Phase change microcapsules are a type of energy storage material that can affect temperature changes by changing its material state and releasing or absorbing latent heat. In this paper, the temperature effect of phase change microcapsules on permeable concrete is investigated. Cooling, heating, and snow melting tests were performed on ordinary permeable concrete and test blocks with different contents of phase change microcapsules. The results indicate that the addition of phase change microcapsules to ordinary permeable concrete has several benefits. First, it effectively raises the internal temperature of concrete in cold conditions. Second, it prolongs the heating duration of concrete in high-temperature environments. Last, it helps in reducing the maximum temperature reached by the concrete. Moreover, the heat storage capacity of phase change microcapsules prevents the refreezing of melted snow water within the concrete. With the increase of the content of phase change microcapsules, the temperature-regulating effect of the test blocks is improved. To sum up, phase change materials can exhibit temperature-regulating effect on permeable concrete under different environmental conditions and have wide applications in the design, manufacture, and performance research of permeable concrete.
The unique output characteristic of synchronous condenser reactive power can compensate reactive power of power grid in real time, but due to strong coupling and nonlinearity, general analysis method is difficult to accurately establish reactive power output model. A synchronous condenser reactive power output model based on deep learning is proposed, which takes field current and field voltage as its inputs, and reactive power and system voltage as its outputs. The simulation results of synchronous condenser reactive power regulation in PSCAD/EMTDC simulation software were used as training samples and test samples, and synchronous condenser reactive power output model based on Directed Acyclic Graph Convolutional Neural Network (DAG-CNN) was established. Simulation results show that the DAG-CNN model for synchronous condenser reactive power output can improve accuracy and generalization ability compared with traditional deep learning model, which can provide some references for the operation state prediction of synchronous condenser.
Segmentation of indicated targets aids in the precise analysis of optical coherence tomography angiography (OCTA) samples. Existing segmentation methods typically perform on 2D projection targets, making it challenging to capture the variance of segmented objects through the 3D volume. To address this limitation, the low-rank adaptation technique is adopted to fine-tune the Segment Anything Model (SAM) version 2, enabling the tracking and segmentation of specified objects across the OCTA scanning layer sequence. To further this work, a prompt point generation strategy in frame sequence and a sparse annotation method to acquire retinal vessel (RV) layer masks are proposed. This method is named SAM-OCTA2 and has been experimented on the OCTA-500 dataset. It achieves state-of-the-art performance in segmenting the foveal avascular zone (FAZ) on regular 2D en-face and effectively tracks local vessels across scanning layer sequences. The code is available at: https://github.com/ShellRedia/SAM-OCTA2.
Abstract In grassland ecosystems, large herbivorous animal grazing activity and increasing nitrogen deposition strongly alter microbial community structure and function. Understanding the effects of grazing and nitrogen addition on the spatial heterogeneity in soil microbial community structure, enzymatic activities and the underlying mechanisms are crucial for making better predictions of soil organic matter dynamics and nutrient cycling. We examined the spatial heterogeneity of soil microbial community structure and enzymatic activity associated with changes in soil microclimate, soil characteristics, plant biomass and soil nutrient responses to grazing and nitrogen addition using a manipulative experiment with control (CK), grazing (G), nitrogen addition (N) and grazing plus nitrogen addition (NG) treatments in a Leymus chinensis meadow steppe, in north‐eastern China. The results demonstrated that soil microbial community structure and enzymatic activities showed a high level of spatial dependence [C/(C + C0) ≥ 0.9] in the CK plot. G, N and NG treatments not only reduced the spatial variability of soil microbial community structure and enzymatic activities but also reshaped the spatial links between enzyme activities and microbial community structure. Litter biomass, soil temperature and soil nutrients (soil dissolved inorganic nitrogen or soil dissolved organic carbon) explained 21%–27% of the spatial variability of soil microbial community structure in the CK treatment and pH was the strongest driver for the spatial variability of soil enzymatic activities. Meanwhile, the homogenization in soil water content induced by the N addition treatment was a determinant of the reduction in spatial heterogeneity of the microbial community structure. The combination of soil physico‐chemical properties (bulk density, soil pH and soil dissolved inorganic nitrogen), soil temperature and root biomass explained 32%–43% of the spatial variability of the microbial community structure in the G treatment, and N and G treatments had additive effects on the spatial heterogeneity of total PLFAs by homogenizing root biomass. Plant biomass and microbial community structure were the major drivers for the spatial heterogeneity of enzymatic activities under G, N and NG. In NG, the change in spatial variability of enzymatic activities was dominated by N addition. Regardless of grazing, N addition facilitated the spatial correlation between microbial community structure and enzyme activities. Overall, our results revealed the drivers of soil microbial community structure and enzymatic activities spatial pattern shift due to grazing and N addition, highlighting the role that spatial variability in soil microbial community structure and enzymatic activities has on the L. chinensis meadow steppe. A free Plain Language Summary can be found within the Supporting Information of this article.
