Enhanced Sunscreen Effects via Layer-By-Layer Self-Assembly of Chitosan/Sodium Alginate/Calcium Chloride/EHA

The sunscreen nanocapsules were successfully synthesized by the way of layer-by-layer self-assembly using charged droplets (prepared by emulsification of LAD-30, Tween-80 and EHA (2-Ethylhexyl-4-dimethylaminobenzoate)) as templates. Chitosan/sodium alginate/calcium chloride were selected as wall materials to wrap EHA. The emulsions with the ratio of Tween-80 to EHA (1:1) were stable. A stable NEI negative emulsion can be obtained when the ratio of Tween-80 and LAD-30 was 9:1. Chitosan solutions (50 kDa, 0.25 mg/mL) and sodium alginate solutions (0.5 mg/mL) were selected to prepare nanocapsules. The nanocapsules were characterized via some physico-chemical methods. Based on the synergistic effects of the electrostatic interaction between wall materials and emulsifiers, EHA was effectively encapsulated. DLS and TEM showed that the sunscreen nanocapsules were dispersed in a spherical shape with nano-size, with the increasing number of assembly layers, the size increased from 155 nm (NEI) to 189 nm (NEII) to 201 nm (NEIII) and 205 nm after solidification. The release studies in vitro showed sustained release behavior of the nanocapsules were observed with the increase of the number of deposition layers, implying a good coating effect. The sunscreen nanocapsules could control less than 50% the release of EHA after crosslinking of calcium chloride and sodium alginate, which also could effectively avoid the stimulation of the sun protection agent on the skin.     

Highly effective and chemoselective hydrodeoxygenation of aromatic alcohols

Effective hydrodeoxygenation (HDO) of aromatic alcohols is very attractive in both conventional organic synthesis and upgrading of biomass-derived molecules, but the selectivity of this reaction is usually low because of the competitive hydrogenation of the unsaturated aromatic ring and the hydroxyl group. The high activity of noble metal-based catalysts often leads to undesired side reactions (e.g., saturation of the aromatic ring) and excessive hydrogen consumption. Non-noble metal-based catalysts suffer from unsatisfied activity and selectivity and often require harsh reaction conditions. Herein, for the first time, we report chemoselective HDO of various aromatic alcohols with excellent selectivity, using porous carbon–nitrogen hybrid material-supported Co catalysts. The C–OH bonds were selectively cleaved while leaving the aromatic moiety intact, and in most cases the yields of targeted compounds reached above 99% and the catalyst could be readily recycled. Nitrogen doping on the carbon skeleton of the catalyst support (C–N matrix) significantly improved the yield of the targeted product. The presence of large pores and a high surface area also improved the catalyst efficiency. This work opens the way for efficient and selective HDO reactions of aromatic alcohols using non-noble metal catalysts.

Porous carbon–nitrogen hybrid material-supported Co catalysts can effectively promote the chemoselective hydrodeoxygenation reaction of a various of aromatic alcohols in ethanol and hydrogen atmosphere, under relatively mild conditions.     

Palladium-catalyzed hydrosilylation of ynones to access silicon-stereogenic silylenones by stereospecific aromatic interaction-assisted Si–H activation

Hydrosilylation is one of the most important reactions in synthetic chemistry and ranks as a fundamental method to access organosilicon compounds in industrial and academic processes. However, the enantioselective construction of chiral-at-silicon compounds via catalytic asymmetric hydrosilylation remained limited and difficult. Here we report a highly enantioselective hydrosilylation of ynones, a type of carbonyl-activated alkynes, using a palladium catalyst with a chiral binaphthyl phosphoramidite ligand. The stereospecific hydrosilylation of ynones affords a series of silicon-stereogenic silylenones with up to 94% yield, 20:1 regioselectivity and 98:2 enantioselectivity. The density functional theory(DFT) calculations were conducted to elucidate the reaction mechanism and origin of high degree of stereoselectivity, in which the powerful potential of aromatic interaction in this reaction is highlighted by the multiple C–H-π interaction and aromatic cavity-oriented enantioselectivitydetermining step during desymmetric functionalization of Si–H bond.     

