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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]

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]

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]

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]

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]

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]

(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]

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]

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]

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]

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]

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: 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]

• 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]

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]

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]

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]

Background: Remimazolam tosilate (HR7056, RT), a novel ultrashort-acting benzodiazepine, can be used for procedural sedation and general anaesthesia. However, few studies have focused on the sedative effect of RT during gastrointestinal endoscopy in elderly patients. The purpose of this study is to compare the sedative effect of RT and propofol for gastrointestinal endoscopy in elderly patients. Methods: A total of 82 patients aged ≥65 years with an American Society of Anaesthesiologists (ASA) grade I-II and a body mass index (BMI) of 18.0 to 30.0 kg/m2 who were scheduled for gastrointestinal endoscopy from Jan 2021 to Aug 2021 were selected and randomly divided into a RT group and a propofol group. Alfentanil 5 μg/kg was used for analgesia in both groups. The RT group was given remimazolam tosilate 0.15 mg/kg with supplemental doses of 0.05 mg/kg as need, while the propofol group was given propofol 1.5 mg/kg with supplemental doses of 0.5 mg/kg. The supplemental doses were determined by the modified observational alertness/sedation assessment (MOAA/S) score and the patients' body movements. Sedative effects, such as the time to loss of consciousness (LOC) (MOAA/S score ≤ 1), successful sedation in one dose, number of supplemental doses after successful induction, and recovery time, were evaluated. Sedation-related side effects, such as injection pain, haemodynamic events and respiratory depression, were also noted. Postoperative nausea and vomiting (PONV), visual analogue scale (VAS) scores at rest, remedial analgesics, and dizziness or headache were recorded. In addition, patients' satisfaction and physician's satisfaction of the procedure were compared between the two groups. Results: Data from 77 patients were analysed. The success rate of sedation in both groups was 100%. The time to LOC (MOAA/S score ≤ 1) in the RT group was longer than that in the propofol group (20.7 ± 6.1s vs. 13.2 ± 5.2s, P < 0.001). There were fewer patients in the RT group reporting injection pain than that in the propofol group (0/39 vs. 5/38, P = 0.025). Haemodynamic events and respiratory depression in the RT group were less frequent than those in the propofol group ((6/39 vs. 17/38, P = 0.005), (2/39 vs. 9/38, P = 0.026), respectively). The number of supplemental doses after successful induction in the RT group was greater than that in the propofol group (4/9/11/13/1/1 vs. 8/4/18/6/2/0 requiring 0, 1, 2, 3, 4 or 5 supplemental doses, P = 0.014). The characteristics of the patients enrolled, postoperative parameters of the patients, and patients' and physician's satisfaction of the procedure were comparable in the two groups. Conclusions: Compared with propofol, RT can be safely and effectively used for gastrointestinal endoscopy sedation in elderly patients, and the incidence of sedation-related adverse reactions, especially haemodynamic events and respiratory depression, is lower. When RT is used, the number of supplemental doses after successful induction may increase slightly. Trial registration: Chictr.org.cn ChiCTR2000040498. Retrospectively registered (date of registration: December 1, 2020). [ABSTRACT FROM AUTHOR]

To distinguish the subtle differences among fine-grained categories, a large amount of well-labeled images are typically required. However, manual annotations for fine-grained categories is an extremely difficult task as it usually has a high demand for professional knowledge. To this end, we propose to directly leverage web images for fine-grained visual recognition. Nevertheless, directly utilizing web images for training fine-grained classification models tends to have poor performance due to the existence of label noise. In this work, we propose an end-to-end method by combining uncertainly dynamic loss correction and global sample selection to solve the problem of label noise. Specifically, we leverage a deep neural network to predict all samples, record the predictions of several recent epochs and calculate the uncertainly dynamic loss for global sample selection in the whole epoch. We conduct experiments on three commonly used noisy fine-grained datasets Web-Aircraft, Web-Bird and Web-Cars. The average classification accuracy is 75.40%, 78.53% and 82.19%, which has 1.20%, 2.16% and 3.43% improvements, respectively. [ABSTRACT FROM AUTHOR]

