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Purpose This study aims to explore the factors influencing intentions to use library social media marketing accounts from users’ perspectives to help libraries use social media to provide targeted information services to users to meet their information needs. Design/methodology/approach This study is based on the technology acceptance model and theory of planned behaviour and uses WeChat as an example to build the model of factors influencing intentions to use library social media marketing accounts. It takes college students as the research object, performing empirical research through questionnaire surveys and structural equation modeling. Findings The results show that attitude, subjective norm and perceived behaviour control have a significant positive impact on library social media marketing – attitude exerts the most significant effect while the impact of perceived usefulness is nonsignificant. Notably, attitude completely mediates perceived usefulness and use intention, while perceived usefulness partially mediates perceived ease of use and attitude. However, birthplace plays a negative moderating role between attitudes and use intention. Originality/value This study integrates the theory of planned behaviour and technology acceptance model, discusses the factors influencing intentions to use library social media marketing accounts from the users’ perspectives and proposes strategies and methods for the optimization of library social media marketing. The study helps enhance the effects of library social media marketing by improving the comprehension of current circumstances and influencing factors relevant to this issue.

Interrupted sampling repeater jamming (ISRJ) is an attracted coherent jamming method to inverse synthetic aperture radar (ISAR) in the past decades. By means of different jamming parameters settings, realistic dense false targets can be formed around the true target. This paper proposed an adaptive anti-jamming method against ISRJ by adjusting the number of measurements based on compressed sensing (CS). The jamming signal is energy concentrated and segmented sparse in the frequency domain. The measurements number of the reconstructed target signal and the jamming signal is different. According to the restricted isometry property (RIP) condition of CS theory, signal reconstructing performance depends on the number of measurements that varies with the sparsity of the vector. Thus, the jamming signal is suppressed, and the true target signal is retained by altering the measurements number of echo signals. Besides, the two-dimensional (2D) anti-jamming method is derived in detail. The anti-jamming effect is analyzed with different signal-to-noise ratios (SNR), sampling rates, and jam-to-signal ratios (JSR). Simulations prove the effectiveness of the proposed anti-jamming method.

Synthetic aperture radar (SAR) images have special physical scattering characteristics owing to their unique imaging mechanism. Traditional deep learning algorithms usually extract features from real-valued SAR images in a purely data-driven manner, which may ignore some important physical scattering characteristics and sacrifice some useful target information in SAR images. This undoubtedly limits the improvement in performance for SAR target recognition. To take full advantage of the physical information contained in SAR images, a complex-valued network guided with sub-aperture decomposition (CGS-Net) for SAR target recognition is proposed. According to the fact that different targets have different physical scattering characteristics at different angles, the sub-aperture decomposition is used to improve accuracy with a multi-task learning strategy. Specifically, the proposed method includes main and auxiliary tasks, which can improve the performance of the main task by learning and sharing useful information from the auxiliary task. Here, the main task is the target recognition task, and the auxiliary task is the target reconstruction task. In addition, a complex-valued network is used to extract the features from the original complex-valued SAR images, which effectively utilizes the amplitude and phase information in SAR images. The experimental results obtained using the MSTAR dataset illustrate that the proposed CGS-Net achieved an accuracy of 99.59% (without transfer learning or data augmentation) for the ten-classes targets, which is superior to the other popular deep learning methods. Moreover, the proposed method has a lightweight network structure, which is suitable for SAR target recognition tasks because SAR images usually lack a large number of labeled data. Here, the experimental results obtained using the small dataset further demonstrate the excellent performance of the proposed CGS-Net.

Podocytes, as terminally differentiated cells within the glomerulus, play a decisive role in maintaining the molecular selectivity of the glomerular filtration barrier (GFB) through structural integrity and functional homeostasis. Podocyte injury not only directly compromises GFB integrity but also serves as a central pathological mechanism underlying the progression of proteinuric nephropathy. Evidence from studies highlights an intricate link between lipid metabolism dysregulation and podocyte dysfunction: Renal ectopic lipid accumulation (ELA) disrupts intracellular homeostasis via lipotoxic effects, inducing mitochondrial oxidative stress, cytoskeletal remodeling, and inflammatory cascades. Concurrently, excessive reactive oxygen species (ROS) generation coupled with compromised antioxidant defense mechanisms establishes a self-perpetuating cycle of redox imbalance. This bidirectional crosstalk within the lipid-oxidative stress axis triggers irreversible pathological alterations. This review summarizes the effects of abnormal signals during lipid synthesis, breakdown, and metabolism on podocytes, as well as the interaction between mitochondria and podocyte dysfunction through signaling mechanisms in lipid metabolism disorders. We also sorted out the key molecular pathways involved in this axis, and the regulation of key nodes of lipid metabolism (SREBP pathway, HMGCR pathway), improvement of mitochondrial function (mitochondrial dynamics and energy metabolism), and activation of antioxidant defenses (AMPK pathway) are highly promising therapeutic targets for intervening in podocyte damage and blocking the progression of the disease.

This study evaluates the income effects of China’s Major Agricultural Technology Collaborative Extension Program (MATCEP) using CFPS panel data and a Difference-in-Differences model. The purpose of this study is to evaluate how large-scale collaborative agricultural extension affects farmers’ income and its underlying mechanisms. The results show that the program significantly raises farm household income through two mechanisms: production expansion, achieved via lower transaction costs and land consolidation, and quality upgrading, driven by improved technical efficiency and standardization. The effects are stronger among entrepreneurial and financially constrained households. These findings demonstrate that coordinated extension systems linking research, education, and production effectively translate technological progress into rural income growth.

