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Immune checkpoint inhibitors provide a definite survival benefit for patients with driver‐negative advanced non‐small cell lung cancer (NSCLC), but predictors of efficacy are still lacking. There may be a relationship between immune inflammatory state and tumor immune response. We explored the relationship of serum neutrophil extracellular traps (NETs) with infiltrating cells in the tumor tissues of patients with NSCLC as well as their relationship with the therapeutic efficacy of programmed cell death protein 1 (PD‐1) inhibitors. Serum myeloperoxidase (MPO)‐double‐stranded DNA (dsDNA) was detected as a marker of NET serum concentration. T cells were detected by immunohistochemical staining, and neutrophils were counted by MPO immunofluorescence staining. Of the 31 patients with NSCLC, a longer progression‐free survival after PD‐1 inhibitor treatment was associated with higher levels of CD3+ T cells, a lower neutrophil : CD3+‐T‐cell ratio (NEU/CD3+) and lower neutrophil : CD8+‐T‐cell ratio (NEU/CD8+) in tumor tissues. Patients with higher serum NETs were more likely to develop progressive disease after treatment (P = 0.003) and to have immune‐related adverse events (IrAEs) as well as higher NEU/CD3+ and NEU/CD8+. The combined model of serum NETs, CD8+ T cells, and tumor proportion score (TPS) significantly improved the prediction of PD‐1 inhibitor efficacy [P = 0.033; area under the curve (AUC) = 0.881]. Our results indicate that serum NETs are effective predictors of PD‐1 inhibitor response and reflect the tissue neutrophil‐to‐lymphocyte ratio and IrAE levels. The combined model of serum NETs, CD8+ T cells, and TPS is a powerful tool for predicting the efficacy of PD‐1 inhibitor treatment in patients with NSCLC. [ABSTRACT FROM AUTHOR]

Fatty acyl‐CoA reductase (FAR) is one of the key enzymes, which catalyses the conversion of fatty acyl‐CoA to the corresponding alcohols. Among the FAR family members in the brown planthopper (Nilaparvata lugens), NlFAR7 plays a pivotal role in both the synthesis of cuticular hydrocarbons and the waterproofing of the cuticle. However, the precise mechanism by which NlFAR7 influences the formation of the cuticle structure in N. lugens remains unclear. Therefore, this paper aims to investigate the impact of NlFAR7 through RNA interference, transmission electron microscope, focused ion beam scanning electron microscopy (FIB‐SEM) and lipidomics analysis. FIB‐SEM is employed to reconstruct the three‐dimensional (3D) architecture of the pore canals and related cuticle structures in N. lugens subjected to dsNlFAR7 and dsGFP treatments, enabling a comprehensive assessment of changes in the cuticle structures. The results reveal a reduction in the thickness of the cuticle and disruptions in the spiral structure of pore canals, accompanied by widened base and middle diameters. Furthermore, the lipidomics comparison analysis between dsNlFAR7‐ and dsGFP‐treated N. lugens demonstrated that there were 25 metabolites involved in cuticular lipid layer synthesis, including 7 triacylglycerols (TGs), 5 phosphatidylcholines (PCs), 3 phosphatidylethanolamines (PEs) and 2 diacylglycerols (DGs) decreased, and 4 triacylglycerols (TGs) and 4 PEs increased. In conclusion, silencing NlFAR7 disrupts the synthesis of overall lipids and destroys the cuticular pore canals and related structures, thereby disrupting the secretion of cuticular lipids, thus affecting the cuticular waterproofing of N. lugens. These findings give significant attention with reference to further biochemical researches on the substrate specificity of FAR protein, and the molecular regulation mechanisms during N. lugens life cycle. [ABSTRACT FROM AUTHOR]

Pulmonary invasive fungal infection in immunocompromised hosts is difficult to diagnose, and current tools for diagnosis or monitoring of response to antifungal treatments have inherent limitations. Droplet digital PCR (ddPCR) has emerged as a promising tool for pulmonary pathogen detection with high sensitivity. This study presents a novel ddPCR panel for rapid and sensitive identification of pulmonary fungal pathogens. First, a ddPCR method for detecting three fungal genera, including Pneumocystis, Aspergillus, and Cryptococcus, was established and evaluated. Then, the clinical validation performance of ddPCR was compared with that of qPCR using 170 specimens, and the 6 specimens with inconsistent results were further verified by metagenomics next-generation sequencing, which yielded results consistent with the ddPCR findings. Finally, the area under the ROC curve (AUC) was used to evaluate the efficiency of ddPCR. While the qPCR identified 16 (9.41%) cases of Aspergillus and 6 (3.53%) cases of Pneumocystis, ddPCR detected 20 (11.76%) Aspergillus cases and 8 (4.71%) Pneumocystis cases. The AUC for Aspergillus, Cryptococcus, and Pneumocystis was 0.974, 0.998, and 0.975, respectively. These findings demonstrated that the ddPCR assay is a highly sensitive method for identifying pathogens responsible for invasive fungal pulmonary infections, and is a promising tool for early diagnosis. [ABSTRACT FROM AUTHOR]

This document provides brief biographical information about three individuals involved in the field of mathematics and systems science. The first individual is a professor at the ISS Academy of Mathematics and Systems Science, CAS, with research interests in system modeling, adaptive control, stochastic systems, and multi-agent systems. The second individual is a professor at Beijing Institute of Technology, specializing in adaptive control, quantized control, multi-agent systems control, and their applications to aircraft control systems. The third individual is a Ph.D. student at the Academy of Mathematics and Systems Science, with research interests in quantized control, adaptive control, and sparse identification. [Extracted from the article]

Purpose: The objective of this multicenter study was to compare the diagnostic performance of lateral flow assay (LFA) and enzyme-linked immunosorbent assay (ELISA) to detect the Dynamiker Aspergillus Galactomannan levels in serum and bronchoalveolar lavage fluid (BALF) samples for I. Methods: We registered 310 clinically suspected Aspergillus infection patients from December 2021 to February 2023 and classified them into subgroups as the "IA group" and "non-IA group" based on the latest EORTC/MSG guidelines. The immunoassays were analyzed by LFA and ELISA respectively. Results: Galactomannan was examined using LFA, and serum and BALF samples demonstrated sensitivities of 82.57% and 89.47%, specificities of 90.76% and 92.00%, PPVs of 89.11% and 96.23%, and NPVs of 85.04% and 79.31%, respectively. Galactomannan was observed using two assays in serum and BALF samples and showed PPAs of 95.11% and 93.33%, NPAs of 89.19% and 96.30%, and TPAs of 92.47% and 94.25%, respectively. The ROC curve demonstrated that LFA had optimum diagnostic value when the index value (I value) = 0.5, the sensitivity was 84.94%, and the specificity was 90.97%. Conclusion: Compared to the ELISA method, the LFA has shown excellent performance for the diagnosis of IA in serum and BALF sample and can be used as an assay for the early diagnosis of patients with IA. The dynamic change in galactomannan levels may be useful for assessing treatment response. [ABSTRACT FROM AUTHOR]

Detection of subsurface hydrodynamic anomalies plays a significant role in groundwater resource management and environmental monitoring. In this paper, based on data from the groundwater level, atmospheric pressure, and precipitation in the Chengdu area of China, a method for detecting outliers considering the factors affecting groundwater levels is proposed. By analyzing the factors affecting groundwater levels in the monitoring site and eliminating them, simplified groundwater data is obtained. Applying sl-Pauta (self-learning-based Pauta), iForest (Isolated Forest), OCSVM (One-Class SVM), and KNN to synthetic data with known outliers, testing and evaluating the effectiveness of 4 technologies. Finally, the four methods are applied to the detection of outliers in simplified groundwater levels. The results show that in the detection of outliers in synthesized data, the OCSVM method has the best detection performance, with a precision rate of 88.89%, a recall rate of 91.43%, an F1 score of 90.14%, and an AUC value of 95.66%. In the detection of outliers in simplified groundwater levels, a qualitative analysis of the displacement data within the field of view indicates that the outlier detection performance of iForest and OCSVM is better than that of KNN. The proposed method for considering the factors affecting groundwater levels can improve the efficiency and accuracy of detecting outliers in groundwater level data. [ABSTRACT FROM AUTHOR]