Background. During total knee arthroplasty (TKA), surgeons mobilize the patella to facilitate clear visualization of the articular surfaces and allow better prosthesis placement. According to the manipulation, this manipulation can be divided into patellar eversion and noneversion. However, the effect of patellar eversion in TKA is controversial, with substantial variability in clinical practice. This systematic review is aimed at assessing the adverse effects of patellar eversion and patellar noneversion duration in TKA. Methods. This updated systematic literature review identified randomized controlled trials comparing patellar eversion and noneversion durations in TKA. Two investigators independently extracted data and evaluated the quality of the studies. A meta-analysis was performed using RevMan version 5.3. Results. Nine studies with a total of 608 patients (730 knees) were included. Of these, 374 knees were classified in the eversion group and 356 knees in the noneversion group. The quality of the studies was high. The results showed that patellar eversion could increase the postoperative complication rate (relative risk RR = 1.67 ; 95% confidence interval [CI], 1.09–2.54; P = 0.02) and postoperative pain before discharge (mean deviation MD = 0.19 ; 95% CI, 0.04–0.34; P = 0.01), compared to noneversion. Additionally, patellar eversion could prolong the time until the patient is able to raise the leg while straightened (MD = 0.42 ; 95% CI, 0.24–0.59; P < 0.00001) and increase the length of stay (MD = 0.65 ; 95% CI, 0.05–1.25; P = 0.03). However, patellar eversion did not influence postoperative pain at 1 year (MD = 0.02 ; 95% CI, -0.23–0.28; P = 0.85), operative time (MD = − 2.66 ; 95% CI, -8.84–3.52; P = 0.40), recovery of quadriceps force throughout the follow-up period, and Insall–Salvati ratio (MD = − 0.04 ; 95% CI, [-0.11–0.02]; P = 0.23). Conclusions. The patellar eversion could increase the postoperative complication rate and postoperative pain. Current evidence supports the avoidance of patellar eversion in TKA. Further large-sample and long-term trials are required to validate these results. [ABSTRACT FROM AUTHOR]

Owing to the advantages of scientific computation and the data feature support provided by artificial intelligence technology, the theoretical exploration and application research of new computing methods for large generators, one of the most expensive energy equipment in a power system, has become a research hotspot toward solving the bearing limit and operation capacity under abnormal working conditions. Because of many factors affecting the distribution of negative sequence loss and temperature rise that have an extremely complex nonlinear relationship, the traditional calculation and prediction methods of negative sequence conditions cannot suitably reflect the time accumulation effect. Therefore, a prediction method of rotor steady-state negative sequence heating based on radial basis function process neural network is proposed in this paper, and a negative sequence working condition prediction model is established. Accordingly, this study focuses on the study of the relationship among negative sequence heating characteristics, negative sequence component proportion, and transverse slot; additionally, their influence degree, variation relationship, and main principles are further explored that provide a theoretical basis for the design and operation of large generators. As observed from the test results, the steady-state negative sequence condition prediction method based on the improved genetic algorithm radial basis function process neural network features high accuracy; it is a feasible prediction method, specifically for negative sequence conditions of large generators. [ABSTRACT FROM AUTHOR]

Virtual synchronous machine (VSM) based high voltage dc systems enhance the inertia of the power system. However, the dynamic interactions between the VSM-based rectifier station, the inverter station, and the grid could induce the system oscillation, which has been investigated in this article. At first, the hybrid ac–dc impedance models of the VSMs considering the coupling between the ac and dc dynamics are established. Then, the relationships between the dc impedance, dq-frame impedance, and the hybrid ac–dc impedance are presented. It is found that the dc impedance of the VSM-based inverter station and the d-d channel impedance of the dq-frame impedance of the rectifier station behave as negative resistors in the low-frequency range. Moreover, a five-dimensional impedance stability criterion based on the hybrid ac–dc impedance and generalized inverse Nyquist criterion is proposed to assess the system stability. The analysis results show that the low-frequency oscillation occurs when the grid short-circuit ratio of the rectifier station is small. Finally, the simulation and experimental results verify the impedance models and the stability criterion. [ABSTRACT FROM AUTHOR]

Source-side virtual synchronous machines (VSGs) and load-side VSMs (LVSM) are gradually utilized together in the microgrid to provide virtual inertia and damping. However, instability occurs in the islanded microgrid system due to the interaction dynamics between the VSG and the LVSM, which has been investigated in this article. At first, the dq-frame impedance models of the VSG and the LVSM are established and compared. It is revealed that the d-d channel impedance of LVSM behaves the negative resistor with a V-type magnitude in the low-frequency range, which easily interacts with the d–d channel impedance of the VSG and leads to instability of the system. Thus, the inductor current feedforward control and the additional voltage feedback control are proposed for the VSG to reshape its impedance. It diminishes the impedance magnitude and generates the active impedance of the VSG. In this way, the low-frequency interaction between the VSG and the LVSM can be mitigated. Besides, the proposed control preserves the dynamic performance of the system. Finally, simulations and experiments verify the effectiveness of stability analyses and the proposed suppression method. [ABSTRACT FROM AUTHOR]

