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Abstract Microplastics pollution in agricultural soil is increasingly recognized, but the specific situation varies with geography, climate conditions, and farming practices. The karst landscape, a typical geomorphology in China, demands a deeper understanding of microplastics pollution in such areas. This research zeroes in on Guizhou, a province known for its karst formations, by collecting soil samples from the mulched cultivation layer in ten counties and cities. The study employed metallographic microscopy, scanning electron microscopy (SEM-EDS), and Fourier-transform infrared spectroscopy (FT-IR) to analyze the presence and distribution of microplastics. Results show that polyethylene is the predominant component of microplastics in the mulched agricultural soils of Guizhou, primarily existing as irregular fragments in black, transparent, and translucent forms, with diameters of 40 ~ 120 μm and rough surfaces marked by significant erosion. The concentration of microplastics varies from 143.28 to 3,283.46 items/kg, averaging 1,150.60 ± 647.86 items/kg. The majority of particles accounting for 64.79% are sized between 10 ~ 100 μm. A highly significant positive correlation (p

Abstract Land use changes significantly impact the structure and functioning of ecosystems. The current research focus lies in how to utilize economic and policy instruments to regulate conflicts among stakeholders effectively. The objective is to facilitate rational planning and sustainable development of land utilization resources. The PLUS model integrates a rule-based mining method for land expansion analysis and a CA model based on multi-type stochastic seeding mechanism, which can be used to mine the driving factors of land expansion and predict the patch-level evolution of land use landscapes. Using the PLUS model, a simulation was conducted to study the future land use distribution in the research area over the next 30 years. Based on land use data from Guizhou Province in 2000, 2010, and 2020, a total of 16 driving factors were selected from three aspects: geographical environment, transportation network, and socio-economic conditions. Four scenarios, namely natural development, urban development, ecological conservation, and farmland rotection, were established. Comparative analysis of the simulated differences among the various scenarios was performed. (1) The overall accuracy of the land use simulation using the PLUS model in the study area was 0.983, with a Kappa coefficient of 0.972 and a FoM coefficient of 0.509. The research accuracy meets the simulation requirements. (2) Through the simulation of four different scenarios, the study investigated the land use changes in Guizhou Province over the next 30 years. Each scenario exhibited distinct impacts on land utilization. Comprehensive comparison of the different simulation results revealed that the farmland protection scenario aligns with the sustainable development goals of the research area. Currently, there is a relative scarcity of research on land use simulation, particularly in model application, for Guizhou Province. This study aims to provide a reference for the rational planning of land resources and high-quality urban construction in Guizhou, promoting the high-quality economic development in tandem with advanced ecological and environmental protection.

BackgroundClinical rotation practicum provides NQNs with more opportunities to learn their professional knowledge and develop basic nursing skills. ICU is often used as one of the clinical practicum departments for NQNs. Nursing shortages have been particularly felt in ICU. Due to the characteristic fast-paced working environments, high acuity of patient care, and technical complexities of an ICU. The experience of NQNs is highly stressful and challenging in these settings, which hinders their professional development and impacts patient care.AimsThe study aimed to systematically review and synthesis the findings of qualitative studies exploring experience of NQNs in ICU rotation, to provide a basis for enhancing the quality of clinical nursing.MethodsNine databases were systematically searched for relevant publications from inception until February 2024. All qualitative studies in English and Chinese that explored the experience of NQNs in ICU rotation were collected. Two independent reviewers selected the studies and used The Joanna Briggs Institute Critical Appraisal Tool to evaluate the quality of the studies. Meta-synthesis was performed to integrate the results.ResultsA total of 13 studies revealed five descriptive themes and 14 sub-themes: ICU readiness, physical and psychological stress, positive self-perception, developing relationships, and ICU reflections.ConclusionStandardized training in ICU, the working ability of NQNs is exercised and their professional quality is improved. However, it is also adversely affected by various stressors. The appropriate guidance and monitoring should be given by hospital managers, so as to promote the development of NQNs and enhance the quality of clinical nursing.Systematic review registrationhttps://www.crd.york.ac.uk/PROSPERO/, CRD42023475257.

