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Abstract Predicting the spread trends of a pandemic is crucial, but long-term prediction remains challenging due to complex relationships among disease spread stages and preventive policies. To address this issue, we propose a novel approach that utilizes data augmentation techniques, compartmental model features, and disease preventive policies. We also use a breakpoint detection method to divide the disease spread into distinct stages and weight these stages using a self-attention mechanism to account for variations in virus transmission capabilities. Finally, we introduce a long-term spread trend prediction model for infectious diseases based on a bi-directional gated recurrent unit network. To evaluate the effectiveness of our model, we conducted experiments using public datasets, focusing on the prediction of COVID-19 cases in four countries over a period of 210 days. Experiments shown that the Adjust-R2 index of our model exceeds 0.9914, outperforming existing models. Furthermore, our model reduces the mean absolute error by 0.85–4.52% compared to other models. Our combined approach of using both the compartmental and deep learning models provides valuable insights into the dynamics of disease spread.

Abstract Olfactory cues are considered a new sensory medium that can enhance learning, but the lack of empirical data has hampered their widespread use in educational practice. This requires empirical research to explore the effects of olfactory cues on learning. To address this research need, an experimental research study was conducted among 87 fourth graders from a Chinese elementary school. It explored the innovative design of adding olfactory cues to text materials by examining their effects on retention and schemata construction as learning outcomes, as well as their influence on learners’ cognitive load and learning experience. In this between-subjects design experiment, the experimental group (n = 44) learned text materials with the introduction of olfactory cues, while the control group (n = 43) only learned text materials. After the learning activity, participants were asked to complete the questionnaires, immediate test, and delayed test. The results revealed that the usage of olfactory cues synchronized with text materials can enhance delayed retention, facilitate schemata construction, and improve learner experience without increasing cognitive load. This study confirms the potential of well-designed olfactory cues in educational practice and provides insights for designing and presenting multimedia learning resources.

Abstract Precisely modulating the Ru-O covalency in RuOx for enhanced stability in proton exchange membrane water electrolysis is highly desired. However, transition metals with d-valence electrons, which were doped into or alloyed with RuOx, are inherently susceptible to the influence of coordination environment, making it challenging to modulate the Ru-O covalency in a precise and continuous manner. Here, we first deduce that the introduction of lanthanide with gradually changing electronic configurations can continuously modulate the Ru-O covalency owing to the shielding effect of 5s/5p orbitals. Theoretical calculations confirm that the durability of Ln-RuOx following a volcanic trend as a function of Ru-O covalency. Among various Ln-RuOx, Er-RuOx is identified as the optimal catalyst and possesses a stability 35.5 times higher than that of RuO2. Particularly, the Er-RuOx-based device requires only 1.837 V to reach 3 A cm−2 and shows a long-term stability at 500 mA cm−2 for 100 h with a degradation rate of mere 37 μV h−1.

Abstract This study investigates the impact of geopolitical risk (GPR) on consumption-based carbon (CCO2) emissions as well as the moderating role of environmental policy stringency (EPS) on the above relationship. Based on data collected from 27 countries from 1990 to 2020, the basic results from the sample of the study indicate that GPR accelerates CCO2 emissions. Quantile regression results reveal that the effect of GPR is more pronounced in countries with higher CCO2 emissions. Moreover, EPS weakens the escalating effect of GPR on CCO2 emissions. The robust test results validate the findings reported in the basic regression model. The heterogeneity test indicates that the impact of GPR on CCO2 emissions is greater in developing countries compared in developed countries. The study also proposes these policy implications based on the findings: (1) countries should ensure a stable political environment, establish a robust legal system and promote energy transition; and (2) the scope of environmental taxes should be expanded where different tax rates should be imposed in order to be useful in reducing CCO2 emissions.

Glioblastoma (GBM) is known for its aggressive nature and poor prognosis, with currently no effective treatment available. Research has shown that introducing fluorinated functional groups into different parts of natural product quinoline significantly affects its anti-tumor activity. Therefore, this study synthesized the trifluoromethyl quinoline derivative FKL296 to investigate its anti-tumor effect on GBM and reveal its mechanism of action. In vitro and in vivo studies have shown that FKL296 effectively inhibitd the growth of GBM and is relatively safe and low toxicity, whice also induced cell apoptosis and autophagy. Additionally, protein kinase profiling and molecular docking analyses have revealed a strong binding affinity between FKL296 and SGK1. Cellular thermal shift assay experiments have confirmed the targeting of SGK1 by FKL296 and its role in enhancing SGK1 stability. Bioinformatics analysis and pathway validation indicated that FKL296 targeted SGK1 and inhibited autophagy in tumor cells through the mTOR/FOXO3a signaling pathway. In summary, FKL296 may become a promising drug for the treatment of GBM.

Leukemia is a malignant tumor with high heterogeneity and a complex evolutionary process. It is difficult to resolve the heterogeneity and clonal evolution of leukemia cells by applying traditional bulk sequencing techniques, thus preventing a deep understanding of the mechanisms of leukemia development and the identification of potential therapeutic targets. However, with the development and application of single-cell sequencing technology, it is now possible to investigate the gene expression profile, mutations, and epigenetic features of leukemia at the single-cell level, thus providing a new perspective for leukemia research. In this article, we review the recent applications and advances of single-cell sequencing technology in leukemia research, discuss its potential for enhancing our understanding of the mechanisms of leukemia development, discovering therapeutic targets and personalized treatment, and provide reference guidelines for the significance of this technology in clinical research.

Abstract This study investigates the impact of macroprudential policies on ecological footprint (EF) in the top 11 largest countries. This study uses country-level panel data from these countries, covering the period from 1992 to 2020. Findings indicate that macroprudential policies alleviates ecological footprint in the sample. Macroprudential policies primarily reduce the ecological footprint before medium quantile (50%) while the environmental benefits of the policies end in the later quantiles. Moreover, environmental policy stringency (EPS) amplifies the positive influence of macroprudential policies on environmental sustainability. Estimate results stay the same with basic regression results in the post-global financial crisis (GFC) period while the impact is positive in the pre-GFC period. Finally, other robust tests validate the findings reported in basic regression model. This study suggests that governments should customize various types of macroprudential policies while also considering environmental concerns. The achievement of a sustainable environment can be facilitated by the combined effects of macroprudential policies and EPS.