As an ordinary alteration mineral in the process of fluid–rock interaction, chlorite (most especially its chemical composition) has the potential to become an effective tool to reveal the physicochemical conditions during alteration and help exploration. However, its elemental characteristics during the chloritization process are yet to be clearly understood. The Dehua‐Youxi‐Yongtai (DYY) ore district in south‐east China is one of the potential areas of gold and polymetallic deposits. Lying in the north‐west section of the DYY ore district, the Donghua area is notable for its remarkable metallogenic potential, and porphyry‐epithermal systems might have developed in the area. This study focuses on the elemental characteristics of chlorite in the Donghua area as footprints of the alteration process and mineralization vectoring. According to the geological features and occurrences, the chlorite from Donghua can be divided into two generations: (a) Chlorite I is closely related to chloritization developed in intrusive and volcanic rocks (Permian quartz monzobiorite and Jurassic volcanic rocks of Changlin Formation), and (b) chlorite II is accompanied by superimposed hydrothermal overprinting. The alteration process suggested by overprinting chlorite II can be regarded as almost coeval with the ca. 154–153 Ma magmatic event, and chlorite II is later than chlorite I generation. According to the geothermometry of the chlorite in Donghua, chlorite I might have crystallized on the temperature of 180–240°C with a peak of ~200°C, and the overprinting chlorite II might have experienced two episodes of hydrothermal/epithermal fluid pulsing. The mineral geochemistry of the trace elements in the two generations of the chlorite in Donghua shows different characteristics. The replacement of Mg2+ by Fe2+ plays an important role for ionic substitution in the octahedral position, especially for chlorite II. The other occasion might be Mg and Fe jointly entering the octahedral position as well as Mg‐ and Fe‐AlVI substitution mechanisms. The enrichment of Mg especially in chlorite II suggests low‐grade oxidation and acid conditions, which might be beneficial for the transportation of metallogenic substances. The obvious differences of Co and Ni are remarkable aspects of the trace elements of chlorite in Donghua, resulted by the ion substitution and function of different octahedral site preference energy. The mineral chemistry of chlorite II from Donghua can be helpful for targeting and exploration vectoring in the DYY ore district. [ABSTRACT FROM AUTHOR]

Cancer-associated fibroblasts (CAFs) deteriorate tumor microenvironment (TME) and hinder intra-tumoral drug delivery. Direct depleting CAFs exists unpredictable risks of tumor metastasis. Epithelial–mesenchymal transition (EMT) is a critical process of CAFs converted from hepatic stellate cells during hepatocellular tumorigenesis; however, until now the feasibility of reversing EMT to battle hepatocellular carcinoma has not been comprehensively explored. In this study, we report a CFH peptide (CFHKHKSPALSPVGGG)-decorated liposomal oxymatrine (CFH/OM-L) with a high affinity to Tenascin-C for targeted inactivating CAFs through reversing EMT, which is verified by the upregulation of E-cadherin and downregulation of vimentin, N-cadherin, and snail protein in vivo and in vitro. After the combination with icaritin-loaded lipid complex, CFH/OM-L obviously boosts the comprehensive anticancer efficacy in both 3D tumor spheroids and stromal-rich tumor xenograft nude mouse models. The combinational therapy not only effectively reversed the in vivo EMT process but also significantly lowered the collagen, creating favorable conditions for deep penetration of nanoparticles. More importantly, CFH/OM-L does not kill but inactivates CAFs, resulting in not only a low risk of tumor metastasis but also a reprogramming TME, such as M1 tumor-associated macrophages polarization and natural killer cells activation. Such strategy paves a moderate way to remold TME without depleting CAFs and provides a powerful tool to design strategies of combinational hepatocellular carcinoma therapy. [ABSTRACT FROM AUTHOR]

To develop an MRI-based radiomics model to predict postlaminar optic nerve invasion (PLONI) in retinoblastoma (RB) and compare its predictive performance with subjective radiologists' assessment. We retrospectively enrolled 124 patients with pathologically proven RB (90 in training set and 34 in validation set) who had MRI scans before surgery. A radiomics model for predicting PLONI was developed by extracting quantitative imaging features from axial T2W images and contrast-enhanced T1W images in the training set. The Kruskal–Wallis test, least absolute shrinkage and selection operator regression, and recursive feature elimination were used for feature selection, where upon a radiomics model was built with a logistic regression (LR) classifier. The area under the curve (AUC) of the receiver operating characteristic (ROC) curve and the accuracy were assessed to evaluate the predictive performance in the training and validation set. The performance of the radiomics model was compared to radiologists' assessment by DeLong test. The AUC of the radiomics model for the prediction of PLONI was 0.928 in the training set and 0.841 in the validation set. Radiomics model produced better sensitivity than radiologists' assessment (81.1% vs 43.2% in training set, 82.4vs 52.9% in validation set). In all 124 patients, the AUC of the radiomics model was 0.897, while that of radiologists' assessment was 0.674 (p < 0.001, DeLong test). MRI-based radiomics model to predict PLONI in RB patients was shown to be superior to visual assessment with improved sensitivity and AUC, and may serve as a potential tool to guide personalized treatment. [ABSTRACT FROM AUTHOR]