Classroom learning behavior recognition can provide effective technical support for teaching and learning. However, in natural classroom teaching scenarios, classroom learning behaviors are often missed or falsely detected due to character occlusion and the small object. To tackle the above issues, this study proposed an improved classroom learning behavior recognition algorithm (YOLOv8n_BT) based on YOLOv8n. On the one hand, for the occlusion problem of classroom learning behaviors, this study incorporated the BRA into the Backbone to better capture feature information; on the other hand, for the small object problem of classroom learning behaviors for back-row-students, this study expanded a Tiny Object Detection Layer (TODL) to detect small targets better. Experiments show that the BRA and the TODL can significantly improve the model performance. The YOLOv8n_BT model, which incorporated both the BRA and the TODL into the YOLOv8n(baseline) model simultaneously, has the most significant performance improvement. Compared with the YOLOv8n(baseline), the YOLOv8n_BT model improved by 3.0%, 6.7%, 5.0%, 3.6%, and 9.0% on P, R, F1, mAP50, and mAP50-90, respectively. The detection performance of YOLOv8n_BT also outperforms other state-of-the-arts.

Farmland ecosystems represent a vital carbon source and sink within terrestrial ecosystems. The investigation into the characteristics of carbon emissions and their influencing factors within farmland ecosystems is crucial for the realization of carbon reduction and the promotion of low-carbon development. This study leveraged the analytical prowess of CiteSpace software (version 6.1.5) to examine a comprehensive body of 2805 scholarly works related to carbon emissions within agricultural ecosystems, as documented in the Web of Science Core Database from 1991 through to 2023. Through a visual dissection of data based on national, institutional, and thematic dimensions, the study elucidated emergent focal points and evolving trajectories within this scholarly domain. The findings revealed that current scholarly discussions on carbon emissions from agricultural lands have primarily focused on three key areas: the factors that influence these emissions, the possibilities for their reduction, and the subsequent environmental impacts. Focal points of research have predominantly centered on four key themes: “greenhouse gas emissions from farmland ecosystems”, “carbon emission models for farmland ecosystems”, ”carbon sequestration in farmland ecosystems”, and ”sustainable development in agricultural ecosystems”. The academic perspective has gradually shifted from a broad overview of carbon emissions towards a detailed examination of the determinants of emissions and the efficiency of agricultural resource utilization. Looking forward, it is crucial to explore the mechanisms behind high-carbon agricultural practices and to establish their optimal operational thresholds. The focus of research is shifting from macro carbon emissions to the analysis of emission factors and the efficiency of agricultural input use. Future efforts should emphasize exploring the mechanisms of the environmental impacts caused by high-carbon agricultural inputs and the optimal input levels, refining emission reduction methods in agricultural ecosystems, and promoting collaboration and exchange among researchers worldwide.

Abstract Background Liver plays an important role in maintaining glucose homeostasis. We aimed to examine the associations of liver enzymes and hepatic steatosis index (HSI, a reliable biomarker for non-alcoholic fatty liver disease) in early pregnancy with subsequent GDM risk, as well as the potential mediation effects of lipid metabolites on the association between HSI and GDM. Methods In a birth cohort, liver enzymes were measured in early pregnancy (6-15 gestational weeks, mean 10) among 6,860 Chinese women. Multivariable logistic regression was performed to examine the association between liver biomarkers and risk of GDM. Pearson partial correlation and least absolute shrinkage and selection operator (LASSO) regression were conducted to identify lipid metabolites that were significantly associated with HSI in a subset of 948 women. Mediation analyses were performed to estimate the mediating roles of lipid metabolites on the association of HSI with GDM. Results Liver enzymes and HSI were associated with higher risks of GDM after adjustment for potential confounders, with ORs ranging from 1.42 to 2.24 for extreme-quartile comparisons (false discovery rate-adjusted P-trend ≤0.005). On the natural log scale, each SD increment of alanine aminotransferase, aspartate aminotransferase, gamma-glutamyl transferase, alkaline phosphatase, and HSI was associated with a 1.15-fold (95% CI: 1.05, 1.26), 1.10-fold (1.01, 1.20), 1.21-fold (1.10, 1.32), 1.15-fold (1.04, 1.27), and 1.33-fold (1.18, 1.51) increased risk of GDM, respectively. Pearson partial correlation and LASSO regression identified 15 specific lipid metabolites in relation to HSI. Up to 52.6% of the association between HSI and GDM risk was attributed to the indirect effect of the HSI-related lipid score composed of lipid metabolites predominantly from phospholipids (e.g., lysophosphatidylcholine and ceramides) and triacylglycerol. Conclusions Elevated liver enzymes and HSI in early pregnancy, even within a normal range, were associated with higher risks of GDM among Chinese pregnant women. The association of HSI with GDM was largely mediated by altered lipid metabolism.