Geophysical exploration plays an important role in detecting and studying impact structures. This article reviews the common geophysical features of Earth's impact craters, including their gravity, magnetic, electrical, and seismic characteristics. The most obvious geophysical feature of impact craters is the circular or ring-shaped negative gravity anomaly, which is mainly caused by rock fracture and brecciation resulting in lower rock density. Low magnetic anomalies with complex details are mainly due to impact melting reducing the magnetic susceptibility of rocks inside the crater and post-impact modification resulting in complex detailed features. High electrical conductivity is found in simple craters, while more complex craters have gradually increasing electrical conductivity from the central uplift to the marginal rim. The conductivity is dominated by the fracture extent and water content. Low seismic velocity is mainly due to the lower velocity of fractured breccia and fractures relative to the original rock. In addition, seismic reflection profiling has found that impact structures have distinct concave shapes.Internationally, there are abundant research on the geophysical exploration of impact craters. However, in China, confirmed impact craters are rare in number and lack related geophysical exploration. Summarizing the common geophysical characteristics of impact craters provides a basis for geophysical exploration of potential impact crater regions in China and offers material for popular science and public engagement purposes.There are two confirmed impact craters in China, the Xiuyan crater in Liaoning Province and the Yilan crater in Heilongjiang Province. Active seismic investigations had been conducted in Xiuyan crater, and revealed its relative velocity and attenuation structure. However, although several geological studies have been conducted, a comprehensive geophysical study of the newly discovered Yilan crater is still lacking. Recently, our group has conducted dense seismic nodes and distributed acoustic sensing in Yilan crater, the results of which will be reported in the near future.

Abstract The increasing prevalence of antibiotic resistance in Cutibacterium acnes (C. acnes) requires the search for alternative therapeutic strategies. Antimicrobial peptides (AMPs) offer a promising avenue for the development of new treatments targeting C. acnes. In this study, to design peptides with the specific inhibitory activity against C. acnes, we employed a deep learning pipeline with generators and classifiers, using transfer learning and pretrained protein embeddings, trained on publicly available data. To enhance the training data specific to C. acnes inhibition, we constructed a phylogenetic tree. A panel of 42 novel generated linear peptides was then synthesized and experimentally evaluated for their antimicrobial selectivity and activity. Five of them demonstrated their high potency and selectivity against C. acnes with MIC of 2–4 µg/mL. Our findings highlight the potential of these designed peptides as promising candidates for anti-acne therapeutics and demonstrate the power of computational approaches for the rational design of targeted antimicrobial peptides.

Medical image analysis, particularly polyp segmentation, plays a pivotal role in the early detection and prevention of colorectal cancer. The accuracy and precision of polyp identification significantly influence the subsequent diagnostic conclusions and therapeutic strategies. However, polyp segmentation still grapples with several challenges such as considerable variations in polyp size, shape, color, and location, and a high degree of visual similarity between polyps and their immediate tissue surroundings, attributable to factors like light reflection and motion blur during the capture of colonoscopy images. In this paper, we propose a novel Cross-level Context Fusion Network (CCFNet) for polyp segmentation within colonoscopy images. This network capitalizes on cross-level and multi-scale contextual information effectively, thereby enhancing segmentation performance significantly. Within the proposed framework, a High-level Feature Cascaded (HFC) module is presented to integrate the high-level features to produce a coarse segmentation map. This map establishes a global relationship for each pixel, which aids in accurately locating the polyps. In addition, a Cross-level Integration Module (CIM) is proposed to fuse the cross-level features to capture the complementary information from the adjacent layers. Consequently, the module extracts and fuses multi-scale features to learn rich feature representations. Moreover, we propose a Global Context Enhancement (GCE) module to utilize the global map to augment feature representations inside the decoder network. These enhanced features are then harnessed to construct multiple side-out segmentation maps. Extensive experimental results on five publicly polyp segmentation datasets demonstrate that our CCFNet surpasses other comparable methods in improving the accuracy of polyp segmentation.

IntroductionWith the rapid expansion of online education, there is a burgeoning interest within the EdTech space to offer tailored learning experiences that cater to individual student's abilities and needs. Within this framework, knowledge tracing tasks have garnered considerable attention. The primary objective of knowledge tracing is to develop a model that assesses a student's proficiency in a particular skill based on their historical performance in exercises, enabling predictions regarding the likelihood of correct responses in future exercises. While existing knowledge tracing models often incorporate information such as students' exercise answering history and skill mastery level, they frequently overlook the students' mental states during the learning process.MethodsThis paper addresses this gap by introducing a novel psychological factors-enhanced heterogeneous learning interactive graph knowledge tracing model (Psy-KT). This model delineates the interactions among students, exercises, and skills through a heterogeneous graph, supplementing it with four psychological factors that capture students' mental states during the learning process: frustration level, confusion level, concentration level, and boredom level. In the modeling of students' learning processes, we incorporate the forgetting curve and construct relevant cognitive parameters from the features. Additionally, we employ the Item Response Theory (IRT) model to predict students' performance in answering exercises at the subsequent time step. This model not only delves into the psychological aspects of students during the learning process but also integrates the simulation of forgetting, a natural phenomenon in the learning journey. The inclusion of cognitive parameters enhances the description of changes in students' abilities throughout the learning process. This dual focus allows for a more comprehensive understanding of students' learning behaviors while providing a high level of interpretability for the model.Results and discussionEmpirical validation of the Psy-KT model is conducted using four publicly available datasets, demonstrating its superior performance in predicting students' future performance. Through rigorous experimentation, the integration of psychological and forgetting factors in the Psy-KT model not only improves predictive accuracy but also enables educators to offer more targeted tutoring and advice, enhancing the overall efficacy of the learning experience.

ABSTRACTRapid urban development has led to severe land subsidence in Luoyang, Henan Province in the past few years. The current research on subsidence in urban areas of Luoyang is relatively few and early, and cannot reflect the current status of land subsidence in Luoyang. To grasp the current status of land subsidence in Luoyang and prevent the harm caused by subsidence. We used 57 Sentinel-1A Synthetic Aperture Radar (SAR) images covering Luoyang to obtain the land subsidence from April 2017 to December 2021 by using the small baseline subset interferometric SAR technique. The results show that there are several areas of land subsidence in Luoyang City, and the most serious area of subsidence is located near the highway in Jianxi District, with a cumulative subsidence of 130 mm. Land subsidence exists to varying degrees near transportation facilities (Expressway roads, railway, metro), key urban facilities (airports, high-speed railway stations) and ancient sites in Luoyang. A number of small-scale local subsidence in Luoyang is mainly related to high-intensity urban construction, and urban highway and building construction are the main causes of local land subsidence. Industrial activities are also an important factor in land subsidence in Luoyang. Groundwater and rainfall can impact land subsidence, and large amounts of rainfall during the flood season can replenish groundwater resources and slow down the rate of land subsidence. Loess foundations and large amounts of artificial fill in the city may also induce land subsidence.

