Bond performance between NSM FRP rods and concrete using ECC as bonding materials

The pull-out test of near-surface-mounted (NSM) FRP (fiber-reinforced plastics) rod from concrete was performed using engineered cementitious composites (ECC) as bonding materials. The feasibility of cementitious materials in NSM FRP strengthened concrete was then analyzed. Carbon FRP (CFRP) rods and Basalt FRP (BFRP) rods with spiral surfaces and diameters of 8 mm were used in the test. The bonding lengths are 5 times and 10 times of the FRP diameter, respectively. Results show that the failure modes of all the specimens using ECC as bonding materials are pull-out of FRP rods with ductile behavior. Moreover, specimens with NSM FRP rods using epoxy are prepared as control specimens to evaluate the feasibility of ECC. For CFRP rods, the pull-out load-bearing capacity of specimens using ECC is 70% and 50% of that in specimens using epoxy for 5 times and 10 times of the FRP diameter, respectively. For BFRP rods, the load-bearing capacity of specimens using ECC is 75% and 55% of that in specimens using epoxy for 5 times and 10 times of the FRP diameter, respectively. Thus, ECC can be applied in NSM FRP strengthened concrete structures as the bonding materials

Coating titania nanoparticles with epoxy-containing catechol polymers via Cu(0)-living radical polymerization as intelligent enzyme carriers

Immobilization of enzyme could offer the biocatalyst with increased stability and important recoverability, which plays a vital role in the enzyme’s industrial applications. In this study, we present a new strategy to build an intelligent enzyme carrier by coating titania nanoparticles with thermoresponsive epoxy-functionalized polymers. Zero-valent copper-mediated living radical polymerization (Cu(0)-LRP) was utilized herein to copolymerize N-isopropylacrylamide (NIPAM) and glycidyl acrylate (GA) directly from an unprotected dopamine-functionalized initiator to obtain an epoxy-containing polymer with terminal anchor for the “grafting to” or “one-pot” modification of titania nanoparticles. A rhodamine B-labeled laccase has been subsequently used as a model enzyme for successful immobilization to yield an intelligent titania/laccase hybrid bifunctional catalyst. The immobilized laccase has shown excellent thermal stability under ambient or even relatively high temperature above the lower critical solution temperature (LCST) at which temperature the hybrid particles could be facilely recovered for reuse. The enzyme activity could be maintained during the repeated use after recovery and enzymatic degradation of bisphenol A was proven to be efficient. The photocatalytic ability of titania was also investigated by fast degradation of rhodamine B under the excitation of simulated sunlight. Therefore, this study has provided a facile strategy for the immobilization of metal oxide catalysts with enzymes, which constructs a novel bifunctional catalyst that will be promising for the “one-pot” degradation of different organic pollutants

Short-term PV power prediction based on the 24 traditional Chinese solar terms and adaboost-GA-BP model

High-precision, short-term power forecasting for photovoltaic systems not only reduces unnecessary energy consumption but also provides power grid security. To this end, in this paper we propose a photovoltaic short-term power forecasting model based on the division of data of the 24 traditional Chinese solar terms and the Adaboost-GA-BP model. The 24 solar terms were condensed from the laws of meteorology, phenology, and seasonal changes to adapt to agricultural times in ancient China and have become intangible cultural heritage. This article first analyzes the numerical characteristics of meteorological factors and demonstrates their close correlation with the turning points of the 24 solar terms. Second, using Standardized Euclidean Distance and Spearman’s Correlation Coefficients to analyze data similarity between the Gregorian half-months and the 24 solar terms divisions for comparative analysis purposes, it is shown that the intragroup data under the division of the 24 solar terms have a higher similarity, leading to an average decrease of 15.68%, 40.57%, 14.68%, and 14.64% in the MAE, MSE, RMSE, and WMAPE of the predicted results, respectively. Finally, based on the data derived from the 24 solar terms, the combined algorithm was compared with the Adaboost-GA-BP model and then was verified. The genetic algorithm and Adaboost were used to optimize the BP neural network algorithm in initial value assignment and neural network structure, resulting in a 23.42%, 18.12%, and 22.28% reduction in the mean values of the MAE, RMSE, and WMAPE of the predicted results, respectively. Analysis of the results show that using the Adaboost-GA-BP model based on the 24 solar terms for short-term photovoltaic power forecasting can improve the accuracy of photovoltaic power forecasting and significantly improve the predictive performance of the model