Coastal long-span bridges are intensively constructed along the western Pacific coast. While the coast is frequently disturbed by typhoons. Given that a coastal long-span bridge will experience a number of typhoons during its service life, it is important to have an understanding of the wind fields formed by typhoons with different crossing paths and corresponding structural dynamic responses. Wind and acceleration data of the Xihoumen Bridge under the influence of onshore, offshore, and landfalling typhoons were acquired by the structural health monitoring system (SHMS). Wind field features of typhoons with three types of paths were compared. The landfalling Typhoon In-fa was used to investigate the differences of wind-induced structural dynamic responses under the influence of each typhoon structural region. The covariance-driven stochastic subspace identification (SSI-COV) was used to identify the modal parameters of the bridge. The results revealed that wind field features at bridge site varied with typhoon crossing paths. The SSI-COV accurately identified the structural frequencies of first 15 vertical modes using the acceleration data under the influence of spiral rainband. The first eyewall has the most detrimental wind conditions to the bridge because the stiffening girder vibrated violently in this region. [ABSTRACT FROM AUTHOR]

The increasing frequency of global drought events poses a significant threat to the stability of grassland ecosystems' functionality. The Inner Mongolian grasslands stand out as one of the world's most drought-prone regions, facing elevated drought risks compared to other biomes. An in-depth comprehension of the impact of drought on grassland ecosystems is paramount for their long-term sustainability. Using the Standardized Precipitation Evapotranspiration Index (SPEI) from 1982 to 2018, this study identified various drought events within the Inner Mongolian grasslands, encompassing moderate drought, severe drought, and extreme drought. The resistance of the vegetation to the different drought conditions, assessed through net primary productivity (NPP) as a metric (reflecting its capacity to maintain its original level during drought periods), was examined. The research findings indicated that the period from 2001 to 2018 witnessed a substantial increase in both the frequency and the extent of drought events compared to the period from 1982 to 2000, particularly concerning severe and extreme droughts. The areas most severely impacted by extreme drought were the Xilingol League and the Alxa League. From 1982–2000 to 2001–2018, under moderate drought conditions, vegetation resistance exhibited a minor decrease in the central and eastern regions but experienced a slight increase in the western region. In contrast, under severe drought conditions, the western region saw a significant decrease in vegetation resistance. Remarkably, under extreme drought conditions, the western region showed a substantial increase in vegetation resistance, while the central and eastern regions experienced a slight decrease. Across all three drought conditions, as precipitation levels declined, the resistance of the meadow–steppe–desert ecosystems demonstrated a high–low–high distribution pattern. The temperate desert steppe exhibited a minimal vulnerability to drought, boasting resistance levels exceeding 0.9. Notably, extreme drought had the most pronounced impact on the temperate meadow steppe, temperate steppe, and temperate desert steppe, particularly within the temperate meadow steppe category. Given these findings, the authorities responsible for grassland management should prioritize regions characterized by frequent drought occurrences and low drought resistance, such as Ulanqab City, the Xilingol League, and the western part of Hulun Buir City. Safeguarding steppe ecosystems is of paramount importance for stabilizing vegetation productivity and land carbon sinks, especially under the anticipated exacerbation of climate conditions in the future. [ABSTRACT FROM AUTHOR]

Noncontact heart rate monitoring techniques based on millimeter-wave radar have advantages in unique medical scenarios. However, the accuracy of the existing noncontact heart rate estimation methods is still limited by interference, such as DC offsets, respiratory harmonics, and environmental noise. Additionally, these methods still require longer observation times. Most deep learning methods related to heart rate estimation still need to collect more heart rate marker data for training. To address the above problems, this paper introduces a radar signal-based heart rate estimation network named the "masked phase autoencoders with a vision transformer network" (MVN). This network is grounded on masked autoencoders (MAEs) for self-supervised pretraining and a vision transformer (ViT) for transfer learning. During the phase preprocessing stage, phase differencing and interpolation smoothing are performed on the input phase signal. In the self-supervised pretraining step, masked self-supervised training is performed on the phase signal using the MAE network. In the transfer learning stage, the encoder segment of the MAE network is integrated with the ViT network to enable transfer learning using labeled heart rate data. The innovative MVN offers a dual advantage—it not only reduces the cost associated with heart rate data acquisition but also adeptly addresses the issue of respiratory harmonic interference, which is an improvement over conventional signal processing methods. The experimental results show that the process in this paper improves the accuracy of heart rate estimation while reducing the requisite observation time. [ABSTRACT FROM AUTHOR]

Detection of subsurface hydrodynamic anomalies plays a significant role in groundwater resource management and environmental monitoring. In this paper, based on data from the groundwater level, atmospheric pressure, and precipitation in the Chengdu area of China, a method for detecting outliers considering the factors affecting groundwater levels is proposed. By analyzing the factors affecting groundwater levels in the monitoring site and eliminating them, simplified groundwater data is obtained. Applying sl-Pauta (self-learning-based Pauta), iForest (Isolated Forest), OCSVM (One-Class SVM), and KNN to synthetic data with known outliers, testing and evaluating the effectiveness of 4 technologies. Finally, the four methods are applied to the detection of outliers in simplified groundwater levels. The results show that in the detection of outliers in synthesized data, the OCSVM method has the best detection performance, with a precision rate of 88.89%, a recall rate of 91.43%, an F1 score of 90.14%, and an AUC value of 95.66%. In the detection of outliers in simplified groundwater levels, a qualitative analysis of the displacement data within the field of view indicates that the outlier detection performance of iForest and OCSVM is better than that of KNN. The proposed method for considering the factors affecting groundwater levels can improve the efficiency and accuracy of detecting outliers in groundwater level data. [ABSTRACT FROM AUTHOR]

The long-term height-resolved wind trend in China under global warming still needs to be discovered. To fill this gap, in this paper we examined the climatology and long-term (1979–2021) trends of the wintertime wind speed at the near-surface and upper atmosphere in China based on long-term radiosonde measurements. At 700, 500, and 400 hPa, much higher wind speed was found over eastern China, compared with western China. At 300, 200, and 100 hPa, maximum wind speed was observed in the latitude zone of around 25–35°N. Furthermore, westerly winds dominated most parts of China between 20°N and 50°N at altitudes from 700 hPa to 100 hPa. A stilling was revealed for the near-surface wind from 1979–2003. From 2004 onward, the near-surface wind speed reversed from decreasing to increasing. This could be largely due to the joint impact of reduced surface roughness length, aerosol optical depth (AOD), and increased sensible heat flux in the ground surface. The decrease of AOD tended to reduce aerosol radiative forcing, thereby destabilizing the planetary boundary layer (PBL). By comparison, the wintertime wind in the upper atmosphere exhibited a significant monotonic upward trend, albeit with varying magnitude for different altitudes. In the upper troposphere, the wintertime maximum wind was observed along a westerly jet stream, with a pronounced upward trend within the zone approximately bounded by latitudes of 25–50°N, particularly above 500 hPa. This accelerating wind observed in the upper troposphere and lower stratosphere could be closely associated with the large planetary-scale meridional temperature trend gradient. Besides, the direction for the wind at the near-surface and lower troposphere (925 and 850 hPa) exhibited a larger variance over the period 1979–2021, which could be associated with the strong turbulence of PBL caused by the heterogeneous land surface. For those pressure levels higher than 850 hPa, large wind directional variance was merely found to the south of 25 °N. The findings from long-term radiosonde measurements in winter over China shed light on the changes in wind speed on the ground and upper atmosphere under global warming from an observational perspective. [ABSTRACT FROM AUTHOR]