Abstract Ligand effect, induced by charge transfer between catalytic surface and substrate in core/shell structure, was widely proved to benefit Pt-catalyzed oxygen reduction reaction by tuning the position of d-band center of Pt theoretically. However, ligand effect is always convoluted by strain effect in real core/shell nanostructure; therefore, it remains experimentally unknown whether and how much the ligand effect solely contributes electrocatalytic activity improvements. Herein, we report precise synthesis of a kind of Pd3Ru1/Pt core/shell nanoplates with exclusive ligand effect for oxygen reduction reaction. Layer-by-layer growth of Pt overlayers onto Pd3Ru1 nanoplates can guarantee no lattice mismatch between core and shell because the well-designed Pd3Ru1 has the same lattice parameters as Pt. Electron transfer, due to the exclusive ligand effect, from Pd3Ru1 to Pt leads to a downshift of d-band center of Pt. The optimal Pd3Ru1/Pt1-2L nanoplates achieve excellent activity and stability for oxygen reduction reaction in alkaline/acid electrolyte.

Continuous monitoring of lower extremity muscles is necessary, as the muscles support many human daily activities, such as maintaining balance, standing, walking, running, and jumping. However, conventional electromyography and physiological cross-sectional area methods inherently encounter obstacles when acquiring precise and real-time data pertaining to human bodies, with a notable lack of consideration for user comfort. Benefitting from the fast development of various fabric-based sensors, this paper addresses these current issues by designing an integrated smart compression stocking system, which includes compression garments, fabric-embedded capacitive pressure sensors, an edge control unit, a user mobile application, and cloud backend. The pipeline architecture design and component selection are discussed in detail to illustrate a comprehensive user-centered STIMES design. Twelve healthy young individuals were recruited for clinical experiments to perform maximum voluntary isometric ankle plantarflexion contractions. All data were simultaneously collected through the integrated smart compression stocking system and a muscle force measurement system (Humac NORM, software version HUMAC2015). The obtained correlation coefficients above 0.92 indicated high linear relationships between the muscle torque and the proposed system readout. Two-way ANOVA analysis further stressed that different ankle angles (p = 0.055) had more important effects on the results than different subjects (p = 0.290). Hence, the integrated smart compression stocking system can be used to monitor the muscle force of the lower extremities in isometric mode.

Cognitive engagement is a crucial factor that shapes successful learning outcomes, but our understanding of the factors that influence such engagement in the smart classroom context remains limited. This study aims to narrow this research gap by exploring the relationships among college students’ perceptions of the smart learning environment, perceived usefulness of mobile technology, achievement emotions, and cognitive engagement. A total of 1293 college students completed an online questionnaire survey, and 1076 valid responses were received. Structural equation modeling was used to analyze the interrelationships among these factors. The results revealed that students’ perceptions of the smart classroom environment and perceived usefulness of mobile technology as well as two achievement emotions (pride and anxiety) significantly impact cognitive engagement. Both pride and anxiety act as mediators in the relationships among perceptions of smart classroom environments, the perceived usefulness of mobile technology, and cognitive engagement, in which context the mediating effect of pride is stronger than that of anxiety. These findings have practical implications for instructors, who should focus on implementing strategies that promote positive achievement emotions when students use mobile technology in smart classrooms. Additionally, these findings can inform the design and construction of smart classroom environments. Moreover, our study has limitations due to reliance on online data collection and self-reported data, which may introduce biases and measurement errors. Future research should incorporate multimodal data and advanced technologies for a comprehensive assessment to better understand students’ engagement in smart learning environments, while also considering individual factors and the educational context to enhance the effectiveness of mobile technology in supporting students’ emotions and achievement.

This study examined the impact of economic uncertainty (EU) on Islamic banks (IBs) and conventional banks' (CBs) efficiency in countries that meet a standard where 1% share of Islamic banking assets is part of their total domestic banking sector assets. In addition, this study explored the moderating effect of country governance (CG) by employing the quantitative methodology based on secondary data from 2006 to 2021. The data analysis was done through ordinary least square, fixed effect model, and the random effect model. EU was found to enhance bank efficiency based on the basic regression results. CG moderated the positive effect of EU on bank efficiency. Additional robustness tests showed that EU was positively related to both types of banks' efficiency. The value of the paper is unique in that few papers have investigated the moderating effect of CG on the impact of EU on banks' efficiency, which enhances comprehension of EU and CG. These results highlight important policy implications whereby banks should continue to invest in and improve their risk management strategies. In addition, governments and regulatory bodies should prioritise good governance practices as these can improve banks’ efficiency.

BackgroundThe increasing prevalence of mental health issues among children and adolescents has prompted a growing number of researchers and practitioners to explore digital technology interventions, which offer convenience, diversity, and proven effectiveness in addressing such problems. However, the existing literature reveals a significant gap in comprehensive reviews that consolidate findings and discuss the potential of digital technologies in enhancing mental health.MethodsTo clarify the latest research progress on digital technology to promote mental health in the past decade (2013–2023), we conducted two studies: a systematic review and meta-analysis. The systematic review is based on 59 empirical studies identified from three screening phases, with basic information, types of technologies, types of mental health issues as key points of analysis for synthesis and comparison. The meta-analysis is conducted with 10 qualified experimental studies to determine the overall effect size of digital technology interventions and possible moderating factors.ResultsThe results revealed that (1) there is an upward trend in relevant research, comprising mostly experimental and quasi-experimental designs; (2) the common mental health issues include depression, anxiety, bullying, lack of social emotional competence, and mental issues related to COVID-19; (3) among the various technological interventions, mobile applications (apps) have been used most frequently in the diagnosis and treatment of mental issues, followed by virtual reality, serious games, and telemedicine services; and (4) the meta-analysis results indicated that digital technology interventions have a moderate and significant effect size (g = 0.43) for promoting mental health.ConclusionBased on these findings, this study provides guidance for future practice and research on the promotion of adolescent mental health through digital technology.Systematic review registrationhttps://inplasy.com/inplasy-2023-12-0004/, doi: 10.37766/inplasy2023.12.0004.

In this paper, a tunable ultra-wideband terahertz (THz) metasurface absorber utilizing vanadium dioxide (VO2) has been designed with the assistance of the Binary Grey Wolf Optimization algorithm. The electromagnetic absorption characteristics and the physical absorption mechanism of the proposed absorber are modeled and numerically simulated based on wave interference cancellation theory and impedance matching theory. Further discussion of field distributions is undertaken to elucidate the underlying physical mechanisms of this absorber. Remarkably, the absorber achieves absorption rates exceeding 90% within the frequency range of 2.83 to 8.46 THz. Through the manipulation of VO2 conductivity, the absorber allows dynamic amplitude adjustment ranging from 1.2% to 97%. Compared to previous studies, the proposed absorber exhibits substantial advantages in terms of absorption bandwidth, polarization insensitivity, and wide-angle absorption. Its potential applications encompass modulators, cloaking devices, chemical energy absorption, and other terahertz domains. The proposed structure and design methodology of the tunable ultra-wideband terahertz absorber can provide valuable references for the investigation of novel multifunctional terahertz devices.