Natural language understanding technologies play an essential role in automatically solving math word problems. In the process of machine understanding Chinese math word problems, comma disambiguation, which is associated with a class imbalance binary learning problem, is addressed as a valuable instrument to transform the problem statement of math word problems into structured representation. Aiming to resolve this problem, we employed the synthetic minority oversampling technique (SMOTE) and random forests to comma classification after their hyperparameters were jointly optimized. We propose a strict measure to evaluate the performance of deployed comma classification models on comma disambiguation in math word problems. To verify the effectiveness of random forest classifiers with SMOTE on comma disambiguation, we conducted two-stage experiments on two datasets with a collection of evaluation measures. Experimental results showed that random forest classifiers were significantly superior to baseline methods in Chinese comma disambiguation. The SMOTE algorithm with optimized hyperparameter settings based on the categorical distribution of different datasets is preferable, instead of with its default values. For practitioners, we suggest that hyperparameters of a classification models be optimized again after parameter settings of SMOTE have been changed.

Ecological restoration, as a vital means of effectively enhancing the carbon sink function of ecosystems, is currently the subject of active research by scientists. Researchers are actively exploring how to scientifically assess the response mechanisms of ecosystem carbon reservoirs during the process of ecological restoration. In this study, CiteSpace 6.1.(R3 and R6) literature visualization software was employed to conduct data mining on 1566 research articles published from 1996 to 2022, focusing on the impact of ecological restoration on ecosystem carbon reservoirs, as recorded in the Web of Science core database. The analysis involved visualizing various aspects, including the countries involved, research institutions, publication output, research hotspots, and cutting-edge research areas. The research indicates that China holds significant influence in the study of the impact of ecological restoration on ecosystem carbon reservoirs. The literature covers a wide range of research directions and encompasses rich content on the subject matter. The current research focuses on ecological restoration, and its impact on the carbon sink function of ecosystems mainly revolves around four key themes: “the carbon sequestration potential of ecological restoration”, “technological approaches to enhancing the carbon sink function of ecological restoration”, “the importance of assessing carbon sink in terrestrial ecosystems”, and “characteristics of carbon sources/sinks in terrestrial ecosystems”. Currently, the development of research findings on the impact of ecological restoration on the carbon reservoirs of ecosystems is progressing rapidly. Novel research theories, methodologies, and scientific techniques are emerging, necessitating the continuous monitoring and investigation of scholarship in this field. It is crucial to integrate ongoing global environmental-change factors, ensuring the continuity of research and observations and, thus, furnishing robust data support for the assessment and computation of ecosystem carbon sinks.