Background: Early fluid resuscitation is one of the main therapeutic strategies for acute pancreatitis (AP). This study investigated the effects of early aggressive and nonaggressive hydration on AP. Objectives: The aim of this meta-analysis is to investigate the differences between aggressive and nonaggressive intravenous fluid resuscitation in AP. Design: This study was based on publicly available data, all of which have been extracted from previous ethically approved studies. Data sources and methods: Two authors systematically searched PubMed, Embase (via OVID), Web of Science, and Cochrane Library to find all published research before February 2023. In-hospital mortality were set as primary endpoints. Results: This meta-analysis included seven randomized controlled trials (RCTs) and eight cohort studies with 4072 individuals in nonaggressive (n = 2419) and aggressive (n = 1653) hydration groups. The results showed that patients in the nonaggressive group had a lower mortality rate than those in the aggressive hydration group [relative risks (RR), 0.66; p = 0.02]. Subgroup analysis results showed that patients in the nonaggressive hydration group had lower mortality rates in RCTs (RR, 0.39; p = 0.001), studies conducted in Eastern countries (RR, 0.63; p = 0.002), and studies with severe pancreatitis (RR, 0.65; p = 0.02). In addition, the nonaggressive hydration group had lower rates of infection (RR, 0.62; p < 0.001), organ failure (RR, 0.65; p = 0.02), and shock (RR, 0.21; p = 0.02), as well as a shorter hospital stay (weighted mean difference, −1.63; p = 0.001) than the aggressive hydration group. Conclusions: Early nonaggressive fluid resuscitation is associated with lower mortality, lower risk of organ failure and infection, and shorter hospital stays than aggressive fluid resuscitation. Registration (prospero registration number): CRD42023396388. [ABSTRACT FROM AUTHOR]

The lensing effect of the cosmic microwave background (CMB) is a powerful tool for our study of the distribution of matter in the universe. The quadratic estimator (QE) method, which is widely used to reconstruct lensing potential, has been known to be suboptimal for the low noise level polarization data from next-generation CMB experiments. To improve the performance of the reconstruction, other methods, such as the maximum-likelihood estimator and machine-learning algorithms, have been developed. In this work, we present a deep convolutional neural network model named the Residual Dense Local Feature U-net (RDLFUnet) for reconstructing the CMB lensing convergence field. By simulating lensed CMB data with different noise levels to train and test network models, we find that for noise levels less than 5 μ K-arcmin, RDLFUnet can recover the input gravitational potential with a higher signal-to-noise ratio than the previous deep-learning and traditional QE methods at almost the entire observation scale. [ABSTRACT FROM AUTHOR]

In recent decades, with the large-scale construction and rapid development of half-through arch bridges, as well as the increase of bridge service time, the suspender damage of arch bridge has become increasingly prominent. Therefore, real-time monitoring and regular detection of the health of arch bridge suspenders and timely detection and accurate judgment of the damage location and extent of suspenders are of great engineering significance for evaluating the reliability and residual life of arch bridge structures. By analyzing the main difficulties and existing problems of suspender damage identification, this paper takes the change rate of modal curvature as the damage index, introduces fireworks algorithm into the neural network model, optimizes the optimization process of neural network weight and threshold, and proposes a prediction model based on improved BP neural network by fireworks algorithm. According to the measured data of the damage degree of a long-span arch bridge in daily monitoring and on-site inspection, the proposed prediction method is applied to verify the effectiveness and accuracy in engineering health detection. On this basis, the improved BP neural network by fireworks algorithm is used to predict the suspender damage of a certain long-span half-through arch bridge, which provides an important basis for the actual bridge safety assessment. [ABSTRACT FROM AUTHOR]

Many researches have shown that nanotwinned structure and graphene reinforcing phase can improve the mechanical properties of aluminum (Al) metal, but the synergistic effect of the two on nanoindentation mechanical response of Al matrix composites is rarely reported. In this research, based on molecular dynamics simulations, the nanoindentation mechanical properties and microscopic deformation mechanisms of graphene/nanotwinned Al matrix composites are studied. The effect of the inclination angle and spacing of the twin boundaries (TBs), the insertion position of the graphene sheet, the graphene coating and the layer number of the graphene sheet on the nanoindentation mechanical properties of the Al matrix composites is analyzed. The nanoindentation mechanical properties of nanotwinned Al strongly depend on the inclination angle of TBs, and the dislocation slip modes mainly includes three types: hard mode I (dislocation pile-up penetration mode), soft mode I (partial dislocation parallel twin boundary slip mode) and hard mode II (dislocation limited slip mode). Moreover, as the twin boundary spacing increases, the dislocation slip mode starts to weaken until the nanoindentation mechanical properties are insensitive to the twin inclination orientation. The insertion of the graphene sheet weakens the indentation mechanical properties of the nanotwinned Al matrix composite, which is attributed to the interaction of the graphene with the dislocations and the subsequent absorption of part of them. The weakening effect depends on the distance between the graphene/Al interface and the plastic zone. What's more, graphene coating can improve the indentation mechanical properties of composites. In addition to the load bearing effect of graphene in the elastic stage, this strengthening effect is also attributed to the combined action of graphene and TBs in the plastic stage, which makes the dense dislocation network widely distributed around the indentation of graphene coating and induces the interfacial strain hardening. [ABSTRACT FROM AUTHOR]

Reduced graphene‐oxide (RGO)‐based electrodes in supercapacitors deliver high energy/power capacities compared to typical nanoporous carbon materials. However, extensive critical analysis of literature reveals enormous discrepancies (up to 250 F g−1) in the reported capacitance (variation of 100–350 F g−1) of RGO materials synthesized under seemingly similar methods, inhibiting an understanding of capacitance variation. Here, the key factors that control the capacitance performance of RGO electrodes are demonstrated by analyzing and optimizing various types of commonly applied electrode fabrication methods. Beyond usual data acquisition parameters and oxidation/reduction properties of RGO, a substantial difference of more than 100% in capacitance values (with change from 190 ± 20 to 340 ± 10 F g−1) is found depending on the electrode preparation method. For this demonstration, ≈40 RGO‐based electrodes are fabricated from numerous distinctly different RGO materials via typically applied methods of solution (aqueous and organic) casting and compressed powders. The influence of data acquisition conditions and capacitance estimation practices are also discussed. Furthermore, by optimizing electrode processing method, a direct surface area governed capacitance relationship for RGO structures is revealed. [ABSTRACT FROM AUTHOR]

Drought stress is a central environmental factor that severely limits maize production worldwide. Root architecture plays an important role in drought tolerance and can be targeted in breeding programmes. Here, we conducted phenotyping of root architecture under different water treatments for 373 maize inbred lines, representative germplasm from both China and the United States in different breeding eras. We found that seminal root length in response to drought stress experienced convergent increase during breeding in both countries. Using a genome‐wide association study, we identified a total of 221 associated loci underlying 13 root traits under well‐watered and water‐stressed conditions. These loci harboured many reported root‐ and abiotic stress‐related genes. Furthermore, a total of 75 strong candidate genes were prioritised by integrating candidate genes associated with seminal root length and differentially expressed genes in seminal root. One of high‐confidence candidate genes, ZmCIPK3 was functionally characterised and probably plays a role in enhancing drought tolerance through regulating seminal root growth. This study provides valuable information for genetic improvement of root architecture and drought tolerance in maize. SUMMARY STATEMENT: This study reports the root architecture changes associated with drought stress in maize seedlings, loci and high‐confidence candidates underlying root traits, and overexpression of ZmCIPK3 exhibiting improved drought tolerance through regulating seminal root growth, laying the foundation for genetic improvement of drought tolerance in maize. [ABSTRACT FROM AUTHOR]