A Novel Method for Pattern Recognition of GIS Partial Discharge via Multi-Information Ensemble Learning

Partial discharge (PD) is the main feature that effectively reflects the internal insulation defects of gas-insulated switchgear (GIS). It is of great significance to diagnose the types of insulation faults by recognizing PD to ensure the normal operation of GIS. However, the traditional diagnosis method based on single feature information analysis has a low recognition accuracy of PD, and there are great differences in the diagnosis effect of various insulation defects. To make the most of the rich insulation state information contained in PD, we propose a novel multi-information ensemble learning for PD pattern recognition. First, the ultra-high frequency and ultrasonic data of PD under four typical defects of GIS are obtained through experiment. Then the deep residual convolution neural network is used to automatically extract discriminative features. Finally, multi-information ensemble learning is used to classify PD types at the decision level, which can complement the shortcomings of the independent recognition of the two types of feature information and has higher accuracy and reliability. Experiments show that the accuracy of the proposed method can reach 97.500%, which greatly improves the diagnosis accuracy of various insulation defects.     

Domain Adaptation with Data Uncertainty Measure Based on Evidence Theory

Domain adaptation aims to learn a classifier for a target domain task by using related labeled data from the source domain. Because source domain data and target domain task may be mismatched, there is an uncertainty of source domain data with respect to the target domain task. Ignoring the uncertainty may lead to models with unreliable and suboptimal classification results for the target domain task. However, most previous works focus on reducing the gap in data distribution between the source and target domains. They do not consider the uncertainty of source domain data about the target domain task and cannot apply the uncertainty to learn an adaptive classifier. Aimed at this problem, we revisit the domain adaptation from source domain data uncertainty based on evidence theory and thereby devise an adaptive classifier with the uncertainty measure. Based on evidence theory, we first design an evidence net to estimate the uncertainty of source domain data about the target domain task. Second, we design a general loss function with the uncertainty measure for the adaptive classifier and extend the loss function to support vector machine. Finally, numerical experiments on simulation datasets and real-world applications are given to comprehensively demonstrate the effectiveness of the adaptive classifier with the uncertainty measure.     

Structural and Bonding Properties of AlnC4-/0 (n=2-4) Clusters:Anion Photoelectron Spectroscopy and Theoretical Calculations

We measured the photoelectron spectra of AlnC4-(n=2-4) clusters by using size-selected anion photoelectron spectroscopy.The structures of AlnC4-/0 (n=2-4) clust...     

A Novel Gelatin-Based Sustained-Release Molluscicide for Control of the Invasive Agricultural Pest and Disease Vector Pomacea canaliculata

Pomacea canaliculata, one of the 100 most destructive invasive species in the world, and it is an important intermediate host of Angiostrongylus cantonensis. The molluscicides in current use are an effective method for controlling snails. However, most molluscicides have no slow-release effect and are toxic to nontarget organisms. Thus, these molluscicides cannot be used on a large scale to effectively act on snails. In this study, gelatin, a safe and nontoxic substance, was combined with sustained-release molluscicide and was found to reduce the toxicity of niclosamide to nontarget organisms. We assessed the effects of gelatin and molluscicide in controlling P. canaliculata snails and eggs. The results demonstrated that the niclosamide retention time with 1.0% and 1.5% gelatin sustained-release agents reached 20 days. Additionally, the mortality rate of P. canaliculata and their eggs increased as the concentration of the niclosamide sustained-release agents increased. The adult mortality rate of P. canaliculata reached 50% after the snails were exposed to gelatin with 0.1 mg/L niclosamide for 48 h. The hatching rate of P. canaliculata was only 28.5% of the normal group after the treatment was applied. The sustained-release molluscicide at this concentration was less toxic to zebrafish, which means that this molluscicide can increase the safety of niclosamide to control P. canaliculata in aquatic environments. In this study, we explored the safety of using niclosamide sustained-release agents with gelatin against P. canaliculata. The results suggest that gelatin is an ideal sustained-release agent that can provide a foundation for subsequent improvements in control of P. canaliculata.     