0.70BiFeO3‐0.30BaTiO3 (0.70BF‐0.30BT) ceramics have been widely concerned because of their potential applications for high‐temperature piezoelectric devices. In this work, a series of dense 0.70BF‐0.30BT ceramics with average grain size variation from 0.55 to 6.0 μm were prepared. XRD results indicate that 0.70BF‐0.30BT ceramics show the coexistence of rhombohedral and pseudo‐cubic phases and the volume fraction of the rhombohedral phase increase with the grain size. The dielectric, ferroelectric and piezoelectric properties increase with the grain size initially from 0.55 to 5.0 μm and then decrease slightly. Values of d33, Pr, and εr, of 0.70BF‐0.30BT ceramics with the grain size of 5.0 μm are 185 pC/N, 21.2 μC/cm2, and 638, respectively, about five times higher than those ceramics with fine‐grain of 0.55 μm. Of particular importance is that 0.70BF‐0.30BT ceramics with large grain sizes possess better piezoelectric thermal stability due to the much stabler poled domain state with the rising temperature. The detailed structural studies indicate that the enhanced electric properties are owing to the significantly improved domain motion and the increased lattice distortion. This clarifying the relationship between electrical properties and grain size offers a novel way of improving the performances of piezoceramics. [ABSTRACT FROM AUTHOR]

Electrocardiogram (ECG) outcomes serve as early manifestations of cardiovascular functional or structural changes. While temperature fluctuation has been demonstrated to be a risk factor for cardiovascular diseases, few epidemiological studies have reported its relationship with ECG outcomes. In this study, we employed temperature anomaly (TA) as an innovative indicator of temperature fluctuation to quantify its detrimental impacts on ECG outcomes. A longitudinal study design was conducted using the repeated ECG records of the China National Stroke Screening Survey from 2013 to 2019. Only individuals undergoing at least two ECG tests were included. The daily temperature was assimilated by combining three kinds of data: in situ observations, satellite remote sensing measurements and weather research forecast simulations. We used generalized estimating equations to control for autocorrelation among repeated records and to estimate the association between TA and the risk of ECG abnormalities. We found 6837 events of ECG abnormalities in 47,286 individuals with 102,030 visits. Each unit increment of TA increased the risk of ECG abnormalities [odds ratio (OR) = 1.009, 95% confidence interval (CI): 1.001–1.017] and the risk of myocardial ischemia (OR = 1.061, 95% CI: 1.012–1.111). Hierarchic analyses presented a similar association of TA with both ECG abnormalities (OR = 1.017, 95% CI: 1.008–1.026) and myocardial ischemia (OR = 1.061, 95%CI: 1.011–1.114) in Northern China, but not in Southern China. The exposure-response relationship was estimated as a U-shaped curve centered at the TA value of zero. Sudden warming tended to increase the risk of ECG abnormalities and myocardial ischemia, and sudden cooling tended to increase the risk of atrial fibrillation. All these detrimental effects of TA could be modified by specific individual characteristics. In summary, ambient temperature fluctuation increased the risk of ECG abnormalities. This result indicated that regular ECG tests could be an early-warning measure for monitoring the adverse health effects of temperature fluctuations. • Temperature anomaly (TA) is an innovative index reflecting temperature fluctuations. • Each unit increment of TA increases the risk of ECG abnormalities. • The exposure-response curve is U-shaped which centered at the TA value of zero. • ECG tests can be used to monitor the health effects of temperature fluctuations. [ABSTRACT FROM AUTHOR]

The study of high-speed rotating matter is a crucial research topic in physics due to the emergence of novel phenomena. In this letter, we combined cranking covariant density functional theory (CDFT) with a similarity renormalization group approach to decompose the Hamiltonian from the cranking CDFT into different Hermite components, including the non-relativistic term, the dynamical term, the spin-orbit coupling, and the Darwin term. Especially, we obtained the rotational term, the term relating to Zeeman-like effect, and the spin-rotation coupling due to consideration of rotation and spatial component of vector potential. By exploring these operators, we aim to identify novel phenomena that may occur in rotating nuclei. Signature splitting, Zeeman-like effect, and spin-rotation coupling are among the potential novelties that may arise in rotating nuclei. Additionally, we investigated the observability of these phenomena and their dependence on various factors such as nuclear deformation, rotational angular velocity, and magnetic field-like strength. [ABSTRACT FROM AUTHOR]