In order to obtain the chemical composition characteristics and source apportionment of PM2.5 in a western industrial region of Jinan, manual sampling and analysis of PM2.5 in Pingyin County was conducted during 2019. The results showed that the total concentration of 29 species of PM2.5 was 53.8 μg·m−3. The NO3− concentration (14.6 ± 14.2 μg·m−3) was the highest, followed by OC (9.3 ± 5.5 μg·m−3), SO42− (9.1 ± 6.4 μg·m−3) and NH4+ (8.1 ± 6.8 μg·m−3). Concentrations of OC, NO3− and SO42− were highest in winter and lowest in summer. The concentration of NH4+ was highest in winter and lowest in spring. The annual SOR and NOR were 0.30 ± 0.14 and 0.21 ± 0.12, respectively. SO2 emission and conversion ratio was highest in winter, leading to the highest SO42− concentration. SO2 emission in summer was low, but the conversion ratio was high. NOR in winter and autumn were close and higher than spring and summer. The high NOR in autumn caused a higher NO3− concentration compared with that in spring and summer. The average concentration of SOC during 2019 was 2.8 ± 1.9 μg·m−3, accounting for 30% of OC. The PMF results showed that coal emission accounted for 36.5% of PM2.5 concentration, followed by mobile sources (32.6%), industry emission (17.4%), dust emission (7.1%) and other emissions (6.4%). [ABSTRACT FROM AUTHOR]

When studying an unfamiliar system, we first look for the symmetry that the system has, so that we can make many predictions about the possible properties of the system. The symmetry in ship network security needs to maintain a stable state and maintain a constant state of ship network security. With the rapid development of network information technology, smart ships have become a new hot spot in the international shipping industry. The smart ships cybersecurity discussion is also at the top of the list in the maritime field. More and more shipping companies feel that their smart ship systems need to be upgraded and the main reason behind this is that the systems are maliciously attacked by cyber hackers. Therefore, it is extremely important to detect and protect the security of intelligent ship network systems in real time. The issue of network security has always accompanied the whole process of the development of the Internet. At the same time, with the development of Internet technology, network hacking attacks against the Internet have never stopped developing, and traditional ship network security risk detection and protection cannot achieve good results. After understanding the operation mode of intelligent ship networks, this paper deeply studied the characteristics of cloud computing technology and proposed a real-time risk detection method and protection strategy for intelligent ship network security based on cloud computing. This paper mainly used multi-sensor nodes to analyze data containing malicious attack information and implemented self-execution protection strategy generation nodes to intercept and protect from the attack, so as to achieve the purpose of maintaining the network security of intelligent ships. Through experiments, the virus intrusion detection and defense rate of the algorithm proposed in this paper was able to reach 85% to 95%, while the virus intrusion detection defense rate of the traditional intelligent ship network security protection algorithm was 55% to 65%. The detection rate of the algorithm proposed in this paper was able to reach 96.95% and the false positive rate was 2.56%. The detection rate of the traditional algorithm was only 70.76%, while the false positive rate reached 4.69%. All of the proposed algorithm's data were significantly better than that of traditional algorithms, which proved that the performance of cloud computing-based real-time risk detection and protection algorithms for intelligent ship network security was significantly better than that of traditional algorithms. [ABSTRACT FROM AUTHOR]

Ceramic-based capacitors with excellent recoverable energy storage density (Wrec) and efficiency (η) are greatly desired for pulsed capacitors but challenge as well. In this work, the high energy storage performance with an Wrec of 5.1 J/cm3, an η of 93.4%, and an ultrafast discharge–charge speed t0.9 of 72 ns is achieved in unusual interstitial and substitutional hybrid solid solution of Sr0.64Bi0.18Na0.18TiO3-ZnO (SBNT-Zn), in which two Zn2+ ions occupy one A-site, while one Zn2+ ion occupies one B-site of ABO3 perovskite lattice simultaneously. The addition of Zn2+ increases lattice distortion and breaks long-range ferroelectric order, resulting in more highly dynamic polar nanoregions, higher relaxation behaviors as well as larger polarization (ΔP). Moreover, the extraordinary hybrid solid solution configuration enhances the bandgap of SBNT-Zn and ZnO as a sintering aid refines grain size, both help to enhance electric breakdown strength. This work affirms the feasibility and reliability of forming a hybrid solid solution to develop high-performance ferroelectric materials. [ABSTRACT FROM AUTHOR]

New Ir complexes bearing N-(methylsulfonyl)-2-pyridinecarboxamide (C1) and N-(phenylsulfonyl)-2-pyridinecarboxamide (C2) were employed as catalysts for aqueous formic acid dehydrogenation (FADH). The ligands were designed to maintain the picolinamide skeleton and introduce strong sigma sulfonamide moieties. C1 and C2 exhibited good stability towards air and concentrated formic acid (FA). During 20 continuous cycles, C1 and C2 could achieve the complete conversion of FA with TONs of 172 916 and 172 187, respectively. C1 achieved a high TOF of 19 500 h−1 at 90 °C and an air-stable Ir–H species was observed by 1H NMR spectroscopy. [ABSTRACT FROM AUTHOR]

(1) Background: Ovarian cancer (OC) and Parkinson's disease (PD) represent a huge public health burden. The relationship of these two diseases is suggested in the literature while not fully understood. To better understand this relationship, we conducted a bidirectional Mendelian ran-domization analysis using genetic markers as a proxy. (2) Methods: Utilizing single nucleotide polymorphisms associated with PD risk, we assessed the association between genetically predicted PD and OC risk, overall and by histotypes, using summary statistics from previously conducted genome-wide association studies of OC within the Ovarian Cancer Association Consortium. Similarly, we assessed the association between genetically predicted OC and PD risk. The inverse variance weighted method was used as the main method to estimate odds ratios (OR) and 95% confidence intervals (CI) for the associations of interest. (3) Results: There was no significant association between genetically predicted PD and OC risk: OR = 0.95 (95% CI: 0.88–1.03), or between genetically predicted OC and PD risk: OR = 0.80 (95% CI: 0.61–1.06). On the other hand, when examined by histotypes, a suggestive inverse association was observed between genetically predicted high grade serous OC and PD risk: OR = 0.91 (95% CI: 0.84–0.99). (4) Conclusions: Overall, our study did not observe a strong genetic association between PD and OC, but the observed potential association between high grade serous OC and reduced PD risk warrants further investigation. [ABSTRACT FROM AUTHOR]

The unambiguous identification of lipids is a critical component of lipidomics studies and greatly impacts the interpretation and significance of analyses as well as the ultimate biological understandings derived from measurements. The level of structural detail that is available for lipid identifications is largely determined by the analytical platform being used. Mass spectrometry (MS) coupled with liquid chromatography (LC) is the predominant combination of analytical techniques used for lipidomics studies, and these methods can provide fairly detailed lipid identification. More recently, ion mobility spectrometry (IMS) has begun to see greater adoption in lipidomics studies thanks to the additional dimension of separation that it provides and the added structural information that can support lipid identification. At present, relatively few software tools are available for IMS-MS lipidomics data analysis, which reflects the still limited adoption of IMS as well as the limited software support. This fact is even more pronounced for isomer identifications, such as the determination of double bond positions or integration with MS-based imaging. In this review, we survey the landscape of software tools that are available for the analysis of IMS-MS-based lipidomics data and we evaluate lipid identifications produced by these tools using open-access data sourced from the peer-reviewed lipidomics literature. [ABSTRACT FROM AUTHOR]

