Radiofrequency ablation of the great saphenous vein demonstrated a high occlusion rate at 5 years of follow-up, and significantly reduced the severity of venous disease and improved patient quality of life in this retrospective study of 1300 patients.
In this work, iron-doped graphite carbon nitride (Fe-g-C3N4) was integrated with CoMoO4 through a simple hydrothermal route and high temperature calcination to synthesize distinctive composites, aiming to create a promising heterogeneous catalyst to active peroxymonosulfate (PMS) for the degradation of methylene blue (MB), a widely used organic dye. The characterization results, including SEM, EDX, FTIR, XRD and XPS, indicated that the crystal structure and physicochemical properties of CoMoO4-Fe-g-C3N4 have changed after modification, with rougher surface and efficient catalytic activity. The effects of several operational factors (catalyst dosage, oxidant dosage, reaction temperature and initial pH) were also extensively evaluated. Under the condition of CoMoO4-Fe-g-C3N4=0.1 g L−1, oxidant = 2.0 mM, dye = 100 mg/L, T = 25 °C, the MB in the CoMoO4-Fe-g-C3N4/PMS catalytic system can reach almost complete degradation in 90 minutes without pH adjustment. Further, stability experiment showed that the CoMoO4-Fe-g-C3N4 catalysts exhibited high stability and superior reusability, with 80% removal rate even after five concessive cycles of use. Additionally, through radical quenching experiments, it proved that SO4•− radicals were dominant and HO• radicals also worked in the MB degradation process. An underlying mechanism was proposed based on the detection of XPS results that both radical and non-radical degradation pathways existed during MB degradation process. The electron transfer from high-valence iron species (FeIV=O) to MB resulting in the degradation of MB through a non-radical mechanism. From the investigation, the CoMoO4-Fe-g-C3N4 composite was proved to have potential superiority as a promising catalyst for the degradation of refractory organic contaminant removal from water.
Various substituted aryl-pyridyl ketones were hydrogenated in the presence of Ru-XylSunPhos-Daipen bifunctional catalytic system with enantiomeric excesses up to 99.5%. Upon introduction of a readily removable ortho-bromo atom to the phenyl ring, enantiomerically enriched 4-chlorophenylpyridylmethanol was obtained by hydrogenation method with 97.3% ee, which provided an important chiral intermediate for some histamine H(1) antagonists.
Smart technology for textiles and clothing - an overview and review. Electrically active polymer materials: application of non-ionic polymer gel and elastomers for artificial muscles. Heat storage and thermo-regulated textiles and clothing. Thermally sensitive materials. Cross-linked polyol fibrous substrates as multifunctional and multi-use intelligent materials. Stimuli-responsive interpenetrating polymer network hydrogels composed of poly(vinyl alcohol) and poly(acrylic acid. Permeation control through stimuli-responsive polymer membrane prepared by plasma and radiation grafting techniques. Mechanical properties of fibre Bragg gratings. Optical responses of FBG sensors under deformations. Smart textile composites integrated with fibre optic sensors. Hollow fibre membranes for gas separation. Embroidery and smart textiles. Adaptive and responsive textile structures (ARTS. Wearable technology for snow clothing. Bio-processing for smart textiles and clothing. Tailor-made intelligent polymers for biomedical applications. Textile scaffolds in tissue engineering.
A series of 3-oxoglutaric acid derivatives have been hydrogenated in different solvents in the presence of [RuCl(benzene)(S)-SunPhos]Cl (SunPhos = (2,2,2',2'-tetramethyl-[4,4'-bibenzo[d][1,3]dioxole]-5,5'-diyl)bis(diphenylphosphine)). Unlike simple β-keto acid derivatives, these advanced analogues can be readily hydrogenated in uncommon solvents such as THF, CH(2)Cl(2), acetone, and dioxane with high enantioselectivities. Two possible catalytic cycles have been proposed to explain the different reactivities of these 1,3,5-tricarbonyl substrates in the tested solvents. The C-2 and C-4 substituents had notable but irregular influence on the reactivity and enantioselectivity of the reactions. More pronounced solvent effects were observed: the ee values increased from around 20% in EtOH or THF to 90% in acetone. Inversion of the product configuration was observed when the solvent was changed from EtOH to THF or acetone, and a mixed solvent system can lead to better enantioselectivity than a single solvent.
Abstract Perovskite based on Sn have attracted extensive attention to address the toxicity challenge associated with Pb‐based perovskite solar cells. However, Sn‐based perovskite solar cells（SPSCs）are notable for their poor stability and loss of efficiency due to rapid oxidation of Sn 2+ to Sn 4+ in air. To slow down the rapid oxidation, a number of antioxidants are suggested. Nevertheless, the antioxidant normally gets oxidized to non‐antioxidizing by‐products in a single‐stage redox reaction and loses the function of oxidation prevention. Herein, vanillin is introduced, a natural antioxidant with a double‐staged redox reaction to inhibit the oxidation of Sn 2+ or reduce Sn 4+ back to Sn 2+ , which improves the efficiency and prolongs the open‐air stability of SPSCs. With 7.5% vanillin doping, an outstanding efficiency of 13.18% is achieved. Moreover, exposure of the solar cell to 160 W microwave irradiation for 3 minutes resulted in significant efficiency recovery from 88% to 96.5% at 812 hours and from 35.7% to 65.4% after 2200 hours of aging. This work reveals the potential of natural antioxidation and short microwave irradiation as suitable approaches to elevate the efficiency and lifetime of SPSCs.
Data-driven method for Structural Health Monitoring (SHM), that mine the hidden structural performance from the correlations among monitored time series data, has received widely concerns recently. However, missing data significantly impacts the conduction of this method. Missing data is a frequently encountered issue in time series data in SHM and many other real-world applications, that harms to the standardized data mining and downstream tasks, such as condition assessment. Imputation approaches based on spatiotemporal relations among monitoring data are developed to handle this issue, however, no additional information is added during imputation. This paper thus develops a robust method for damage identification that considers the missing data occasions, based on long-short term memory (LSTM) model and dropout mechanism in the autoencoder (AE) framework. Inputs channels are randomly dropped to simulate the missing data in training, and reconstruction errors are used as the loss function and the damage indicator. Quasi-static response (cable tension) of a cable-stayed bridge released in 1st IPC-SHM is employed to verify this proposed method, and results show that the missing data imputation and damage identification can be implemented together in a unified way.
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