The aim of our study is to reveal the hub genes related to the pathogenesis of chronic rhinosinusitis with nasal polyps (CRSwNP) and their association with immune cell infiltration through bioinformatics analysis combined with experimental validation. In this study, through differential gene expression analysis, 1,516 upregulated and 1,307 downregulated DEG were obtained from dataset GSE136825 of the GEO database. We identified 14 co-expressed modules using weighted gene co-expression network analysis (WGCNA), among which the most significant positive and negative correlations were MEgreen and MEturquoise modules, containing 1,540 and 3,710 genes respectively. After the intersection of the two modules and DEG, two gene sets—DEG-MEgreen and DEG-MEturquoise—were obtained, containing 395 and 1,168 genes respectively. Through GO term analysis, it was found that immune response and signal transduction are the most important biological processes. We found, based on KEGG pathway enrichment analysis, that osteoclast differentiations, cytokine–cytokine receptor interactions, and neuroactive ligand–receptor interactions are the most important in the two gene sets. Through PPI network analysis, we listed the top-ten genes for the concentrated connectivity of the two gene sets. Next, a few genes were verified by qPCR experiments, and FPR2, ITGAM, C3AR1, FCER1G, CYBB in DEG-MEgreen and GNG4, NMUR2, and GNG7 in DEG-MEturquoise were confirmed to be related to the pathogenesis of CRSwNP. NP immune cell infiltration analysis revealed a significant difference in the proportion of immune cells between the NP group and control group. Finally, correlation analysis between target hub genes and immune cells indicated that FPR2 and GNG7 had a positive or negative correlation with some specific immune cells. In summary, the discoveries of these new hub genes and their association with immune cell infiltration are of great significance for uncovering the specific pathogenesis of CRSwNP and searching for disease biomarkers and potential therapeutic targets.

BackgroundCardiac rehabilitation (CR) improves outcomes in patients with heart failure. However, data on CR efficacy in patients with acute decompensated heart failure is limited. This study is designed to assess the efficacy and safety of CR in patients hospitalized in cardiac intensive care unit (CICU) with acute decompensated heart failure (ADHF).MethodsThis is a single-center, randomized controlled, single-blind clinical trial. A total of 120 participants hospitalized in CICU with ADHF will be randomly allocated in the ratio of 1:1 to two groups: CR group and control group. Participants will receive tailored and progressive CR intervention or attention control. The CR intervention include personalized breathing training, small muscle group resistance training, and aerobic endurance training based on the physical fitness assessment results. The subjects will receive the CR training for 5 days and will be followed up for 6 months. The primary endpoints are the score of the short physical performance battery (SPPB) and 6-month all-cause rehospitalization. The secondary endpoints include cardio-pulmonary function, activities of daily living (ADL), in-hospital mortality rate and 6-month all-cause mortality rate.DiscussionThis randomized, controlled, clinical trial will assess whether CR improves physical function and reduces rehospitalization in patients hospitalized in CICU with ADHF. The results will provide further research-based evidence for the clinical application of CR in patients with ADHF.Trial RegistrationChinese Clinical Trial Registry ChiCTR2100050151. Registered on 19 August 2021.

Background/Aims: Alpinia zerumbet (Pers.) Burtt. et Smith has been used as a flavor additive in food and a traditional medicine for centuries, especially in Guizhou Province, China, and it prolongs people’s lives with multiple beneficial effects. Thus, one of the aims of this review was to expound the chemical constituents of this plant, especially its fruits. Since cardiovascular diseases, including atherosclerosis, pose a health threat to humans, another aim was to expound the possible mechanisms of its potential use as an herbal medication for atherosclerosis. Methods: In this study, 10 reports are cited to expound the potential bioactive compounds. Moreover, 33 reports explain the antihypertensive and antiatherosclerotic effects of the plant by ameliorating inflammation and endothelial dysfunction, increasing vasodilation, improving hyperlipidemia, downgrading the glucose status, and working as an antioxidant. Results: A. zerumbetis rich in terpenes, essential oils, flavonoids, polyphenolics, and sterols. Pharmacological experiments showed that A. zerumbet has antioxidative and anti-inflammatory effects on the NF-κB signaling pathway and can ameliorate oxidative stress in the NOS-NO signaling pathway. Moreover, A. zerumbet demonstrates antihypertensive effects by accelerating vasorelaxant response and increasing 3T3-L1 intracellular cAMP, which has promising antiobesity properties, as well as hypolipidemic and anti-diabetic complication effects. Conclusions: A. zerumbet has potential functions and applications in the prevention of atherosclerosis, but further studies are required before clinical trials.