Developed ceramic capacitors with excellent recoverable energy storage density (W rec) and efficiency (η) are greatly desired for next-generation pulsed power devices but challenge as well. Herein, outstanding W rec of 5.2 J/cm3 and η of 82% are achieved in the PbO-doped fine grain Bi 0.25 Na 0.25 Sr 0.5 TiO 3 (BNST-P) based relaxor ferroelectric ceramics. The corresponding mechanism is that A-site Pb-doping increases maximum polarization and breakdown strength, and suppresses remnant polarization simultaneously. Meanwhile, the energy storage property possesses excellent temperature and frequency stability, and the variation of W rec and η is less than 5% within the range of 25–100 °C and 2–100 Hz. Encouragingly, superior charge-discharge performance with fast discharge speed t 0.9 of 24 ns and high power density P D of 296 MW/cm3 is obtained. These striking comprehensive results suggest BNST-P ceramics possess potential prospects for applications. [ABSTRACT FROM AUTHOR]

Low temperature (LT) during the grain-filling stage is an important factor that affects the source–sink relationship and leads to yield loss in maize (Zea mays L). In this study, field and pot trials were conducted to investigate the effects of LT during the grain-filling stage on leaf photosynthesis, antioxidant system, hormones, and grain yield of waxy maize cultivars Suyunuo 5 (S5) and Yunuo 7 (Y7). The results showed that LT treatment inhibited the chlorophyll biosynthesis and reduced the photosynthetic pigment levels during grain-filling stage. Ribulose-1,5-bisphosphate carboxylase and phosphoenolpyruvate carboxylase activities, photosynthetic rate, transpiration rate, and stomatal conductance decreased under LT treatment during the grain-filling stage. Furthermore, LT treatment increased the contents of malondialdehyde and reactive oxygen species, and decreased the activities of catalase, superoxide dismutase, peroxidase, and ascorbate peroxidase in the ear leaves, which accelerated the oxidative damage of leaf. The LT treatment also raised abscisic acid content and reduced indole acetic acid content in the ear leaves during grain-filling stage. The results of field and pot trials were verified by each other, but the field effect was greater than that of pot. Overall, LT treatment reduced the waxy maize dry matter accumulation after silking by affecting the physiological and biochemical processes of leaves, and ultimately decreased grain yield. Low temperature (LT) is an important abiotic stress that seriously affects the production and development of maize (Zea mays L). In this study, two waxy maize hybrids were selected and planted in two experimental environments to determine the dynamic changes in leaf photosynthesis, antioxidant system, hormones, and grain yield under post-silking LT stress. This study can be used as a reference for waxy maize to develop adaptation strategies under future climate conditions. [ABSTRACT FROM AUTHOR]

Preference relations have been extended to q-rung orthopair fuzzy environment, and the q-rung orthopair fuzzy preference relations (q-ROFPRs) with additive consistency are defined. Then, the concept of normalized q-rung orthopair fuzzy weight vector (q-ROFWV) is proposed, and the transformation method of constructing q-ROFPR with additive consistency is given. To obtain the weight vector of any q-ROFPRs, a goal programming model to minimize the deviation of the q-ROFPRs from the constructed additive consistent q-ROFPRs is established. The q-rung orthopair fuzzy weighted quadratic (q-ROFWQ) operator is selected to aggregate multiple q-ROFPRs, efficiently handling extreme values and satisfying monotonicity about the order relation. Further, a group decision-making (GDM) method is developed by combining the q-ROFWQ operator and the goal programming model. Finally, the practicality and feasibility of the developed GDM method are demonstrated by an example of rail bogie crucial component identification. [ABSTRACT FROM AUTHOR]

For the drag and heat flux reduction of hypersonic blunt body, a novel combinational spike-aerodisk and channel concept has been proposed. The high pressure air behind the bow shock flows into the channel at the head of the aerodisk, and then sprays out through the lateral jet in the middle of the spike. The Reynolds-averaged Navier-Stokes (RANS) equations coupled with the shear stress transport (SST) k - ω turbulence model have been employed to simulate the flow field. The numerical results reveal that compared with the spike-aerodisk, with the application of the channel, the lateral jet pushes the separated shock wave away from the spike. The range of the recirculation zone between the shear layer and the spike is increased, and the intensity of the reattached shock wave is significantly weakened, so the drag and heat flux reduction properties of the combinational configuration are significantly improved. The influences of the channel convergent half angle and lateral jet location on the flow field, drag and heat flux reduction properties are investigated thoroughly. When the channel convergent half angle is appropriate and the location of the lateral jet is close to the middle of the spike, the drag and heat flux reduction effect becomes better. Besides, with the increase of the Mach number and the decrease of the flying height, the drag and heat flux reduction performance become more significant. In the research range, the combinational configuration in which the convergent half angle is 60° and the lateral jet is located in the middle of the spike has a better overall effect of drag and heat flux reduction, and the effect reaches the best when the Mach number is 6 and the flying height is 20 km. Compared with the spike-aerodisk, the total drag coefficient of the configuration is reduced by 12.95%, and the peak value of Stanton number along the blunt body surface is reduced by 35.19%. • A novel combinational spike-aerodisk and channel concept was numerically investigated. • The combinational concept has better performance in both drag and heat flux reduction. • Effects of channel convergent half angle and lateral jet location on drag and heat flux reduction were studied. • Variation laws of drag and heat flux reduction under different Mach numbers and flight altitudes were analyzed. [ABSTRACT FROM AUTHOR]

The instability of rock slope is still a very frequent geological disaster, which seriously affects people's life and production activities. Previous studies have mainly focused on deformation mechanism, prediction, and control of hard rock with single lithology, while there are limited studies on the theoretic computational method of the stability for soft–hard interbedded anti-inclined rock strata. In this study, a geomechanical model for the toppling failure of soft–hard-interbedded anti-inclined rock slope is established. The modes of failure for soft and hard rock strata are analyzed, the computational formula of the downward thrust for each anti-inclined rock stratum is derived, and the stability safety factor of each rock stratum is defined. A theoretical computational method for determining the potentially most dangerous failure surface of soft–hard-interbedded anti-inclined rock slope is proposed. By comparing with the existing research results, the theoretical solving method proposed in this study can well solve the location of the potentially most dangerous failure surface of soft–hard-interbedded anti-inclined rock slope. The potentially most dangerous failure surface of this kind of slope is approximately planar, and the angle between it and the normal plane of the rock strata is an acute angle within 30°. It provides theoretical support for the stability analysis of this kind of slope. [ABSTRACT FROM AUTHOR]

Impedance-based approachis generally studied for stability analysis of the power electronic converter-based system. Considering multiple-frequency coupling effects, in this article, we establish the harmonic transfer function (HTF) based αβ-frame impedance models of droop inverters based islanded microgrid with unbalanced loads. Therein, the HTF-based αβ-impedance modeling methods of unbalanced loads, as well as droop inverters in parallel, are proposed. Afterward, the HTF-based αβ-frame impedance models are equivalent to single-input single-output (SISO) impedances for simpler impedance measurement and stability analysis, preserving the αβ-frame coupling and multiple-frequency coupling characteristics. Finally, the experimental measurement results verify the accuracy of the αβ-frame SISO impedances. Besides, the stability analysis based on the SISO impedance models accurately reveals low-frequency oscillations of the islanded microgrid with unbalanced loads, further verifying the effectiveness of the SISO impedance models. [ABSTRACT FROM AUTHOR]

Rapeseed (Brassica napus L.) is one of the most important oil crops in the world. The planting area and output of rapeseed are affected by the flowering time, which is a critical agronomic feature. COL9 controls growth and development in many different plant species as a member of the zinc finger transcription factor family. However, BnaCOL9 in rapeseed has not been documented. The aim of this study was to apply CRISPR/Cas9 technology to create an early-flowering germplasm resource to provide useful material for improving the early-maturing breeding of rapeseed. We identified four COL9 homologs in rapeseed that were distributed on chromosomes A05, C05, A03, and C03. We successfully created quadruple BnaCOL9 mutations in rapeseed using the CRISPR/Cas9 platform. The quadruple mutants of BnaCOL9 flowered earlier than the wild-type. On the other hand, the flowering time of the BnaCOL9 overexpression lines was delayed. An analysis of the expression patterns revealed that these genes were substantially expressed in the leaves and flowers. A subcellular localization experiment demonstrated that BnaCOL9 was in the nucleus. Furthermore, we discovered that two key flowering-related genes, BnaCO and BnaFT, were highly elevated in the BnaCOL9 mutants, but dramatically downregulated in the BnaCOL9 overexpression lines. Our findings demonstrate that BnaCOL9 is a significant flowering inhibitor in rapeseed and may be employed as a crucial gene for early-maturing breeding. [ABSTRACT FROM AUTHOR]

