Photoresponsive metal–organic frameworks (PMOFs) are of interest for tailorable CO2 adsorption. However, modulation of CO2 adsorption on PMOFs is based on steric hindrance or structural change owing ...to weak interactions between CO2 and active sites. It is challenging to fabricate PMOFs with strong but tailorable sites for CO2 adsorption. Now, the construction of PMOFs with target‐specific (strong) active sites is achieved by introducing tetraethylenepentamine into azobenzene‐functionalized MOFs for tailorable CO2 adsorption. Amines are specific active sites for CO2, contributing to capture CO2 selectively. Cis/trans isomerization of azobenzene motifs trigged by UV/Vis light adjusts the electrostatic potential of amines significantly, leading to exposure/shelter of amines and modulation of CO2 adsorption on strong active sites. This system enables us to design adsorption processes for CO2 capture from mixtures, which is impossible to realize by traditional PMOFs.
Smart adsorbents were fabricated by introducing target‐specific active sites (amines) into photoresponsive metal–organic frameworks (PMOFs). The cis/trans isomerization of azobenzene motifs trigged by UV/Vis light irradiation adjusts the electrostatic potential of amines significantly. This leads to exposure/shelter of amines and successful modulation of CO2 adsorption on strong active sites, which is impossible to realize by traditional PMOFs.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
AbstractThe delineation of vertical geological cross-sections is an essential task in geotechnical site characterization and has a profound impact on subsequent geotechnical designs and analyses. It ...is a long-lasting challenge, particularly for complex geological settings, to properly produce a subsurface geological cross-section from limited boreholes that are usually encountered in engineering practice. Emerging machine learning methods, such as the convolutional neural network (CNN), provide a fresh perspective of this challenge and effective alternatives for exploiting the complex stratigraphic relationships between different soil deposits. In this study, a novel iterative convolution eXtreme Gradient Boosting model (IC-XGBoost) is proposed. This model interpolates a subsurface geological cross-section from limited site-specific boreholes and a training geological cross-section obtained from previous projects with similar geological settings. This direct application of previous geological cross-sections for training is based on the assumption of similar local spatial connectivity or stratigraphic relationships between soils in areas with similar geological settings. The proposed method can learn stratigraphic patterns from a training image in an automatic manner. In addition, the proposed method is purely data-driven and does not require the specification of any parametric function form. The model performance is illustrated using both a simulated example and real data from a tunnel project in Australia. The proposed method not only infers the most probable geological cross-section but also quantifies the associated interpolation uncertainty from multiple realizations. The effect of the borehole number on the interpolation performance is also explicitly investigated.
An essential task in many geotechnical projects is delineation of subsurface soil stratigraphy from scatter measurements. Geotechnical engineers often use their knowledge on local geology and ...interpret soil strata boundaries by linear interpolation of measured data. This usual practice may encounter difficulties when interpreting complex deposits, particularly when measurements are limited. In this study, a novel nonparametric, data-driven method based on multiple point statistics (MPS) is proposed to interpolate subsurface soil stratigraphy from sparse measurements. MPS may be formulated as Bayesian supervised machine learning, which adaptively learns high-order spatial information (e.g., curvilinear features of soil layers) using sparse measurements obtained in a specific site and training image that reflects pre-existing engineering knowledge on similar geological settings. The proposed method is the first ever purely data-driven method (i.e., without using any pre-specified parametric functions) for geotechnical site characterization. The proposed method is illustrated by a simulated example and real data from a reclamation site in Hong Kong. The proposed method not only accurately interpolates the subsurface soil stratigraphy from sparse measurements, but also quantifies uncertainty associated with the interpolation. Effects of governing parameters in the proposed method are explicitly investigated, and parameters appropriate for subsurface soil stratigraphy are identified.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
A series f=∑n=0∞a(n)qn is lacunary if the set of n for which a(n)=0 has density 1. We say f is well lacunary if f is lacunary and a(n) assumes every integer value infinitely often. A well-known ...theorem of Deligne and Serre states that each modular form of weight one is lacunary. In this paper, we show that each modular form of weight one is well lacunary provided that certain special values can be attained. We also construct a family of well lacunary series via binary quadratic forms.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
The carbene and photocatalyst co-catalyzed radical coupling of acyl electrophile and a radical precursor is emerging as attractive method for ketone synthesis. However, previous reports mainly ...limited to prefunctionalized radical precursors and two-component coupling. Herein, an N-heterocyclic carbene and photocatalyst catalyzed decarboxylative radical coupling of carboxylic acids and acyl imidazoles is disclosed, in which the carboxylic acids are directly used as radical precursors. The acyl imidazoles could also be generated in situ by reaction of a carboxylic acid with CDI thus furnishing a formally decarboxylative coupling of two carboxylic acids. In addition, the reaction is successfully extended to three-component coupling by using alkene as a third coupling partner via a radical relay process. The mild conditions, operational simplicity, and use of carboxylic acids as the reacting partners make our method a powerful strategy for construction of complex ketones from readily available starting materials, and late-stage modification of natural products and medicines.