UV/chlorine advanced oxidation process (AOP), as a potential alternative to UV/H2O2 in water treatment, may pose a potential risk of increased disinfection by-product (DBP) formation and is of great concern. In this paper, seven benzene derivatives, containing two chlorine-inert and five chlorine-active compounds, were selected as typical model DBP precursors, and the effects of medium pressure UV/chlorine (MPUV/chlorine) on their chlorine demand and DBP formation potential (DBPFP) were evaluated. The results showed that MPUV/chlorine could significantly increase the chlorine demand and DBPFP of the two inert precursors. For the four slow but active DBP precursors, MPUV/chlorine may accelerate their short-term DBP formation, whereas it showed an insignificant effect or even reduced their chlorine demand and DBPFP. For the only fast and active DBP precursor, MPUV/chlorine showed an insignificant effect on its short-term DBP formation or DBPFP. The overall effect of MPUV/chlorine was more significant at pH 6 than at pH 8. In the presence of Br−, MPUV/chlorine significantly increased the bromine substitution factors of THMs. In addition, linear fitting results indicated that the UV/chlorine-induced change in overall chlorine demand may be considered as a potential indicator for the prediction of DBPFP alteration.

Background: Both socially regulated learning and cognitive quality are important factors affecting collaborative knowledge building, but the current research lacks a joint quantified evaluation method that combines these two aspects. Objectives: Based on the existing framework, we proposed a joint evaluation method for regulated learning and cognitive quality in collaborative knowledge building, and further extracted the evaluation indicators. Methods: This study involved 74 learners enrolled in a course named 'the Application of Modern Educational Technology' as the subject of study, and made a case analysis with this method. Results and Conclusions: First, the indicators of this joint evaluation method could complement the indicators of traditional frequency statistics methods and facilitate an analysis of regulated learning and cognitive quality in collaborative knowledge building. Second, the group with a higher proportion of high-level cognitive quality and socially shared regulation in collaborative knowledge building achieved better final scores. Finally, four types of groups were obtained through clustering: excellent, risky, mixed group, and highly collaborative group. This study introduced a joint evaluation method for regulated learning and cognitive quality in collaborative knowledge building and provides suggestions for future research.

Massive Open Online Courses (MOOCs) are platforms teachers can use to seek guidance on different strategies to update their teaching skills. This study finds the effectiveness of MOOCs in developing professional performance and skills of school teachers. It tries to show the extent to which school teachers can benefit from these courses and how they apply them in their practical teaching. A mixed-method sequential explanatory (following up the quantitative findings with qualitative ones) method by using multiple data sources, including the MOOC system's log files, final grades and the discussion forum, with additional of face to face class snapshots was used. Some of the data were analysed using statistical, correlations and clustering models, with others coded in excel to develop different themes based on reported experiences. Results indicated how TPD core features uncover school teachers' knowledge and skills level through their learning behaviour variables for the MOOC platform, which will help to transform their pedagogical and instructional approaches while shifting their classrooms into 21st Century classrooms. Generally, this study contributes fresh insights into the literature on the importance of MOOCs for teachers' professional growth while sustaining their work and connections for networked learning. Implications for future studies are also discussed.

Problem-oriented teaching (POT) activities are important in classroom instruction. The level of student response can be influenced by different teacher behaviours in POT. However, the characteristics of teachers' multimodal behaviours at different levels of response are unclear. This study applied epistemic network analysis to explore the characteristics of teachers' multimodal behaviours in POT with different response levels. Using 256 POT segments from 12 classroom teaching videos in primary and secondary schools, this study found that authentic questions and iconic gestures occupied a central position in multimodal behaviours. The concomitant use of multimodal behaviours and the flexibility in eye contact could improve the response levels of students. These findings help understand how teachers' multimodal behaviours can promote students' responses.

Virtual reality learning environment (VRLE), which allow students to transcend time and space and provide them with a sense of immersion, is becoming more common in education. Although many studies have explored the effects of VRLE on learners' learning outcomes as well as learning experiences, the results of these studies indicate that the effects of VRLE on learning outcomes and cognitive load are mixed. This is influenced by multiple factors that can be broadly grouped into two categories: learner characteristics and VRLE features. This study aimed to investigate how the autonomy of VRLE and learner characteristics affect learning in the VRLE. 94 volunteered students (aged 18 to 26) were randomly assigned to a high-autonomy VRLE (N = 47) or a low-autonomy VRLE (N = 47). We did a fuzzy-set qualitative comparative analysis (fsQCA) and discovered that VRLE is not good for all students but only for those with particular features. According to the findings, teachers should personalize their use of instructional technology depending on the profiles of their students.