Sanguisorba is a small genus which consists of about 15 species widely distributed in North America and Eurasia. Previous studies on Sanguisorba are useful for understanding its phylogeny and chloroplast (cp) genome evolution, however, the cp genome resources of Sanguisorba are still limited, and the phylogeny and molecular dating for Sanguisorba and its relatives still need to be further explored. Here, we report four cp genomes of Sanguisorba and conduct comparative analysis of these four Sanguisorba cp genomes plus five previously published ones. The nine cp genomes have a typical quadripartite structure with a total length of 154 282–155 730 bp and their gene content, gene structure and gene order are relatively conserved. Analysis of single copy (SC)/inverted repeat (IR) boundaries shows only very slight boundary differences among the Sanguisorba cp genomes. Eight variation hotspots were screened as excellent candidate markers for future studies in Sanguisorba. Phylogenetic analysis indicated that Sanguisorba is monophyletic and a member of Agrimonieae subtribe Sanguisorbinae. Within Sanguisorba, S. filiformis is the sister group of the six other taxa in the present sampling. Estimation of divergence times indicates that the subtribes Agrimoniinae and Sanguisorbinae diverged at the transition between the Oligocene and the Miocene, and divergent times of Agrimonieae genera ranged from the late Miocene to the Middle Pleistocene. This study enriches the available cp genome resources of Sanguisorba, and it is of great significance to further study of the phylogeny and evolution of Sanguisorba and its relatives. [ABSTRACT FROM AUTHOR]

It is widely recognized that the iron loss produced by motors at high speeds will directly affect the angle and size of the back electromotive force, and, therefore, it cannot be ignored. In this paper, a high-performance sensorless control algorithm is proposed for high-speed permanent magnet synchronous motors (HSPMSM), taking the iron loss into account. First, the resistance representing the core loss is precalculated by finite element analysis, and then a sliding mode observer with disturbance observation is designed to estimate the rotor position. The observer possesses the advantages of suppressing the chattering phenomenon and enhancing the robustness against uncertainty. Meanwhile, the idea of the characteristic model is used to design an adaptive robust control law to improve the speed control accuracy. Subsequently, a sensorless control scheme is proposed by using the proposed observer in combination with the designed control scheme. The stability of the observer and controller is verified by the Lyapunov theory method. Finally, a simulation example is given to demonstrate the correctness and the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

Based on the Lennard-Jones potential function, a theoretical model of atoms/ions interaction with finite-size (doped) graphene is presented to investigate the mechanical behaviors of atoms/ions adsorption and migration on the surface of finite-size boron, nitrogen and boron nitride doped graphene. The results show that boron, nitrogen and boron nitride doping can change the interaction between atoms/ions and graphene, and the type, position and domain size of doping elements have significant effects on the adsorption sites and adsorption energy of atoms/ions. The stable adsorption sites, adsorption heights and adsorption energy of atoms/ions on the surface of doped graphene can be controlled by regulating the doping elements. Meanwhile, boron, nitrogen and boron nitride doping can affect the energy period and energy barrier of atoms/ions migration on graphene surface. The proper design of boron, nitrogen and boron nitride doping position, size and distribution can effectively control the atom/ion migration behavior on graphene surface. This research work can provide a theoretical reference for atoms/ions carriers, molecular sieves and ion battery electrodes based on doped graphene and graphene heterostructures. [ABSTRACT FROM AUTHOR]

Sports apps are third-party applications for smartphones or wearables that can help users record fitness data and guide their exercise behavior. Many Chinese college students are compelled to use sports apps for running exercises to improve their physical health and cultivate extracurricular exercise habits; however, the acceptance and use of sports apps by college students in mandatory situations requires elucidation. We explored the influencing factors of university students' behavioral intention and usage behavior to use sports apps in mandatory situations by combining the unified theory of acceptance and use of technology and the Self-Determination Theory. A questionnaire survey was conducted among 249 students of Liaoning University of Technology by using non-probabilistic convenient sampling. Data analysis was performed by employing partial least squares structural equation modeling. The results showed that (1) the research model explained 66% (R2 = 0.66) of the variance in behavioral intention and 30% (R2 = 0.30) of the variance in usage behavior; (2) performance expectancy, effort expectancy, social influence, and autonomous motivation significantly positively affected behavioral intention, while controlled motivation negatively affected behavioral intention; and (3) behavioral intention, autonomous motivation, and controlled motivation significantly positively affected usage behavior. The influence of facilitating conditions on usage behavior was non-significant. The results will help technical developers and schools to better understand the influencing factors of college students' use of sports apps in mandatory situations, and formulate corresponding improvement strategies and policies to further promote the role sports apps play in college students' exercise behavior. [ABSTRACT FROM AUTHOR]

Advancements in computer science and software engineering have greatly facilitated mass spectrometry (MS)-based untargeted metabolomics. Nowadays, gigabytes of metabolomics data are routinely generated from MS platforms, containing condensed structural and quantitative information from thousands of metabolites. Manual data processing is almost impossible due to the large data size. Therefore, in the "omics" era, we are faced with new challenges, the big data challenges of how to accurately and efficiently process the raw data, extract the biological information, and visualize the results from the gigantic amount of collected data. Although important, proposing solutions to address these big data challenges requires broad interdisciplinary knowledge, which can be challenging for many metabolomics practitioners. Our laboratory in the Department of Chemistry at the University of British Columbia is committed to combining analytical chemistry, computer science, and statistics to develop bioinformatics tools that address these big data challenges. In this Feature Article, we elaborate on the major big data challenges in metabolomics, including data acquisition, feature extraction, quantitative measurements, statistical analysis, and metabolite annotation. We also introduce our recently developed bioinformatics solutions for these challenges. Notably, all of the bioinformatics tools and source codes are freely available on GitHub (https://www.github.com/HuanLab), along with revised and regularly updated content. [ABSTRACT FROM AUTHOR]

Traffic signs detection and recognition is an essential and challenging task for driverless cars. However, the detection of traffic signs in most scenarios belongs to small target detection, and most existing object detection methods show poor performance in these cases, which increases the difficulty of detection. To further improve the accuracy of small object detection for traffic signs, this paper proposed an optimization strategy based on the YOLOv4 network. Firstly, an improved triplet attention mechanism was added to the backbone network. It was combined with optimized weights to make the network focus more on the acquisition of channel and spatial features. Secondly, a bidirectional feature pyramid network (BiFPN) was used in the neck network to enhance feature fusion, which can effectively improve the feature perception field of small objects. The improved model and some state-of-the-art (SOTA) methods were compared on the joint dataset TT100K-COCO. Experimental results show that the enhanced network can achieve 60.4% mAP(Mean Average Precision), surpassing the YOLOv4 by 8% with the same input size. With a larger input size, it can achieve a best performance capability of 66.4% mAP. This work provides a reference for research on obtaining higher accuracy for traffic sign detection in autonomous driving. [ABSTRACT FROM AUTHOR]

