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As the information era develops rapidly, it's common to utilize multiple features from different sources to represent one object. Measuring the similarity between multi-view objects is the fundamental task in multi-view learning. To effectively measure the similarity between multi-view samples, multi-view metric learning has gained extensive attention recently. Nevertheless, most existing methods merely focus on the closeness of similar pairs and the separability of dissimilar ones inside each view, so that rich consensus properties existing in multi-views data might be ignored to some extent. To mitigate this issue, we come up with a novel method entitled Hierarchical Multi-view Metric learning with HSIC regularization (HM2H). HM2H aims to simultaneously maintain the closeness of similar points and the separability of dissimilar ones in intra-view and inter-view. Since multiple views depict different perspectives of the same object, the shared metric is introduced to capture the consensus information among those views. Moreover, we take advantage of the Hilbert–Schmidt Independence Criterion to seek the maximum distribution agreement of the multi-view dataset. Correspondingly, an algorithm based on Alternating Direction Method is provided to solve the proposed HM2H. Finally, various experimental results on five visual recognition datasets confirm the effectiveness and feasibility of our proposed method. [ABSTRACT FROM AUTHOR]

Deng, H.Y.; Dai, G.L., and Azadi, M.R., 2020. Fractional time-dependent merchant model for coastal soft clay. In: Guido Aldana, P.A. and Kantamaneni, K. (eds.), Advances in Water Resources, Coastal Management, and Marine Science Technology. Journal of Coastal Research, Special Issue No. 104, pp. 825–831. Coconut Creek (Florida), ISSN 0749-0208. Soft clayey soils behave a time-dependent creep property subjected to sustained load. In order to describe the stress-strain-time property of soft clayey soil, a time-based fractional creep constitutive model is proposed based on the Caputo fractional calculus by applying the Abel dashpot in classical component model. The proposed fractional Merchant model is validated by drained creep test of coastal soft clay. The model parameters are obtained by fractional nonlinear fitting in terms of drained creep test results of coastal soft clay. Then the predicted results by the proposed fractional Merchant model and classical component models are also compared and validated with creep test results. It shows that the proposed fractional Merchant model is more approached to drained creep test results than classical component models. In particular, the proposed fractional Merchant model could well reduce the errors in the initial phase of creep compared with the classical model. It is indicated that the fractional Merchant model is superior in predicting drained creep property of coastal soft clay. [ABSTRACT FROM AUTHOR]

The development of metal-free catalysts with excellent reusability and the research of effects for carbon network structures in activation process are great challenges in non-metallic catalysis today. In this study, a regenerated metal-free biochar (Re-TBC-800) was prepared by pyrolyzing multi-use black tea biochar (TBC-800) to activate peroxymonosulfate (PMS) for cycling degradation of naproxen (NPX) up to 48 times (only 6 times before regeneration). It was demonstrated by Raman and DFT calculations that the rearrangement of carbon networks during thermal regeneration resulted in the formation of a higher conjugated structure. After regeneration, C−O changed from electron acceptor to electron donor to achieve self-cycling between C=O and C−O. The reaction pathways changed from a non-radical (1O 2 and electron transfer) effect to a synergistic (•OH, SO 4 •−, 1O 2 and electron transfer) effect. Re-TBC-800 provided new insights into the structural design of functional catalysts. [Display omitted] • The thermally regenerated black tea residue biochar could cyclically degrade naproxen for 48 times. • 1O 2 ,.•OH, SO 4 •− and electron transfer worked together in Re-TBC-800/PMS system. • The thermal regeneration led to the formation of highly conjugated structures. • The highly conjugated structures changed the direction of OFGs to transfer electrons. • Self-cycling between C=O and C−O increased the reusability of Re-TBC-800 after regeneration. [ABSTRACT FROM AUTHOR]

In this work, waste herb senna obtusifolia was utilized as the biochar precursor, and a N-doped biochar (NSOBC-6) was prepared to activate peroxymonosulfate (PMS) for degrading Naproxen (NPX). NSOBC-6 exhibited superior catalytic performance in activating PMS, which could degrade NPX completely within 60 min. The NSOBC-6/PMS system also had good reusability and effectiveness under a wide range of pH values and high salinity conditions. The significant contribution of singlet oxygen (1O 2) and superoxide radicals (O 2 •−) in NPX degradation was revealed. The results of XPS and DFT calculations indicated C=O, pyridinic-N and graphitic-N participated as catalytic sites in the degradation of NPX. The differences in electron density and the E LUMO -E HOMO (ΔE LUMO-HOMO) gap were induced by N doping, enhancing the PMS activation capacity of NSOBC-6. This work presented a strategy to convert waste herbal into functional biochar materials, which was of great significance for the development of green and efficient catalysts. [Display omitted] • N-doped waste herb (Senna Obtusifolia) biochar was prepared by single-step pyrolysis method. • Doping of heteroatoms N significantly enhanced the catalytic activity of SOBC. • 1O 2 and O 2 •− instead of SO 4 •− and •OH were dominant ROS in the NSOBC-6/PMS system. • The synergistic effect of carbonyl and N sites played a crucial role in the NSOBC-6/PMS system by DFT calculations. • The degradation pathways of NPX were predicted by DFT calculations and UPLC-MS. [ABSTRACT FROM AUTHOR]