Rutin Inhibits Ox-LDL-Mediated Macrophage Inflammation and Foam Cell Formation by Inducing Autophagy and Modulating PI3K/ATK Signaling

Atherosclerosis (AS) is one of the leading causes of death among the elderly, and is primarily caused by foam cell generation and macrophage inflammation. Rutin is an anti-inflammatory, anti-oxidant, anti-allergic, and antiviral flavonoid molecule, known to have anti-atherosclerotic and autophagy-inducing properties, but its biological mechanism remains poorly understood. In this study, we uncovered that rutin could suppress the generation of inflammatory factors and reactive oxygen species (ROS) in ox-LDL-induced M2 macrophages and enhance their polarization. Moreover, rutin could decrease foam cell production, as shown by oil red O staining. In addition, rutin could increase the number of autophagosomes and the LC3II/I ratio, while lowering p62 expression. Furthermore, rutin could significantly inhibit the PI3K/ATK signaling pathway. In summary, rutin inhibits ox-LDL-mediated macrophage inflammation and foam cell formation by inducing autophagy and modulating PI3K/ATK signaling, showing potential in treating atherosclerosis.     

A new inorganic–organic hybrid compound constructed from polyoxoanions and rare earth coordination complexes

A new chainlike polymer, Na[Ce(dipic)(H₂O)₃]₂ [CrMo₆H₆O₂₄] · 13H₂O (H₂dipic = pyridine-2,6-dicarboxylic acid) (1), has been synthesized and characterized by elemental analysis; IR and XPS spectroscopy, TG analysis, and single-crystal X-ray diffraction. Compound (1) is built up of Anderon-type polyoxoanions as structural motifs and cerium–dipic coordination fragments as linkers to yield an unprecedented one-dimensional chain. Such chains are further in close contact forming a three-dimensional supramolecular framework with channels via extensive hydrogen-bonding interactions among polyoxoanions, dipic ligands and water molecules. Furthermore, the magnetic properties of compound (1) have been studied by measuring their magnetic susceptibility in the temperature range 2–300 K.     

Two new hydrogen bond-supported supramolecular compounds assembly from polyoxovanadate and organoamines

Two novel organic-inorganic hybrid compounds based on organoamines and polyoxovanadates formulated as (H₂dien)₄[H₁₀V₁₈O₄₂(PO₄)](PO₄)·2H₂O (1) (dien=diethylenetriamine) and (Him)₈[HV₁₈O₄₂(PO₄)] (2) (im=imidazole) have been prepared under hydrothermal conditions by using different starting materials, and characterized by elemental analyses, IR, ESR, XPS, TGA and single-crystal X-ray diffraction analyses. Crystal data for compound 1: C₁₆H₇₄N₁₂O₅₂V₁₈P₂, Monoclinic, space group C2/c, a=23.9593(4) Å, b=13.0098(2) Å, c=20.1703(4) Å, β=105.566(3)°, V=6056.6(19) Å³, Z=4; for compound 2, C₂₄H₄₁N₁₆O₄₆V₁₈P, Tetragonal, space group I4/mmm, a=13.5154(8) Å, b=13.5154(8) Å, c=19.1136 Å, β=90°, V=3491.4(3) Å³, Z=2. Compound 1 consists of protonated diens together with polyoxovanadates [H₁₀V₁₈O₄₂(PO₄)]⁵⁻. Compound 2 is composed of protonated ims and polyoxovanadates [HV₁₈O₄₂(PO₄)]⁸⁻. There are hydrogen-bonding interactions between polyoxovanadates and different organoamines in 1 and 2. Polyoxovanadates are linked through H₂dien into a three-dimensional network via hydrogen bonds in 1, while polyoxovanadates are linked by Him into a two-dimensional layer network via hydrogen bonds in 2. The crystal packing patterns of the two compounds reveal various supramolecular frameworks.