Background: The bone marrow is the place of hematopoiesis with a microenvironment that supports lifelong maintenance of stem cells and high proliferation. It is not surprising that this environment is also favourable for malignant cells emerging in the bone marrow or metastasizing to it. While the cellular composition of the bone marrow microenvironment has been extensively studied, the extracellular matrix and interstitial fluid components have received little attention. Since the sinusoids connect the bone marrow interstitial fluid to the circulation, it is often considered to have the same composition as peripheral blood plasma. Stark differences in the cellular composition of the bone marrow and peripheral blood with different secretory capacities would however suggest profound differences. Methods: In this study we set out to better define if and how the bone marrow interstitial fluid (BMIF) compares to the peripheral blood plasma (PBP) and how both are remodeled during chemotherapy. We applied a multi-omic strategy to quantify the metabolite, lipid and protein components as well as the proteolytic modification of proteins to gain a comprehensive understanding of the two compartments. Results: We found that the bone marrow interstitial fluid is clearly distinct from peripheral blood plasma, both during active pediatric acute lymphoblastic leukemia and following induction chemotherapy. Either compartment was shaped differently by active leukemia, with the bone marrow interstitial fluid being rich in extracellular vesicle components and showing protease dysregulation while the peripheral blood plasma showed elevation of immune regulatory proteins. Following chemotherapy, the BMIF showed signs of cellular remodeling and impaired innate immune activation while the peripheral blood plasma was characterized by restored lipid homeostasis. Conclusion: This study provides a comprehensive examination of the fluid portion of the acute lymphoblastic leukemia microenvironment and finds the contribution of either microenvironment to tumourigenesis. [ABSTRACT FROM AUTHOR]

Background: Salicylic acid (SA) is a phytohormone which works to regulate the abiotic stress response of plants. However, the molecular mechanism by which SA mediates heat tolerance in waxy maize (Zea mays L. sinsensis Kulesh) remains unknown. Results: Two varieties of waxy maize seedlings, heat-tolerant 'Yunuo7' (Y7) and heat-sensitive 'Suyunuo5' (S5), were pretreated with SA prior to heat stress (HTS). After treatment, physiological and transcriptomic changes were analyzed. Compared with HTS, the exogenous application of SA enhanced the shoot dry weight, the activities of antioxidant enzymes (e.g., SOD, POD, CAT and APX), and the concentration of endogenous phytohormones (e.g., SA, ABA, IAA, GA3), while decreased the MDA content. Transcriptome analysis showed that the number of differentially expressed genes (DEGs) identified in the control (CK) vs HTS and HTS vs HTS + SA comparisons were more in S5 than in Y7. HTS induced the downregulation of genes involved in photosynthesis and the upregulation of genes encoding heat shock transcription factors (HSFs) and heat shock proteins (HSPs). Compared with HTS, SA pretreatment reversed the expression of 5 photosynthesis-related genes, 26 phytohormone-related genes, and all genes encoding HSFs and HSPs in S5. Furthermore, the number of alternative splicing (AS) events increased under HTS treatment for both varieties, while decreased under SA pretreatment of S5. Differentially spliced genes (DSGs) showed little overlap with DEGs, and DEGs and DSGs differed significantly in functional enrichment. Conclusions: Physiological and transcriptional together indicated that HTS and SA pretreatment had a greater effect on S5 than Y7. Additionally, it appears that transcriptional regulation and AS work synergistically to enhance thermotolerance in heat-sensitive waxy maize. Our study revealed the regulatory effects and underlying molecular mechanisms of SA on waxy maize seedling under HTS. [ABSTRACT FROM AUTHOR]

The lunar soils evolution over time is mainly caused by space weathering that includes the impacts of varying-sized meteoroids and charged particles implantation of solar/cosmic winds as well. It has long been established that space weathering leads to the formation of outmost amorphous layers (50–200 nm in thickness) embedded nanophase iron (npFe0) around the mineral fragments, albeit the origin of the npFe0 remains controversial. The Chang'e-5 (CE-5) mission returned samples feature the youngest mare basalt and the highest latitude sampling site , providing an opportunity to seek the critical clues for understanding the evolution of soils under space weathering. Here, we report the surface microstructures of the major minerals including olivine, pyroxene, anorthite, and glassy beads in the lunar soil of CE-5. Unlike the previous observations, only olivine in all crystals is surrounded by a thinner outmost amorphous SiO 2 layer (∼10 nm thick) and embedded wüstite nanoparticles FeO (np-FeO, 3–12 nm in size) instead of npFe0. No foreign volatile elements deposition layer and solar flare tracks can be found on the surface or inside the olivine and other minerals. This unique rim structure has not been reported for any other lunar, terrestrial, Martian, or meteorite samples so far. The observation of wüstite FeO and the microstructures support the existence of an intermediate stage in space weathering for lunar minerals by thermal decomposition. [ABSTRACT FROM AUTHOR]

On June 17, 2020, a debris flow dammed lake was formed in Meilong gully, Danba County, China, and a subsequent outburst flood led to the reactivation of the Aniangzhai ancient landslide. This new type of multi-hazard chain (MHC) has attracted widespread attention. This study aims to introduce the formation and evolution processes associated with this novel MHC and develop proposed countermeasures based on field investigations and numerical simulations. We show that this type of MHC comprises five stages: (1) debris flow blocking a river; (2) formation of a barrier dam and lake; (3) lake outburst; (4) revival of an ancient landslide; and (5) flood-induced debris flow. Among these, stage (4) brings particular uncertainty to the risk assessment of the MHC. For translational landslides, the erosion associated with an outburst flood may continuously reduce their stability, while for rotational landslides, their stability may instead increase. By analyzing the formation conditions of the debris flow, criteria required for river blockage, deformation history of the Aniangzhai landslide, and changes in geomorphology, we conclude that the risk of an MHC at this locality may increase in the future. Both rigid dams and flexible barriers could be effective measures to address these risks. Our field investigations and remote sensing analyses indicate that other watersheds in the study area are also exposed to the risk of a similar MHC; this requires detailed future analysis. [ABSTRACT FROM AUTHOR]

Over the years, it has become obvious that simultaneous backfill grouting is of great significance to the design of the tunnel lining and process control of shield construction. It is essential to know the grout pressure distribution around the tunnel lining. The purpose of this study is to seek an alternative method to simulate the grout diffusion process and obtain pressure distribution of different time during simultaneous backfill grouting of tunnel construction. A lattice Boltzmann method (LBM) based free surface flow model is introduced and modified, and a Smagorinsky large-eddy simulation model serves to deal with the small-scale turbulent problem, which is a challenge for LBM to simulate the large-scale real-world engineering. The simulation results obtain the grout filling state with time and pressure distribution around the tunnel lining. Additionally, the grout pressures on site are measured at a ring in line 8 of Chengdu Rail tunnel, and the measurement results are also compared with ones taken from numerical simulation, it is showed that the numerical results are consistent with that of measurement on the whole. Through simulating different grouting strategies, it is concluded that for four-holes grouting schemes, the grouting pressures of upper holes are significant for the grout pressure distribution and should be paid most attention in construction. [ABSTRACT FROM AUTHOR]

Cutaneous wound healing in diabetes is impaired and would develop into nonhealing ulcerations. However, the molecular mechanism underlying the wound-healing process remains largely obscure. Here, we found that cutaneous PDGFRα+ fibroblast-expressing lncRNA-H19 (lncH19) accelerates the wound-healing process via promoting dermal fibroblast proliferation and macrophage infiltration in injured skin. PDGFRα+ cell-derived lncH19, which is lower in contents in the wound-healing cutaneous tissue of patients and mice with type 2 diabetes, is required for wound healing through promoting proliferative capacity of dermis fibroblasts as well as macrophage recruitments. Mechanistically, lncH19 relieves the cell cycle arrest of fibroblasts and increases macrophage infiltration in injured tissues via inhibiting p53 activity and GDF15 releasement. Furthermore, exosomes derived from adipocyte progenitor cells efficiently restore the impaired diabetic wound healing via delivering lncH19 to injured tissue. Therefore, our study reveals a new role for lncRNA in regulating cutaneous tissue repair and provides a novel promising insight for developing clinical treatment of diabetes. [ABSTRACT FROM AUTHOR]