Neural Speaker Diarization Using Memory-Aware Multi-Speaker Embedding with Sequence-to-Sequence Architecture

We propose a novel neural speaker diarization system using memory-aware multi-speaker embedding with sequence-to-sequence architecture (NSD-MS2S), which integrates the strengths of memory-aware multi-speaker embedding (MA-MSE) and sequence-to-sequence (Seq2Seq) architecture, leading to improvement in both efficiency and performance. Next, we further decrease the memory occupation of decoding by incorporating input features fusion and then employ a multi-head attention mechanism to capture features at different levels. NSD-MS2S achieved a macro diarization error rate (DER) of 15.9% on the CHiME-7 EVAL set, which signifies a relative improvement of 49% over the official baseline system, and is the key technique for us to achieve the best performance for the main track of CHiME-7 DASR Challenge. Additionally, we introduce a deep interactive module (DIM) in MA-MSE module to better retrieve a cleaner and more discriminative multi-speaker embedding, enabling the current model to outperform the system we used in the CHiME-7 DASR Challenge. Our code will be available at https://github.com/liyunlongaaa/NSD-MS2S.Comment: Submitted to ICASSP 202

Investigating the driving forces of NOx generation from energy consumption in China

In China, nitrogen oxide (NOx) emissions have been declining in recent years, whereas NOx generation continues to increase. This has prompted a growing focus of policy design to inspect the driving mechanisms of NOx generation. In this study, a decomposition model of NOx generation in China from 1995 to 2014 was built using the Logarithmic Mean Divisia Index (LMDI) method. According to the decomposition results, technological effects (e.g., energy intensity and the sector generation factor) inhibited NOx generation in China, while gross domestic product (GDP) per capita was found to have the most positive effect on increasing NOx generation, accounting for 151.00% of the total change and showing an increasing trend in recent years. The sector structure of energy consumption always increased NOx generation, which contradicts the results of previous studies. All population effects considered in this study contributed to the growth in NOx generation. The population scale effect was increasingly impactful on the growth of NOx generation; the population spatial structure was active but less impactful. In general, technological impact cannot offset the increases caused by economic, structural, and population effects. Considering NOx reduction policy in China, more attention should be given to emission reduction policies, energy consumption, and socio-economic effects; together, these approaches will improve initiatives to reduce NOx

Physicochemical Properties, Structural Characterization, Immunoenhancing and Hypoglycemic Activities of Fucoidan Extracts from Two Sargassums Species

In this study, the chemical compositions, structures, immunomodulatory and hypoglycemic activities of fucoidans from Sargassum zhangii (SZ-Fuc) and Sargassum hemiphylla (SH-Fuc) were analyzed and compared. The results showed that the sulfate group content and molecular mass of SZ-Fuc were (29.74 ± 0.01)% and 111.28 kDa, respectively, and SZ-Fuc had a relatively loose surface structure. The main chain of SZ-Fuc was composed of (→1) linked fucose, xylose, glucose, mannose and galactose, (1→3)- and (1→4)- linked xylose, (1→2)-linked mannose, (1→3)-, (1→4)- and (1→6)-linked galactose, and (1→4)- and (1→6)-linked glucose. Meanwhile, the sulfate group content and molecular mass of SH-Fuc were (44.11 ± 0.01)% and 1 166.48 kDa, respectively, SH-Fuc had a compact surface structure, and its main chain contained (→1), (1→3)- and (1→4)-linked fucose, (→1), (1→4)- and (1→6)-linked glucose, (→1) and (1→2)-linked mannose, and (1→4)-linked galactose. Besides, both SZ-Fuc and SH-Fuc had branched structures. They significantly increased NO release from RAW264.7 cells and improved the protein expression of inducible nitric oxide synthase (iNOS) and cyclooxygenase-2 (COX-2), indicating good immunomodulatory activity. The immunomodulatory activity of SZ-Fuc was better than that of SH-Fuc, while the inhibitory effect of SH-Fuc on α-glucosidase was better than that of SZ-Fuc, suggesting that SH-Fuc had better hypoglycemic potential. This study can provide a theoretical basis for polysaccharides from S. zhangii and S. hemiphylla in the development of functional and nutritional foods with immunomodulatory and blood glucose-reducing activity