This study investigates the impact of macroprudential policies on CO2 emissions in G7 and BRIC countries using country-level panel data from 11 countries, covering the period from 1992 to 2020. The findings indicate that macroprudential policies alleviate CO2 emissions in the sample. Quantile regression results reveal that policies can exacerbate CO2 emissions in countries with high levels of CO2 emissions due to carbon leakage. The positive impact of macroprudential policies on sustainable development can be strengthened by high level of globalisation. Moreover, the influence of macroprudential policies stayed the same based on the basic regression results during the post-global financial crisis (GFC) period, while the impact was positive in the pre-GFC period. Finally, robust tests validated the findings reported in the basic regression model. From this, policymakers should prioritise sustainable economic growth when implementing macroprudential policies and leverage the influence of globalisation to amplify their impact on CO2 emissions. Furthermore, it is crucial to strengthen environmental regulations to prevent carbon leakage that result from industries seeking lenient standards.

An appropriate wound dressing is necessary to enhance the recovery of wounds and the restoration of tissue after the skin gets injured. In this study, a hollow porous microfiber (HPMF) scaffold composed of a combination of polylactic acid (PLA)/polybutylene adipate/butylene terephthalate (PBAT)/polyvinyl alcohol (PVA) was developed using coaxial electrospinning for wound healing. The porous structure of PLA/PBAT HPMFs was formed by dissolving PVA in water. The results showed that when maintaining a PLA: PBAT weight ratio of 7:3, high-quality porous PLA/PBAT composites were achieved, leading to a 36.25% increase in toughness and a 4.9% increase in biodegradability compared to pure PLA. Furthermore, in vivo wound healing assays suggest that composites successfully loaded can effectively promote wound healing on the 13th day. Therefore, this work underscores the significant potential of PLA/PBAT HPMF dressing for wound repair.

Abstract Lactic acidosis is a feature of solid tumors and plays fundamental role(s) rendering cancer cells to adapt to diverse metabolic stresses, but the mechanism underlying its roles in redox homeostasis remains elusive. Here we show that G6PD is phosphorylated at tyrosine 249/322 by the SRC through the formation of a GSTP1-G6PD-SRC complex. Lactic acid attenuates this formation and the phosphorylation of G6PD by non-covalently binding with GSTP1. Furthermore, lactic acid increases the activity of G6PD and facilitates the PPP (NADPH production) through its sensor GSTP1, thereby exhibiting resistance to reactive oxygen species when glucose is scarce. Abrogating a GSTP1-mediated lactic acid signaling showed attenuated tumor growth and reduced resistance to ROS in breast cancer cells. Importantly, positive correlations between immuno-enriched SRC protein and G6PD Y249/322 phosphorylation specifically manifest in ER/PR positive or HER negative types of breast cancer. Taken together, these results suggest that GSTP1 plays a key role in tumor development by functioning as a novel lactate sensor.

Dictyophora rubrovolvata volva, an agricultural by-product, is often directly discarded resulting in environmental pollution and waste of the proteins’ resources. In this study, D. rubrovolvata volva proteins (DRVPs) were recovered using the ultrasound-assisted extraction (UAE) method. Based on one-way tests, orthogonal tests were conducted to identify the effects of the material–liquid ratio, pH, extraction time, and ultrasonic power on the extraction rate of DRVPs. Moreover, the impact of UAE on the physicochemical properties, structure characteristics, intermolecular forces, and functional attributes of DRVPs were also examined. The maximum protein extraction rate was achieved at 43.34% under the best extraction conditions of UAE (1:20 g/mL, pH 11, 25 min, and 550 W). UAE significantly altered proteins’ morphology and molecular size compared to the conventional alkaline method. Furthermore, while UAE did not affect the primary structure, it dramatically changed the secondary and tertiary structure of DRVPs. Approximately 13.42% of the compact secondary structures (α-helices and β-sheets) underwent a transition to looser structures (β-turns and random coils), resulting in the exposure of hydrophobic groups previously concealed within the molecule’s core. In addition, the driving forces maintaining and stabilizing the sonicated protein aggregates mainly involved hydrophobic forces, disulfide bonding, and hydrogen bonding interactions. Under specific pH and temperature conditions, the water holding capacity, oil holding capacity, foaming capacity and stability, emulsion activity, and stability of UAE increased significantly from 2.01 g/g to 2.52 g/g, 3.90 g/g to 5.53 g/g, 92.56% to 111.90%, 58.97% to 89.36%, 13.85% to 15.37%, and 100.22% to 136.53%, respectively, compared to conventional alkali extraction. The findings contributed to a new approach for the high-value utilization of agricultural waste from D. rubrovolvata.

AbstractOur study investigates the influence of information and communication technology (ICT) applications at the national level on the efficiency of Islamic banks (IBs) and conventional banks (CBs) operating in Gulf Cooperation Council (GCC) countries. We analyze data collected from both CBs and IBs in GCC countries over the period spanning from 2006 to 2021. Specifically, ICT in this context refers to the extent to which ICT is applied on a national scale, encompassing activities both within and outside the banking sector. In our basic regression, we observe that ICT negatively impacts both types of bank efficiency, with the effect varying depending on the type of bank. Notably, the coefficient of IBs is slightly higher than that of CBs. Country governance (GC) moderates the negative effect of ICT on both types of bank efficiency. Additional robustness tests indicate that ICT is negatively related to both types of bank efficiency.

The last decade has witnessed the rapid development of immersive virtual reality (IVR) and its application in various contexts. However, its application in supporting real-time virtual collaboration has been quite rare due to technical barriers and the lack of validated design principles. To address this research gap, this study designed and developed an IVR space to enable multiuser synchronous co-located collaboration to complete a fantasy game. An evaluation study (N = 95) was conducted to explore its useful design considerations and the influencing factors for collaboration experience in the game. The IVR space was enabled by the simultaneous localization and mapping (SLAM)-based inside-out tracking technique and was informed by four essential design considerations for promoting effective collaboration in IVR, namely, the role script, learning task, collaboration mechanism, and communication design. The study results revealed that students in general were satisfied with their collaboration experience in IVR, with social presence and collaboration competency as significant predictors of collective efficacy and social experience. Based on both quantitative and qualitative results, this study proposes four validated principles for designing effective IVR spaces to support synchronous co-located collaboration.

Crop mapping is vital in ensuring food production security and informing governmental decision-making. The satellite-normalized difference vegetation index (NDVI) obtained during periods of vigorous crop growth is important for crop species identification. Sentinel-2 images with spatial resolutions of 10, 20, and 60 m are widely used in crop mapping. However, the images obtained during periods of vigorous crop growth are often covered by clouds. In contrast, time-series moderate-resolution imaging spectrometer (MODIS) images can usually capture crop phenology but with coarse resolution. Therefore, a time-series-based spatiotemporal fusion network (TSSTFN) was designed to generate TSSTFN-NDVI during critical phenological periods for finer-scale crop mapping. This network leverages multi-temporal MODIS-Sentinel-2 NDVI pairs from previous years as a reference to enhance the precision of crop mapping. The long short-term memory module was used to acquire data about the time-series change pattern to achieve this. The UNet structure was employed to manage the spatial mapping relationship between MODIS and Sentinel-2 images. The time distribution of the image sequences in different years was inconsistent, and time alignment strategies were used to process the reference data. The results demonstrate that incorporating the predicted critical phenological period NDVI consistently yields better crop classification performance. Moreover, the predicted NDVI trained with time-consistent data achieved a higher classification accuracy than the predicted NDVI trained with the original NDVI.