• A novel performance-enhancement strategy for SLGHP geothermal system is proposed. • It relies on arousing inter-layer groundwater crossflow in reservoirs of multi-aquifers. • A numerical model is developed to describe and study the enhanced SLGHP system. • Effects of related parameters are comprehensively studied. The super-long gravity heat pipe (SLGHP) is a novel down-hole heat exchanger (DHE), which is in fast-developing and extremely suitable for deep-earth geothermal energy exploitation. The SLGHP itself has very high heat transfer coefficient, making the poor heat transfer capability of the surrounding geothermal formulations become the bottleneck constraining the overall performance of the SLGHP geothermal system. Inspired by the enhancing effect of the flowing groundwater in the aquifers on the thermal performance of the traditional DHE system, the present work proposes a heat transfer enhancement strategy based on arousing inter-layer crossflow in wellbore-connected multi-aquifers for the SLGHP geothermal system. A detailed numerical study is conducted to examine the effects of key parameters like the permeability and thickness of aquifers, the distance and pressure difference between aquifers. It is found that: i) a larger aquifer permeability leads to larger heat extraction rate of the SLGHP, but the heat extraction rate increment decreases due to the marginal effect when the aquifer permeability is larger than 10−12 m2; ii) a larger pressure difference improves the heat extraction of the SLGHP, the groundwater flow pattern from the deep to the shallow aquifers rather than the reversed pattern is found to be more beneficial due to the geothermal gradient; iii) the distance between aquifers shows a composite impact on the heat extraction performance of the SLGHP. A larger distance not only enlarges the heat transfer area between the SLGHP and the groundwater, but also creates an impeding effect on the heat uptake of SLGHP from the geothermal formation owing to the presentence of temperature-lowered groundwater in the flow path ending-part in the wellbore. In addition, the aquifer's thickness is found to have great impacts on the SLGHP heat extraction rate, and the "cask" effect may be encountered when the thickness difference between the connected aquifers is considerably large. [ABSTRACT FROM AUTHOR]

SiC/multi-walled carbon nanotube (MWCNT) composites are considered to be promising materials for high-temperature electromagnetic wave (EMW) absorption due to their strong thermal stability and tunable dielectric properties. However, the EMW absorption performance of these composites is limited by poor impedance matching. This study proposes a novel multiscale structure synergistic regulation approach to enhance EMW absorption performance, which involves constructing a heterointerface structure and a triple periodic minimal surface (TPMS) meta-structure. The addition of a SiO 2 shell as an impedance layer to the SiC/MWCNT core to improve the intrinsic impedance. Meanwhile, the heterointerface between the core-shell structure leads to multiple interface polarization, significantly enhancing EMW energy dissipation. Consequently, the effective absorption bandwidth (EAB) of SiO 2 –SiC/MWCNT composites increased from 0.88 to 4.56 GHz. Furthermore, a TPMS meta-structure, fabricated by three-dimensional (3D) printing and sol infiltration technology, is developed to further improve impedance matching with the equivalent electromagnetic effect. Simulation and experimental results demonstrate that the SiO 2 –SiC/MWCNT TPMS meta-structure exhibits broadband EMW absorption performance, with the EAB reaching 7.2 GHz. This improvement is attributed to the synergistic regulation of the heterointerface structure and TPMS meta-structure, which provides a good balance between the requirements of electromagnetic loss and impedance matching. Additionally, the composites exhibit excellent oxidation resistance, as their EAB remains almost unchanged after exposure to 1000 °C for 6 h. This research offers a new design paradigm for ultrabroadband design of the nonmagnetic high-temperature absorbing materials. [Display omitted] [ABSTRACT FROM AUTHOR]

A recycled solvent-based green synthesis strategy for 2D/3D zeolitic imidazolate frameworks (ZIFs) has been developed to produce functional nanoporous carbons (NPCs) with tuneable morphology, graphitization, N-doping and high porosity via direct pyrolysis. These tailored NPCs show superior supercapacitance performance over typical NPC derived from MOFs and chemical activation/template-directed methods. [Display omitted] • Two important aspects of green synthesis and improved supercapacitance are reported. • A green synthesis route for ZIF-8 via recycling mother liquors (RMLs) is developed. • Rod-/sheet-/polyhedral-like 2D/3D microstructures are produced with RMLs. • 2D/3D NPCs deliver excellent capacitance values and device-level performance. Carbonized metal–organic frameworks (MOFs)-based nanoporous carbon materials (NPCs) offer attractive activities in electrochemical energy conversion and storage (EECS) applications; however, there is the need for scalable MOFs production under reduced energy/environmental impact. This study reports a green synthesis route for model zeolitic imidazolate framework (ZIF-8) materials via recycling methanol-based mother liquors (ZIF-RML x) under room temperature stirring and their carbonized materials (CZC-RML x) for high-performance supercapacitors. Series of ZIF-RML x samples produced in four recycles offer rod-/sheet-/polyhedral-like 2D/3D microstructures with tuneable internal and external framework and morphological features. Accordingly, CZC-RML x , obtained by direct pyrolysis, with high microporosity and surface area of 1500 m2 g−1 deliver excellent capacitance values of 200–340 F g−1, compared to typical MOFs-derived or chemically activated/templated NPCs, produced via extended chemical processing. Structure-relevant and comparative performance analysis reveal insights for improved charge storage and carbonization-dependent graphitization, nitrogen-doping and microporosity-controlled capacitance characteristics in the CZC-RML x over typical NPCs in literature. The device-level performance with a long-term durability over 21,000 cycles is demonstrated. The practical potential of CZC-RML x is further evaluated by fabricating solid-state cells and their parallel and series circuit combinations result in overall capacitance and voltage boost to 450 F g−1 and 2.4 V, respectively. [ABSTRACT FROM AUTHOR]

This study investigates the influence of elevated temperatures on concrete's pore structure and moisture transfer mechanisms. Concrete samples exposed to temperatures of 200℃, 400℃, 600℃, and 800℃ were subjected to capillary water absorption (CWA) tests, and their properties were analyzed using Scanning Electron Microscopy (SEM) and Nuclear Magnetic Resonance (NMR) techniques employing different sequences (CPMG and SE-SPI). The results reveal after high temperature four distinct categories of pores within the concrete: micropores, mesopores, capillary pores, and macropores. Mesopores are in the highest abundance, followed by capillary pores, macropores, and micropores. As temperature increases, hydration reactions lead to an upsurge in micropores and a decline in the proportion of other pores. With further temperature escalation, the cement slurry's volume alteration causes pore expansion, resulting in a rise in capillary pores and macropores and a decrease in micropores. Furthermore, NMR technology, employing CPMG sequences, identifies three stages in the concrete's CWA process: rapid moisture transfer, moisture transfer rate descent, and moisture transition stage. SE-SPI sequence-based NMR results show that, following high-temperature exposure, moisture transfer within concrete progresses as follows: initially, water rapidly permeates mesopores and capillary pores from the exterior. As CWA time increases, these pores tend to saturate, and water gradually infiltrates micropores and macropores. High temperatures significantly impact the CWA process, enlarging pore sizes and altering the type of pore filling during capillary water absorption in concrete. • The transfer mechanism of water in concrete pores was analyzed in two and three dimensions based on different sequences of NMR technique tests such as Carr-Purcell-Mebum-Gill (CPMG) and Spin Echo Single Point Imaging (SE-SPI). • Based on NMR and SEM techniques to explore the types and percentage of concrete pores after high temperature. • After high temperatures, the distribution of pores in concrete was in the order of mesopores > capillary pores > macropores > micropores in terms of quantity. • There are three different stages in the process of water absorption in concrete: rapid moisture transfer, moisture transfer rate descent, and moisture transition stage. • After high temperature, water initially penetrates into the mesopores and capillary pores and then saturates and enters the micropores and macropores. [ABSTRACT FROM AUTHOR]