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The adsorption and desorption of phosphorus (P) in soil constitute a crucial internal cycle that is closely associated with soil fertility, exerting direct influence on the quantity, form, and availability of P within the soil. The vertical spatial variation characteristics of soil adsorption and desorption were investigated for the 0–100 cm soil layer in the northeast black soil region in this study. The maximum adsorption capacity (Qmax) and maximum adsorption buffer capacity (MBC) of black soil in the study area ranged from 313.8 to 411.9 mg kg-1 and from 3.1 to 28.8 L kg-1, respectively, within the soil layer of 0–100 cm depth, exhibiting an increasing trend with greater soil depth. The degree of P adsorption saturation (DPS) exhibited a contrasting trend with the variations in Qmax and MBC, ranging from 3.8% to 21.6%. The maximum desorption capacity (Dmax) and desorption rate (Dr) of soil P ranged from 112.8 to 215.7 mg kg-1 and 32.1% to 52.5%, respectively, while the readily desorbable P (RDP) in soil was within the range of 1.02 to 3.35 mg kg-1. Both Dmax, Dr, and RDP exhibited a decreasing trend with increasing soil depth before showing an upward trend. These research findings not only provide essential background data for the systematic investigation of soil P in the black soil region but also serve as a valuable reference for assessing soil quality in this area. [ABSTRACT FROM AUTHOR]

Corporate social responsibility (CSR) disclosure is an important way for firms to achieve social goals. As stakeholders pay more attention to CSR performance, the CSR report strategy has attracted academic attention. Prior studies have stressed the important role of positive CSR disclosure strategies in a firm's reputation and market value, but our study shows different findings. Using a sample of China's A‐share listed firms from 2008 to 2019, we find a significant negative correlation between administrative penalties and the use of pictures and tables in CSR reports, which is more significant for firms being penalized rather than individuals in firms. Investor attention and agency costs provide a mechanism explanation. Heterogeneity analysis shows that in regions with a low level of legal institutions, the effects of administrative penalties on the use of pictures and tables in CSR reports are more significant. Nevertheless, the seemingly negative disclosure strategy ultimately contributes to corporate value. [ABSTRACT FROM AUTHOR]

This article discusses the development of a humanized mouse model for studying asthma. The researchers used NOG-EXL mice, which were modified to have a human immune system, and transplanted human cord blood-derived hematopoietic stem cells into them. The mice were then induced with human IL-33 to simulate asthmatic airway remodeling and mucous secretion. The study found that the model successfully replicated key features of asthma, including inflammatory cell infiltration, collagen deposition, and increased mucous secretion. This humanized mouse model has the potential to be a valuable tool for studying asthma and developing clinical strategies for treatment. [Extracted from the article]

Herein, we investigate the temperature compensation for a dual-mass MEMS gyroscope. After introducing and simulating the dual-mass MEMS gyroscope's working modes, we propose a hybrid algorithm for temperature compensation relying on improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN), sample entropy, time–frequency peak filtering, non-dominated sorting genetic algorithm-II (NSGA II) and extreme learning machine. Firstly, we use ICEEMDAN to decompose the gyroscope's output signal, and then we use sample entropy to classify the decomposed signals. For noise segments and mixed segments with different levels of noise, we use time–frequency peak filtering with different window lengths to achieve a trade-off between noise removal and signal retention. For the feature segment with temperature drift, we build a compensation model using extreme learning machine. To improve the compensation accuracy, NSGA II is used to optimize extreme learning machine, with the prediction error and the 2-norm of the output-layer connection weight as the optimization objectives. Enormous simulation experiments prove the excellent performance of our proposed scheme, which can achieve trade-offs in signal decomposition, classification, denoising and compensation. The improvement in the compensated gyroscope's output signal is analyzed based on Allen variance; its angle random walk is decreased from 0.531076°/h/√Hz to 6.65894 × 10−3°/h/√Hz and its bias stability is decreased from 32.7364°/h to 0.259247°/h. [ABSTRACT FROM AUTHOR]