Background As one of the most serious types of coronary heart disease, ST-elevation myocardial infarction (STEMI) faces huge challenges in the equal management and care of patients due to its life-threatening and time-critical condition. Health inequalities such as sex and age differences in STEMI care have been reported from developed countries. However, limited outcomes have been investigated and the major drivers of inequality are still unclear, especially in under-developed areas. This study aimed to explore the major drivers of health inequalities in STEMI care before implementation of a new regional network in the south-west of China. Methods Prefecture-level data of STEMI patients before the implementation of a regional network were analysed retrospectively. Drivers of inequality were identified from six social determinants of health, namely area of residence, ethnicity, sex, age, education and occupation. Outcomes of STEMI care included timely presentation, reperfusion therapy, timely reperfusion therapy, heart failure, inpatient mortality, length of hospital stay, hospital costs, and various intervals of ischaemic time.Results A total of 376 STEMI patients in the research area before implementation of the STEMI network were included. Compared with urban residents, rural patients were significantly less likely to have timely presentation (odds ratio [OR] = 0.47, 95% CI: 0.28-0.80, P = .004) and timely reperfusion therapy (OR = 0.32, 95% CI: 0.14-0.70, P = .005). Rural residents were less likely to present to hospital promptly than urban residents (HR = 0.65, 95% CI = 0.52-0.82, P < .001). In the first 3 hours of percutaneous coronary intervention (PCI) reperfusion delay and first 6 hours of total ischaemic time, rural patients had a significantly lower probability to receive prompt PCI (hazard ratio [HR] = 0.40, 95% CI: 0.29-0.54, P < .001) and reperfusion therapy (HR = 0.37, 95% CI: 0.25-0.56, P < .001) compared to urban patients. Conclusion Rural residents were a major vulnerable group before implementation of the regional STEMI network. No obvious inequalities in ethnicity, sex, age, education or occupation existed in STEMI care in Chuxiong Prefecture of China.

BackgroundNatural product sanguinarine chloride (SC) can significantly alleviate liver fibrosis and acute liver injury in mice, but whether it has a protective effect on mouse liver injury caused by sodium arsenite (SA) has not been studied. ObjectiveTo verify if SC may present preventive and therapeutic effects on SA-induced liver injury in mice. MethodsA total of 140 SPF male Kunming mice were randomly divided into two sub-studies, which included a prevention sub-study and a treatment sub-study. In each sub-study, a blank group (normal saline), a model group (5 mg·kg−1 SA), and a positive control group (11.375 mg·kg−1 bicyclol and 182 mg·kg−1 glutathione), as well as SC low, medium, and high dose groups (25, 50, and 100 mg·kg−1) were arranged with 10 mice in each group. In the prevention sub-study, the blank group was given normal saline, the model group was given SA, and the other groups (the SC low, medium, and high dose groups and the positive control group) were given the corresponding treatment 30 min before gavage of SA, once a day, for 28 d. In the treatment sub-study, except for the blank group which was given normal saline, the other groups were given SA for 28 d, then the model group was given normal saline, and the other groups were given the corresponding treatment every day for 28 d. After the experiment, the mice were sacrificed to evaluate selected physiological and biochemical indicators in serum and liver tissue and to observe histopathological changes after HE staining. ResultsIn either sub-study of preventive effect or treatment effect: compared with the blank group, body weight, liver weight, liver coefficient, as well as serum alanine transaminase (ALT), aspartate aminotransferase (AST), total bilirubin (TBIL), malondialdehyde (MDA), glutathione peroxidase (GSH), and superoxide dismutase (SOD) among all SC groups were not significantly different (P>0.05); but compared with the model group, the SC groups showed increased body weight (P

This study investigated the effects of gender and gender pairing on behaviors and social interaction during collaborative learning in a blended learning environment. Three types of pairing (all-female, all-male, and mixed) were considered in an empirical study with 44 undergraduate students. The results revealed that, first, female students were more likely to perform well in listening, talking, and integrating during class, and in the quality of posts after class, whereas male students tended to engage more in irrelevant behavior in collaboration. Second, same-gender groups were more active in collaborative discussion, but all-male groups performed worst in quality of posts after class. Third, both male and female students were more active in same-gender groups than in mixed groups. Finally, same-gender groups tended to have greater interpersonal connectedness than mixed-gender groups. The paper ends with a list of practical implications for facilitating effective collaborative learning in co-educational college classrooms.

Increasing attention has been paid to the regulation of electromagnetic parameters by reasonable micromorphological design and proper composition to realize high-performance electromagnetic wave absorbers. Herein, a unique hierarchical SiC nanowire-reinforced SiC aerogel decorated with Ni-capped carbon nanotubes (SiCnw@SiC-Ni@CNT) was constructed. The effective synergism between the combination of multiphase magnetic/dielectric materials and the introduction of specific 3D hierarchical microstructures is beneficial for the apparent improvement of multiple dielectric/magnetic losses, electromagnetic scattering effects, and impedance matching capabilities, exhibiting remarkable tunable microwave absorption performance. Accordingly, a strong microwave absorption intensity (RLmin) at 10.24 GHz of −47.75 dB with a loading of 20 wt% and an ultrawide effective absorption bandwidth (EAB, RL

Sustained drug release has attracted increasing interest in targeted drug therapy. However, existing methods of drug therapy suffer drug action time, large fluctuations in the effective concentration of the drug, and the risk of side effects. Here, a biodegradable composite of polybutylene adipate co-terephthalate/polyvinylpyrrolidone (PBAT/PVP) consisting of electrospun hollow microspheres as sustained-released drug carriers is presented. The as-prepared PBAT/PVP composites show faster degradation rate and drug (Erlotinib) release than that of PBAT. Furthermore, PBAT/PVP composites loaded with Erlotinib provide sustained release effect, thus achieving a better efficacy than that after the direct injection of erlotinib due to the fact that the composites allow a high drug concentration in the tumor for a longer period. Hence, this work provides a potential effective solution for clinical drug therapy and tissue engineering using drug microspheres with a sustained release.

