density functional theory (DFT) calculations, which revealed that the cavity structure plays an important role in uranium capture. This study not only realizes highly efficient uranium removal from aqueous solution but also opens the door to achieving ultrathin MOF nanosheets with cavity structures, which will greatly expand the applications of MOF nanosheets.
A carboxylate‐functionalized 2D metal–organic framework (MOF) nanosheet with cage‐like cavities was constructed based on the calix4arene, which not only facilitates MOF exfoliation and pollutant capture but also prevents pollutant desorption. The as‐synthesized MOF nanosheets show an ultrahigh selectivity and anti‐interference performance for uranium.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
![Synthesis of Calix[4]arene‐...](http://api.summon.serialssolutions.com/2.0.0/image/issn/XR4PS5YY4K/0947-6539/small "Synthesis of Calix[4]arene‐Based Porous Organic Cages and Their Gas Adsorption")