Background: Calcium-free (Ca-free) solutions are theoretically the most ideal for regional citrate anticoagulation (RCA) in continuous renal replacement therapy (CRRT). However, the majority of medical centers in China had to make a compromise of using commercially available calcium-containing (Ca-containing) solutions instead of Ca-free ones due to their scarcity. This study was designed to probe into the potential of Ca-containing solution as a secure and efficient substitution for Ca-free solutions. Methods: In this prospective, randomized single-center trial, 99 patients scheduled for CRRT were randomly assigned in a 1:1:1 ratio to one of three treatment groups: continuous veno-venous hemodialysis Ca-free dialysate (CVVHD Ca-free) group, continuous veno-venous hemodiafiltration calcium-free dialysate (CVVHDF Ca-free) group, and continuous veno-venous hemodiafiltration Ca-containing dialysate (CVVHDF Ca-containing) group at cardiac intensive care unit (CICU). The primary endpoint was the incidence of metabolic complications. The secondary endpoints included premature termination of treatment, thrombus of filter, and bubble trap after the process. Results: The incidence of citrate accumulation (18.2% vs. 12.1% vs. 21.2%) and metabolic alkalosis (12.1% vs. 0% vs. 9.1%) did not significantly differ among three groups (p > 0.05 for both). The incidence of premature termination was comparable among the groups (18.2% vs. 9.1% vs. 9.1%, p = 0.582). The thrombus level of the filter and bubble trap was similar in the three groups (p > 0.05 for all). Conclusions: In RCA-CRRT for CICU population, RCA-CVVHDF with Ca-containing solutions and traditional RCA with Ca-free solutions had a comparable safety and feasibility. Trial Registration: ChiCTR2100048238 in the Chinese Clinical Trial Registry. [ABSTRACT FROM AUTHOR]

Context: Chronic low-grade inflammation may play a crucial role in the pathogenesis of gestational diabetes mellitus (GDM). However, prospective studies on the relations of inflammatory blood cell parameters during pregnancy with GDM are lacking. Objective: To prospectively investigate the associations of inflammatory blood cell parameters in both early and middle pregnancy, and their change patterns from early to middle pregnancy, with GDM risk. Methods: We used data from the Tongji-Shuangliu Birth Cohort. Inflammatory blood cell parameters (white blood cells [WBC], neutrophils, lymphocytes, monocytes, neutrophil to lymphocyte ratio [NLR], and platelets) were assayed before 15 weeks and between 16 and 28 weeks of gestational age. Logistic regression was used to evaluate the associations between inflammatory blood cell parameters and GDM. Results: Of the 6354 pregnant women, 445 were diagnosed with GDM. After adjustment for potential confounders, WBC, neutrophils, lymphocytes, monocytes, and NLR in early pregnancy were positively associated with GDM risk (odds ratios [95% CI] for extreme-quartile comparison were 2.38 [1.76-3.20], 2.47 [1.82-3.36], 1.40 [1.06-1.85], 1.69 [1.27-2.24], and 1.51 [1.12-2.02], respectively, all P for trend ≤ .010). Similarly, higher levels of WBC, neutrophils, monocytes, and NLR in middle pregnancy were associated with increased risk of GDM (all P for trend ≤ .014). Stable high levels (≥ median in both early and middle pregnancy) of WBC, neutrophils, monocytes, and NLR were positively associated with GDM risk (all P≤ .001). Conclusion: Increased WBC, neutrophils, monocytes, and NLR in both early and middle pregnancy and their stable high levels from early to middle pregnancy were associated with higher GDM risk, highlighting that they might be clinically relevant for identifying individuals at high risk for GDM. [ABSTRACT FROM AUTHOR]