Collaborative learning has been widely used in both offline and online contexts to support deep learning, and its effectiveness may be adjusted by the size of the collaborative groups. To examine the effect of learning context and group size on collaborative learning, this study conducted two experiments with 62 third-year undergraduate students enrolled in the course named Application of Modern Educational Technology to compare learning outcomes, learning engagement, and collaborative experience between quad (four-person) and dyad groups in both face-to-face and online learning contexts. The results indicated that learning outcomes and collaborative experience were not significantly affected by group size and learning context, but for peer interaction, the dyad group showed more communication and interaction during the learning process. In general, the dyad group showed higher and more stable scores in all aspects, as well as being able to adapt to changes in learning contexts. Based on the research results, three practical implications were proposed to promote the implementation of collaborative learning in teaching.

Despite offshore aquaculture brings great economic benefits, it also has destructive effects on the ecological environment of coastal regions. Therefore, the accurate monitoring of offshore aquaculture areas is vital. Existing methods for extracting aquaculture ponds are still limited by the lack of high-resolution hyperspectral imagery and inadequate feature extraction. In this paper, we proposed an unsupervised aquaculture ponds extraction method based on hyperspectral imagery super-resolution, feature fusion and stepwise extraction strategy. First, the resolution of the original hyperspectral imagery is enhanced via a deep learning-based super-resolution method. Then we introduce a feature fusion method by combining multi-dimensional features including elevation, reflectance, biochemistry, principal component analysis, and fast-Fourier transform features to enhance the feature sensitivity to the aquaculture ponds. The aquaculture ponds are finally extracted via a step-wise extraction strategy. Experiments on ZH-1 and GF-7 imageries are conducted, and the experimental results show that our method achieves an OA of 97.9% on the aquaculture pond extraction and that the method can be generalized for the object extraction on multispectral datasets. Ablation experiments show that all three of our innovative modules can effectively improve the extraction accuracy and confirm the generalization of the method.

On February 6, 2023, two large earthquakes occurred near the Turkish town of Kahramanmaraş. The moment magnitude (Mw) 7.8 mainshock ruptured a 310 km-long segment of the left-lateral East Anatolian Fault, propagating through multiple releasing step-overs. The Mw 7.6 aftershock involved nearby left-lateral strike-slip faults of the East Anatolian Fault Zone, causing a 150 km-long rupture. We use remote-sensing observations to constrain the spatial distribution of coseismic slip for these two events and the February 20 Mw 6.4 aftershock near Antakya. Pixel tracking of optical and synthetic aperture radar data of the Sentinel-2 and Sentinel-1 satellites, respectively, provide near-field surface displacements. High-rate Global Navigation Satellite System data constrain each event separately. Coseismic slip extends from the surface to about 15 km depth with a shallow slip deficit. Most aftershocks cluster at major fault bends, surround the regions of high coseismic slip, or extend outward of the ruptured faults. For the mainshock, rupture propagation stopped southward at the diffuse termination of the East Anatolian fault and tapered off northward into the Pütürge segment, some 20 km south of the 2020 Mw 6.8 Elaziğ earthquake, highlighting a potential seismic gap. These events underscore the high seismic potential of immature fault systems.

The flipped classroom is a well-recognized instructional approach that improves learning performance and experience through two sequential phases: pre-class preparation and in-class collaboration. Despite the large differences between the two phases, few studies have explored their separate effects on flipped learning. This study conducted a hierarchical linear regression to investigate how the two sequential phases and their featured behaviors can predict learning performance and experience in a flipped classroom at the undergraduate level. The results indicated that students' pre-class discussion positively predicted their assignment scores to a moderate degree, while the in-class collaboration was negatively correlated with test scores. However, the two phases had a limited impact on students' flipped learning experience. The results also highlight the influence of students’ initial interest and prior achievement on their flipped learning experience. The findings can extend our understanding of the flipped classroom approach and inform its design and implementation in higher education contexts.

In the present study, a series of novel L-phenylalanine dipeptides were designed and synthesized by a multi-step sequence of reactions, including carbodiimide-mediated condensation, hydrolysis, mixed anhydride condensation, and nucleophilic substitution. Among them, compound 7c exhibited potent antitumor activity against prostate cancer cell PC3 in vitro and in vivo via inducing apoptosis. We investigated the significantly differentially expressed proteins in the cells caused by the compound 7c to unravel the molecular mechanisms underlying the regulation of PCa cell growth, which indicated that 7c mainly regulated the protein expression of apoptosis-related transcription factors, including c-Jun, IL6, LAMB3, OSMR, STC1, OLR1, SDC4 and PLAU; and 7c also regulated the protein expression of inflammatory cytokines including IL6, CXCL8, TNFSF9, TNFRSF12A and OSMR, and the phosphorylation levels of RelA. The action target confirmed that TNFSF9 protein is the critical binding target of 7c. These findings suggested that 7c could regulate the apoptosis and inflammatory response related signaling pathways for the inhibition of the proliferation of PC3 cells, implying that 7c could be considered a promising therapeutic candidate for PCa therapy.

This study provides a comprehensive review of the application of virtual reality (VR) in social and emotional learning (SEL) for children and adolescents over the past decade (January 2013–May 2023), with a specific interest in the relations between their technological and instructional design features. A search in Web of Science resulted in 32 relevant articles that were then manually screened. Coding analysis was conducted from four perspectives: participant characteristics, research design, technological features, and instructional design. The analysis provides insights into the VR literature regarding publication trends, target populations, technological features, instructional scenarios, and tasks. To test the effectiveness of VR interventions for promoting SEL, a meta-analysis was also conducted, which revealed an overall medium effect size and significant moderating effects of SEL disorder type and instructional task. Finally, based on the research results, the practical implications of and future research directions for applying VR in SEL were discussed.

Arsenic is a carcinogenic metalloid toxicant widely found in the natural environment. Acute or prolonged exposure to arsenic causes a series of damages to the organs, mainly the liver, such as hepatomegaly, liver fibrosis, cirrhosis, and even hepatocellular carcinoma. Therefore, it is imperative to seek drugs to prevent arsenic-induced liver injury. Quinazolines are a class of nitrogen heterocyclic compounds with biological and pharmacological effects in vivo and in vitro. This study was designed to investigate the ameliorating effects of quinazoline derivatives on arsenic-induced liver injury and its molecular mechanism. We investigated the mechanism of the quinazoline derivative KZL-047 in preventing and ameliorating arsenic-induced liver injury in vitro by cell cycle and apoptosis. We performed real-time fluorescence quantitative polymerase chain reaction (qPCR) and Western blotting combined with molecular docking. In vivo, the experiments were performed to investigate the mechanism of KZL-047 in preventing and ameliorating arsenic-induced liver injury using arsenic-infected mice. Physiological and biochemical indices of liver function in mouse serum were measured, histopathological changes in liver tissue were observed, and immunohistochemical staining was used to detect changes in the expression of RecQ-family helicases in mouse liver tissue. The results of in vitro experiments showed that sodium arsenite (SA) inhibited the proliferation of L-02 cells, induced apoptosis, blocked the cell cycle at the G1 phase, and decreased the expression of RecQ family helicase; after KZL-047 treatment in arsenic-induced L-02 cells, the expression of RecQ family helicase was upregulated, and the apoptosis rate was slowed, leading to the restoration of the cell viability level. KZL-047 inhibited arsenic-induced oxidative stress, alleviated oxidative damage and lipid peroxidation in vivo, and ameliorated arsenic toxicity-induced liver injury. KZL-047 restored the expression of RecQ family helicase proteins, which is consistent with the results of in vitro studies. In summary, KZL-047 can be considered a potential candidate for the treatment of arsenic-induced liver injury.