Industrialized society-caused dysregular human behaviors and activities such as overworking, excessive dietary intake, and sleep deprivation lead to perturbations in the metabolism and the ...development of metabolic syndrome. Non-alcoholic fatty liver disease (NAFLD), the most common chronic liver disease worldwide, affects around 30% and 25% of people in Western and Asian countries, respectively, which leads to numerous medical costs annually. Insulin resistance is the major hallmark of NAFLD and is crucial in the pathogenesis and for the progression from NAFLD to non-alcoholic steatohepatitis (NASH). Excessive dietary intake of saturated fats and carbohydrate-enriched foods contributes to both insulin resistance and NAFLD. Once NAFLD is established, insulin resistance can promote the progression to the more severe state of liver endangerment like NASH. Here, we review current and potential studies for understanding the complexity between insulin-regulated glycolytic and lipogenic homeostasis and the underlying causes of NAFLD. We discuss how disruption of the insulin signal is associated with various metabolic disorders of glucoses and lipids that constitute both the metabolic syndrome and NAFLD.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Axially chiral styrenes bearing a chiral axis between a sterically non-congested acyclic alkene and an aryl ring are difficult to prepare due to low rotational barrier of the axis. Disclosed here is ...an N-heterocyclic carbene (NHC) catalytic asymmetric solution to this problem. Our reaction involves ynals, sulfinic acids, and phenols as the substrates with an NHC as the catalyst. Key steps involve selective 1,4-addition of sulfinic anion to acetylenic acylazolium intermediate and sequential E-selective protonation to set up the chiral axis. Our reaction affords axially chiral styrenes bearing a chiral axis as the product with up to > 99:1 e.r., > 20:1 E/Z selectivity, and excellent yields. The sulfone and carboxylic ester moieties in our styrene products are common moieties in bioactive molecules and asymmetric catalysis.
Due to the wet and dynamic environment of the oral cavity, the healing of intraoral wounds, such as tooth extraction wounds, requires stable and firm wound dressings. In clinical practice, cotton ...balls and gauzes, sponge plugs, or sutures are used to treat extraction wounds, but none of these means can continuously isolate the wound from the intraoral environment and facilitate ideal healing conditions. Herein, inspired by the natural extracellular matrix, a family of wound dressings is developed for intraoral wound repair. Infiltrating a ductile long‐chain hydrogel network into a prefabricated, sturdy macromolecular meshwork and in situ crosslinking endowed the composite hydrogel with controllable swelling behaviors and robust mechanical properties. The macromolecular meshwork functioned as the backbone to support the composite and restricts the swelling of the long‐chain hydrogel network. In vitro tests verified that this wound dressing can provide durable protection for intraoral wounds against complex irritations. Furthermore, accelerated wound healing occurred when the wound dressing is applied in vivo on a canine tooth extraction model, due to the effective reduction of acute inflammation. These results suggest that this family of bioinspired hydrogels has great potential for application as intraoral wound dressing.
An extracellular matrix‐mimicking hydrogel wound dressing is designed as tooth extraction adhesive wound dressing for intraoral application. The hydrogel exhibits excellent anti‐swelling efficiency, along with consistent mechanical and adhesive robustness in aqueous environments. In vitro and in vivo tooth extraction models demonstrate the stability of hydrogels as physical and antibacterial barriers for intraoral wounds, leading to continuous protection and effective healing acceleration.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Tunable halofluoroalkylation and hydrofluoroalkylation of 1,6‐enynes were first reported by switching between copper‐catalysis and photocatalysis, leading to the atom‐economic and highly ...stereoselective protocols toward functionalized 1‐indenones with moderate to good yields. Copper‐catalysis enabled the concomitant incorporation of two important fluoroalkyl and halo functionalities into 1‐indenone skeleton, in which fluoroalkyl bromides were transformed into (E)‐1‐indenones as a major stereoisomer while fluoroalkyl iodides oriented complete Z‐selectivity to access (Z)‐1‐indenones. Specifically, photocatalysis allowed hydrofluoroalkylation of 1,6‐enynes to access fluoroalkylated (Z)‐1‐indenones under mild conditions, in which THF behaved as a hydrogen source. These two approaches feature remarkable compatibility with a wide variety of 1,6‐enynes and fluoroalkyl halides and excellent atomic utilization.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
•A data-driven method is proposed for development of 3D subsurface geological model.•Prior geological knowledge is combined with limited site-specific boreholes.•The method not only infers 3D model ...but also quantifies prediction uncertainty.•The predicted 3D geological model is represented as a point cloud for digital twin.
A digital twin is a digital replica or virtual representations of 3D physical entities in the real world. In practice, it is challenging for 3D modelling of subsurface stratigraphy in an underground digital twin due to insufficient site-specific measurements and a lack of efficient 3D spatial prediction tools. In this study, a data-driven and deep learning method, called IC-XGBoost3D, is proposed to build a 3D geological model from limited site-specific boreholes and 2D training images reflecting prior geological knowledge. Anisotropic stratigraphic relationships are learned from two perpendicular 2D training images, and the extracted stratigraphic statistics serve as the input for pre-training a 2D simulation slice. A sequence of 2D simulation slices is then simulated with constraints by site-specific boreholes and subsequently reassembled into a 3D geological model. Note that the parameters of the deep learning method are calibrated with site-specific data and prior training images before being applied to develop the geological model. The model performance is demonstrated and validated using an illustrative example. The proposed method can efficiently generate an anisotropic 3D geological model as a point cloud from two perpendicular training images and sparse boreholes with a high prediction accuracy. More importantly, the proposed method not only infers the most probable 3D geological domain, but also provides a quantitative evaluation of associated 3D stratigraphic uncertainty. Effects of irregular borehole spacing and single training image on the simulation performance are also investigated.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
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