Background This study directly examined the effects of antenatal micronutrient supplementation on adolescent blood pressure (BP). Methods This study involved adolescents from two rural counties in western China. Their mothers had previously participated in a cluster-randomized trial of antenatal micronutrient supplementation. All pregnant women were randomized to take a daily capsule of folic acid (FA) as control, folic acid plus iron (IFA), or multiple micronutrients (MMNs) until delivery. Adolescent BP was assessed using a validated electronic sphygmomanometer and converted into percentiles by population reference. We examined the effects of antenatal micronutrient supplementation on adolescent BP and BP percentiles using generalized estimation equations. Multinomial logistic regression was employed to examine the associations between antenatal micronutrient supplementation and categorical BP outcomes, with relative risk reduction estimated. Results Among 4488 singleton births eligible for long-term follow-up, 1994 (44.4%) adolescents were followed, and among them, 59.2% were male, with a mean age of 11.73 (SD, 0.86) years old. After adjusting for a range of covariates, antenatal MMNs supplementation relative to FA alone was associated with a 1.13 (95% CI -2.09, -0.17) mmHg lower systolic blood pressure (SBP) and a 2.59 (95% CI -5.01, -0.17) points lower SBP percentile. The similar benefits of MMNs were observed for categorized adolescent high BP (SBP and/or diastolic blood pressure (DBP) ≥ the 95th percentile for age, sex, and height). Conclusions Compared with folic acid alone, antenatal MMNs supplementation was associated with lower adolescent SBP. This finding suggests that comprehensive antenatal nutritional interventions may offer a potential strategy for the primordial prevention of hypertension in offspring. Trial registration ISRCTN08850194, retrospectively registered December 14, 2006. https://www.isrctn.com/ISRCTN08850194?q=ISRCTN08850194&filters=&sort=&offset=1&totalResults=1&page=1&pageSize=10 .

Soil salinization is the main abiotic stressor faced by crops. An improved understanding of the transcriptional response to salt stress in roots, the organ directly exposed to a high salinity environment, can inform breeding strategies to enhance tolerance and increase crop yield. Here, RNA-sequencing was performed on the roots of salt-tolerant wheat breeding line CH7034 at 0, 1, 6, 24, and 48 h after NaCl treatment. Based on transcriptome data, a weighted gene co-expression network analysis (WGCNA) was constructed, and five gene co-expression modules were obtained, of which the blue module was correlated with the time course of salt stress at 1 and 48 h. Two GO terms containing 249 differentially expressed genes (DEGs) related to osmotic stress response and salt-stress response were enriched in the blue module. These DEGs were subsequently used for association analysis with a set of wheat germplasm resources, and the results showed that four genes, namely a Walls Are Thin 1-related gene (TaWAT), an aquaporin gene (TaAQP), a glutathione S-transfer gene (TaGST), and a zinc finger gene (TaZFP), were associated with the root salt-tolerance phenotype. Using the four candidate genes as hub genes, a co-expression network was constructed with another 20 DEGs with edge weights greater than 0.6. The network showed that TaWAT and TaAQP were mainly co-expressed with fifteen interacting DEGs 1 h after salt treatment, while TaGST and TaZFP were mainly co-expressed with five interacting DEGs 48 h after salt treatment. This study provides key modules and candidate genes for understanding the salt-stress response mechanism in wheat roots.

Purpose This study aims to explore the switching behaviour of short video (SV) users and its influencing factors and promote the sustainable development of SV platforms (SVPs) and the marketing strategy formulation of library and information institutions. Design/methodology/approach Using the qualitative research method of semi-structured interviews and grounded theory, this study conducts an exploratory study on the user switching phenomenon of an SVP. The authors encoded the interview text at three levels, extracted the factors influencing user switching behaviour on an SVP and constructed the corresponding theoretical model. Findings This study identifies the following major internal and external factors influencing user switching behaviour of SVP: platform quality, social environment, individual characteristics and use needs. It also elaborates on the impact of these internal and external factors on user switching behaviour. Originality/value This study explored the factors influencing SV user switching behaviour and constructed corresponding theoretical models, enriching research in information technology and social media switching. In practice, this study helped the existing SVPs and library and information institutions establish a corresponding early warning mechanism to prevent the loss of existing users and attract new users.

Remaining useful life estimation of the prognostics and health management technique is a complicated and difficult research question for maintenance. In this article, we consider the problem of prognostics modeling and estimation of the turbofan engine under complicated circumstances and propose a kernel principal component analysis–based degradation model and remaining useful life estimation method for such aircraft engine. We first analyze the output data created by the turbofan engine thermodynamic simulation that is based on the kernel principal component analysis method and then distinguish the qualitative and quantitative relationships between the key factors. Next, we build a degradation model for the engine fault based on the following assumptions: the engine has only had constant failure (i.e. no sudden failure is included), and the engine has a Wiener process, which is a covariate stand for the engine system drift. To predict the remaining useful life of the turbofan engine, we built a health index based on the degradation model and used the method of maximum likelihood and the data from the thermodynamic simulation model to estimate the parameters of this degradation model. Through the data analysis, we obtained a trend model of the regression curve line that fits with the actual statistical data. Based on the predicted health index model and the data trend model, we estimate the remaining useful life of the aircraft engine as the index reaches zero. At last, a case study involving engine simulation data demonstrates the precision and performance advantages of this prediction method that we propose. At last, a case study involving engine simulation data demonstrates the precision and performance advantages of this proposed method, the precision of the method can reach to 98.9% and the average precision is 95.8%.