The middle and lower reaches of the Yangtze River is an important iron, copper, gold and other polymetallic metallogenic belt in China. The southern part of the Yangtze River is the southeast Hubei ore concentration area. As an important source of iron and copper deposits in China, several iron-rich copper deposits are concentrated in this area. The Jinniu volcanic basin is located in the southeastern Hubei ore concentration area. The basin has the ore potential of iron, copper, gold and other polymetallic deposits with the similar metallogenic conditions of other mining areas in this metallogenic belt. However, the basin has a thick overlying strata of magnetic rock and sedimentary rock, which increases the difficulty of ore prospecting. Therefore, it is necessary to strengthen the application of technologies for improving the effect of ore prediction. In the adjacent ore concentration areas, the prospecting work mainly focuses on gravity and magnetic data and combined with other geophysical data for comprehensive analysis, which lays a good foundation for the study of structural characteristics and the guidance of prospecting prediction. These previous works has proved that by comprehensive analysis and interpretation of high-precision gravity and magnetic data combined with other geophysical data, the tectonic framework characteristics, buried rocks and physical property distribution of the study area can be extracted, so as to infer the tectonic characteristics of the basin and its basement and put forward prospecting prediction. For the lack of systematic research and demand for prospecting in Jinniu volcanic basin, based on measured and collected geological and geophysical data, comprehensive analysis and interpretation of gravity and magnetic data combined with MT data were carried out. The techniques of linear signal extraction, multi-scale analysis, inversion and resistivity imaging, etc., were utilized to estimate the depth of the basin basement, delineate volcanic mechanism and buried rocks, and speculate fractures, basin boundary, and some areas of prospecting prospect. The such research has the guidance or reference significance for the basic geological survey and deep ore prediction in this area.

Thermal structural materials integrated with specific electromagnetic function have arised great attention in recent years. Driven by the urgent demand of multi-functional composites involving oxidation resistance, high strength and strong microwave attenuation in application of future high speed stealth vehicle, ceramics and their derivative architectures have considered to be a promising candidate in the field of high-temperature microwave absorption (HTMA) owning to tunable dielectric properties as well as intrinsic excellent thermo-physical properties. This article mainly systematically summarizes state-of-art research progress of high temperature stealth performance of ceramic matrix composites from multi-scale collaborative design. Specifically, the influence on microstructure of SiC fibers, interfaces, matrix and meta-structure design on the microwave absorbing are summarized. Besides, compatibility design over microwave and infrared range of ceramic matrix absorbing composites are summarized. Finally, the prospects in the future challenges and guidelines are provided to design more novel functional high temperature stealth materials. Looking forward to the development trend of high-temperature stealth technology of ceramic matrix composites, it is proposed that the more attention should be devoted to combination of structural and functional performance in terms of compatibility stealth materials with strong absorption, wide frequency bandwidth, multi-frequency absorption, high temperature resistance and low density in application of high temperature stealth materials in the future.

Problem-based learning (PBL) has been used in different domains, and there is overwhelming evidence of its value. As an emerging field with excellent prospects, learning analytics (LA)—especially multimodal learning analytics (MMLA)—has increasingly attracted the attention of researchers in PBL. However, current research on the integration of LA with PBL has not related LA results with specific PBL steps or paid enough attention to the interaction in peer learning, especially for text data generated from peer interaction. This study employed MMLA based on machine learning (ML) to quantify the process engagement of peer learning, identify log behaviors, self-regulation, and other factors, and then predict online PBL performance. Participants were 104 fourth-year students in an online course on social work and problem-solving. The MMLA model contained multimodal data from online discussions, log files, reports, and questionnaires. ML classification models were built to classify text data in online discussions. The results showed that self-regulation, messages post, message words, and peer learning engagement in representation, solution, and evaluation were predictive of online PBL performance. Hierarchical linear regression analyses indicated stronger predictive validity of the process indicators on online PBL performance than other indicators. This study addressed the scarcity of students’ process data and the inefficiency of analyzing text data, as well as providing information on targeted learning strategies to scaffold students in online PBL.

Abstract Endometrial cancer had a relatively high prevalence of MMR deficiency. MMR-D/MSI-H endometrial cancer patients are suggested to be potential beneficiaries of PD-1/PD-L1 inhibitor therapy. Here, we explored the prognostic value of MSI subtype in endometrial cancer and its correlation with immune environment. Based on expression and clinical data of 78 POLE, 123 MSI and 299 Other EC samples from the TCGA-UCEC project, we found that the MSI tumors were identified more often in early stage, had a lower age, better patient survival, enriched CD8+ T cells, and regulatory T cells and less M2 macrophages and activated dendritic cells than the Other group, and shared a relatively similar expression profile with POLE group by differential analysis. In addition, we established the immune landscape of an MMR-D endometrial cancer tissue using unbiased single-cell RNA-seq analysis of 3371 cells. By immunohistochemistry analysis, we found that the MMR-D tumors showed a higher trend of CD20+ B cells infiltration. Our study might expand our understanding of the role of immune subsets in MSI endometrial carcinomas and provide guidance of immunotherapy for endometrial cancer.

Wound healing is a complex, dynamic process supported by a myriad of cellular events that must be tightly coordinated to efficiently repair damaged tissue. These wounds are a significant socioeconomic burden due to their high prevalence and recurrence, which is why the phenomenon of wounds has also been labeled as a “Silent Epidemic”. Most of these wounds become “chronic”, with around 15% of them remaining unresolved 1-year post incidence, which results in a prolonged yet avoidable burden to patients, families, and the health system. In this experimental study, we tried to purify the potent components in chick early amniotic fluid (ceAF) and applied these components to the wound healing mechanism. We first subjected ceAF to a series of purifications, including an HPLC purification system along with ion-exchange chromatography technology to purify other potential components. Upon narrowing down, we found two structural analogs: guanosine and deoxyinosine. We performed these components’ cell scratch and trans-well migration assays to validate the accurate dosage. We also assessed these components via topical administration on the skin of murine model wounds. For this, we randomly divided C57BL/6 (all black, male, 5 weeks old) mice into groups. The wound model was established through excising the skin of mice and treated the wounds with different fractions of guanosine and deoxyinosine continuously for 8–10 day intervals. Once the healing was complete, the skin was excised to determine the inflammatory response and other biochemical parameters of the healed skin, including epidermal thickness, collagen density, macrophages, and neutrophil infiltration at the wounded site. Quantitative real-time PCR and immunoblot assays were performed to determine active gene expression and protein expression of proinflammatory molecules, growth factors, and cytokines. All these findings support our data indicating the promising healing properties of guanosine and deoxyinosine isolated from ceAF.