In recent decades, the oriental armyworm, Mythimna separata (Walker), has caused severe damage to staple grains in China. However, little is known about when M. separata begin their first migration and the role of males in reproduction and migration. Here, the migratory benefits and reproductive costs of flight frequency were examined in adults under laboratory conditions. We found that flying males had a positive effect on ovarian and reproductive development in females who flew for 1-2 nights by comparing two treatment groups (flying and nonflying male groups). Moreover, flying males decreased the flight capacity and flight propensity of females. In contrast, flight for more than two nights by males significantly inhibited ovarian and reproductive development in adult females. Compared with the controls (0 night), male flight for 1-2 nights significantly shortened the preoviposition period but significantly increased ovarian and reproductive development in females. However, male flight for more than three nights significantly inhibited female reproduction and flight capacity. These results indicate that M. separata begin their first migration within 2 days after emergence and fly for two nights. Prolonged flight times can result in significant reproductive costs. Females initiated their first migration earlier than males due to a stronger flight capacity. These observed findings will be useful for forecasting and monitoring population dynamics to prevent outbreaks of M. separata and reduce crop losses.
In a single-stage photovoltaic grid-connected control system based on a quasi-Z source inverter (qZSI), the current inner loop controller based on improved active disturbance rejection control (LADRC) is designed to improve robustness, and the parameters of LADRC are optimized by the sparrow search algorithm (SSA) to further improve performance. The simulation results show that compared with the traditional PI control, the LADRC algorithm based on SSA optimization has superior performance.
Abstract Background: Numerous animal and in vitro human chondrocyte studies have highlighted galectin-3 (Gal-3) as a risk factor for osteoarthritis (OA), but there is little supporting evidence from human studies. This study used Mendelian randomization (MR) to further explore the relationship between Gal-3 levels in human circulation and OA. Methods: Instrumental variables were obtained from published genome-wide association studies (GWASs). The OA data in the two samples Mendelian randomization (MR) came from the GWAS catalog database. The remaining data were obtained from the Integrative Epidemiology Unit (IEU) OpenGWAS database. Firstly, two-sample (MR) analysis was used to evaluate the association between Gal-3 levels and OA. Secondly, the causal relationship between circulating Gal-3 levels and obesity was studied using bidirectional two-sample MR. Thirdly, mediated MR was used to analyze whether the effect of circulating Gal-3 levels on the KOA predicted by genes was mediated by obesity. Results: Gal-3 levels were correlated with increased risk of KOA and HOA. Bidirectional MR analysis showed that a genetic predisposition to circulating Gal-3 levels was associated with increased risk of obesity, while a genetic predisposition to obesity was not associated with circulating Gal-3 levels. Mediated MR analysis suggested that waist circumference (WC) played a mediating role in the occurrence of KOA as a function of circulating Gal-3 levels. Conclusions: There is a causal relationship between Gal-3 levels and the occurrence of KOA and HOA, and its effect on KOA is mediated by WC to a certain extent.
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