Investigating the effects of g–C 3 N 4 –based photocatalysts on experimental parameters during tetracycline (TC) degradation can be helpful in discovering the optimal parameter combinations to improve the degradation efficiencies in general. Machine learning methods can avoid the problems of high cost, time-consuming and possible instrumental errors in experimental methods, which have been proven to be an effective alternative for evaluating the entire experimental process. Eight typical machine learning models were explored for their effectiveness in predicting the TC degradation efficiencies of g-C 3 N 4 based photocatalysts. XGBoost (XGB) was the most reliable model with R2, RMSE and MAE values of 0.985, 4.167 and 2.900, respectively. In addition, XGB's feature importance and SHAP method were used to rank the importance of features to provide interpretability to the results. This study provided a new idea for developing g–C 3 N 4 –based photocatalysts for TC degradation and intelligent algorithms for predicting the photocatalytic activity of g–C 3 N 4 –based photocatalysts. [Display omitted] • Eight typical machine learning models were applied to predict the photodegradation of TC. • 431 data points related to the photodegradation percentage of different g–C 3 N 4 –based catalysts were used. • The g-C 3 N 4 catalyst properties and five photocatalytic conditions were selected as inputs. • XGBoost showed the best fit among all models. [ABSTRACT FROM AUTHOR]

[Display omitted] • Advances in salt-free electrolytes in electrochemical reduction CO 2 /O 2 are summarized. • Both H 2 O 2 production by power consuming mode (2e--ORR), or H 2 /O 2 fuel-cell are included. • Diverse roles of solid electrolytes have been reviewed. • Both roles and mechanism of solid electrolytes are included. Electrochemical conversion of abundant CO 2 /O 2 into value-added products and fuels holds great promise to achieve sustainable energy systems. In most cases, aqueous electrolyte containing salts are used, inevitably suffering subsequent purification if pure products needed for further purpose. Instead, the application of solid electrolyte has seen a booming and that thought to be commercially attractive. Nevertheless, there is a scarcity of comprehensive reviews focusing exclusively on the application of solid electrolytes in electrochemical CO 2 /O 2 reduction, in contrast to the more readily available reviews on battery technologies. In this manner, we review recent advance and challenges in the understanding electrochemical reduction of CO 2 /O 2 using solid electrolytes to produce high valuable chemicals like H 2 O 2 , formic acid, etc. It begins with a brief introduction of historical development of solid electrolyte and their properties. Then it followed with summarizing of its application used in oxygen reduction reaction (ORR) by power consuming mode (2e--ORR), or by power generating mode in fuel-cell. Afterward, diverse type of solid electrolytes has been systemically reviewed, including the corresponding cells, the production rate along with different roles in electrochemical CO 2 reduction. Finally, challenges and prospects of solid electrolytes are discussed, aiming to guide a promising direction for directly producing high-value chemicals in near future. [ABSTRACT FROM AUTHOR]

Sludge biochar (SBC) modified by humic acid (HA) was used to activate peroxymonosulfate (PMS) for degrading naproxen (NPX). HA-modified biochar (SBC-50HA) boosted the catalytic performance of SBC for PMS activation. The SBC-50HA/PMS system had good reusability and structural stability, and was unaffected by complex water bodies. The results of Fourier transform infrared (FTIR) and X-ray diffraction spectroscopy (XPS) indicated that graphitic carbon (C C), graphitic N, and C–O on SBC-50HA played a vital part on the removal of NPX. The key role of non-radical pathways such as singlet oxygen (1O 2) and electron transfer in the SBC-50HA/PMS/NPX system was verified by inhibition experiments, electron paramagnetic resonance (EPR), electrochemistry, and PMS consumption. The possible degradation pathway of NPX was proposed by density functional theory (DFT) calculations, and the toxicity of NPX and its degradation intermediates were evaluated. [Display omitted] • SBC was modified by Humic acid (HA) to enhance its catalytic ability. • C C, graphitic N, and C–O on SBC-50HA played an important role in the catalytic process. • The removal of NPX was attributed to singlet oxygen (1O 2) and electron transfer. • The possible degradation pathway of NPX was investigated by density functional theory (DFT) calculations. [ABSTRACT FROM AUTHOR]

[Display omitted] • Sludge-bagasse mixed biochar (SB-BC-900) exhibited its outstanding catalytic performance. • Singlet oxygen (1O 2) was the main reactive oxygen species. • Graphitic carbon (sp2 C=C) and oxygenated functional groups (OFGs) played a significant role in the SB-BC-900/PMS system. • The enhanced mechanism was elucidated by density functional theory (DFT). The exploitation of cost-effective and environmentally friendly biochar catalysts is of major importance for the oxidative treatment of toxic organic wastewater and the resource utilization of waste biomass. In this work, sewage sludge and bagasse waste were co-pyrolyzed into a novel biochar catalyst (SB-BC-900) for efficiently activating peroxymonosulfate (PMS) to degrade bisphenol AF (BPAF) in wastewater. Compared with single sludge biochar (S-BC-900), SB-BC-900 had a larger cumulative pore volume, more oxygenated functional groups (OFGs) and higher graphitization degree, with a significantly higher catalytic capacity. SB-BC-900 enabled rapid degradation of BPAF within 10 min at a low PMS dosage (molar ratio [PMS]: [BPAF] = 2.67:1). There was mainly the non-free radical pathway dominated by singlet oxygen (1O 2) in the SB-BC-900/PMS system. Graphitic carbon (sp2 C=C) and OFGs on SB-BC-900 played a crucial part in the catalytic degradation of BPAF. A green approach is provided to resource waste biomass for efficient wastewater treatment in this work. [ABSTRACT FROM AUTHOR]