Although instructional feedback plays an essential role in regulating learning and improving performance, few studies have systematically investigated the needs of teachers and students for instructional feedback systems or developed designs and experiments, especially at the high school level. To address this research need, the present study investigated the needs of selected students and teachers in a high school in Hubei Province, China, and designed and developed a diagnostic visual feedback system for an experimental study with 125 students from a 10th-grade biology class in the same high school. The results showed that this diagnostic visual feedback report improved student performance (ES = 0.37) and that functions such as misconception location, knowledge diagnosis, and knowledge alert were well received by students. These findings have multiple implications for facilitating the design and development of diagnostic visual feedback systems.

In this paper, square-shaped water metamaterial is reported, which can be used as a perfect absorber for ultra-broadband absorption in the microwave frequency range. Computer Simulation Technology (CST) software was used to investigate the results numerically, while a 3D printing technology was used to fabricate the proposed design. The simulated and experimental results showed that the proposed structure achieved absorption of more than 90% in the frequency range from 10.4 to 30 GHz. Moreover, the proposed metamaterial-based system was able to show polarization insensitivity and to maintain a high absorption response in the temperature range from 0 to 100 °C, which reaveled a good thermal stability. The absorption mechanism was elaborated taking into consideration the power loss, electric and magnetic field distributions at three resonant frequencies of 12.1, 17.5 and 24.97 GHz. The performance of the proposed system was seen to outperform that of the reported works in literature. It is believed that the metamaterial structure can be a good candidate for the application of energy harvesting and stealth technology due to the high absorption, thermal stability, low cost and easy fabrication of the proposed design.

Twenty-three novel trifluoromethyl pyrimidine derivatives containing an amide moiety were designed and synthesized through four-step reactions and evaluated for their antifungal, insecticidal, and anticancer properties. Bioassay results indicated that some of the title compounds exhibited good in vitro antifungal activities against Botryosphaeria dothidea (B. dothidea), Phompsis sp., Botrytis cinereal (B. cinerea), Colletotrichum gloeosporioides (C. gloeosporioides), Pyricutaria oryzae (P. oryzae), and Sclerotinia sclerotiorum (S. sclerotiorum) at 50 μg/ml. Meanwhile, the synthesized compounds showed moderate insecticidal activities against Mythimna separata (M. separata) and Spdoptera frugiperda (S. frugiperda) at 500 μg/ml, which were lower than those of chlorantraniliprole. In addition, the synthesized compounds indicated certain anticancer activities against PC3, K562, Hela, and A549 at 5 μg/ml, which were lower than those of doxorubicin. Notably, this work is the first report on the antifungal, insecticidal, and anticancer activities of trifluoromethyl pyrimidine derivatives bearing an amide moiety.

Targeting the problem of the power grid facing greater risks with the connection of large-scale wind power, a method for power grid state analysis using big data is proposed. First, based on the big data, the wind power matrix and the branch power matrix are each constructed. Second, for the wind energy matrix, the eigenvalue index in the complex domain and the spectral density index in the real domain are constructed based on the circular law and the M-P law, respectively, to describe the variation of wind energy. Then, based on the concept of entropy and the M-P law, the index for describing the variation of the branch power is constructed. Finally, in order to analyze the real-time status of the grid connected to large-scale wind power, the proposed index is combined with the sliding time window. The simulation results based on the enhanced IEEE-33 bus system show that the proposed method can perform real-time analysis on the grid state of large-scale wind power connection from different perspectives, and its sensitivity is good.

Soil pollution is a global environmental problem. Nanoscale zero-valent iron (nZVI) as a kind of emerging remedial material is used for contaminated soil, which can quickly and effectively degrade and remove pollutants such as organic halides, nitrates and heavy metals in soil, respectively. However, nZVI and its composites can enter the soil environment in the application process, affect the physical and chemical properties of the soil, be absorbed by microorganisms and affect the growth and metabolism of microorganisms, thus affecting the ecological environment of the entire soil. Because of the potential risks of nZVI to the environment and ecosystems, this paper summarizes the current application of nZVI in the remediation of contaminated soil environments, summarizes the various factors affecting the toxic effects of nZVI particles and comprehensively analyzes the toxic effects of nZVI on microorganisms, toxic mechanisms and cell defense behaviors to provide a theoretical reference for subsequent biosafety research on nZVI.

Objectives With the rapid development of naval equipment and its increasing use frequency and failure rate, the traditional repair mode has limitations. This paper puts forward a rapid prototyping manufacturing (RPM) and equipment design method used in ship maintenance support. Methods Based on the hardware, software, technology and materials, the integration technology of rapid prototyping equipment is researched according to the actual situation of the ship. The design method of quick removal and combination using the equipment movement mechanism is adopted, achieving rapid prototyping repair with nitrogen as the shielding gas. The key technologies and methods of rapid prototyping repair are then studied, including technology, shape coordination and control, and post-repair treatment. Results The results of this study show that mobile rapid prototyping repair equipment with quick removal and combination can help to settle the problems of the online repair of real ships; marine nitrogen can be used as the shielding gas, which is convenient and affordable; and the dust collection system module greatly reduces the pollution of equipment in prototyping repairing process. Conclusions The developed quick removal and combination equipment for prototyping repair, which helps to realize "repair in case of damage" for ships under on-site conditions, can help to meet the requirements of accompanying support for spare ship equipment parts under actual combat conditions.

Most of studies for hydrogen bonds focus on the static model especially between two polar atoms. In contrast, introducing the third polar atom may emerge the competitive hydrogen bonds, which would represent a distinct perspective to perturb the catalytic chemical transformation. Herein, we report quantum mechanics calculations and quasi-classical direct dynamics simulations that demonstrate a triangle form of proton accepters enabled by Cl− anion can afford diverse hydrogen bonds, which control the reactivity and selectivity of Rh catalyzed phenol functionalization. A redox mechanism for carbene insertions with notable ligand effect was discovered and supported by both calculations and the experimental kinetic isotopic effect. The quaternary ammonium additive can stabilize key oxonium ylide intermediates with O–H⋯Cl hydrogen bonds that inhibit the common O–H insertion and promote the carbene C–H insertion product. The nonclassical dynamic hydrogen bonds coupling with Rh complex dissociation may result in an intermediate shuttle of oxonium ylides, which unify the site-selective of the direct phenol functionalization.