Background: China has made tremendous progresses in serving the needs of its people living with rare diseases in the past decade, especially over the last 5 years. The Chinese government's systematic approach included a series of coordinated initiatives, amongst these are: forming the Rare Disease Expert Committee (2016), funding the "Rare Diseases Cohort Study" (2016-2020), and publishing its first "Rare Disease Catalog" (2018). Herein, we present the National Rare Diseases Registry System (NRDRS)-China's first national rare diseases registry, and the analysis of cases registered in the first 5 years ending Dec 31, 2020.Results: The total 62,590 cases covered 166 disease/disease types, forming 183 disease cohorts. The data from nearly 22% of them (13,947 cases) is also linked to valuable biological samples. The average age of definitive diagnosis was 30.88 years; 36.07% of cases were under 18 years of age. Regional distribution analysis showed 60% of cases were from the more developed, wealthier East and North China, suggesting the local availability of quality care and patients' financial status were key access factors. Finally, 82.04% of cases were registered from the five clinical departments: Neurology, Endocrine, Hematology, Cardiovascular, and Nephrology, suggesting that either these are most affected by rare diseases, or that there were disease non-specific ascertainment factors.Conclusions: The preliminary analysis of the first 5-year's data provides unique and valuable insight on rare disease distribution in China, and higlights the directions for enhancing equity, scale and utility. [ABSTRACT FROM AUTHOR]

Premise: The distribution of genetic diversity on the landscape has critical ecological and evolutionary implications. This may be especially the case on a local scale for foundation plant species because they create and define ecological communities, contributing disproportionately to ecosystem function. Methods: We examined the distribution of genetic diversity and clones, which we defined first as unique multilocus genotypes (MLG), and then by grouping similar MLGs into multilocus lineages. We used 186 markers from inter‐simple sequence repeats (ISSR) across 358 ramets from 13 patches of the foundation grass Leymus chinensis. We examined the relationship between genetic and clonal diversities, their variation with patch size, and the effect of the number of markers used to evaluate genetic diversity and structure in this species. Results: Every ramet had a unique MLG. Almost all patches consisted of individuals belonging to a single multilocus lineages. We confirmed this with a clustering algorithm to group related genotypes. The predominance of a single lineage within each patch could be the result of the accumulation of somatic mutations, limited dispersal, some sexual reproduction with partners mainly restricted to the same patch, or a combination of all three. Conclusions: We found strong genetic structure among patches of L. chinensis. Consistent with previous work on the species, the clustering of similar genotypes within patches suggests that clonal reproduction combined with somatic mutation, limited dispersal, and some degree of sexual reproduction among neighbors causes individuals within a patch to be more closely related than among patches. [ABSTRACT FROM AUTHOR]

Embedded applications are becoming more complex and are required to utilize computing platform resources more efficiently. Existing dynamic memory allocation (DSA) schemes cannot adaptively perform memory management according to the environment in which they are located or integrate various memory allocation strategies, making it impossible to guarantee a constant execution time. Efficient memory utilization is a crucial challenge for developers, especially in embedded OSs (operating systems). In this paper, we propose an adaptive layered segregated fit (ALSF) scheme for DSA. The ALSF scheme combines dynamic two-dimensional arrays and bitmaps, completes the allocation and freeing of memory blocks within constant execution time, and uses memory splitting technology to reduce internal fragmentation. The proposed scheme also adjusts the number of segregated lists by analyzing the system's allocation of different memory sizes, which improves the matching accuracy of memory blocks. We conducted a comparative experimental analysis and investigation of the ALSF and two-level segregated fit (TLSF) schemes in the Zephyr OS. Experiments show that the average memory utilization of the proposed ALSF scheme reaches 94.95%. Compared with the TLSF scheme, our scheme has a 12.99% higher allocation success rate in the memory-scarce environment, and the execution speeds of the two are similar. [ABSTRACT FROM AUTHOR]

Lead‐free 0.75BiFeO3–0.25BaTiO3 (0.75BF–0.25BT) ceramics have been extensively studied because of their high Curie temperature. The aging behavior and thermal stability of piezoceramics play decisive roles in their device applications. In this work, effects of Mn doping on the phase structure, aging behavior, and thermal stability of 0.75BF–0.25BT ceramics were characterized and related mechanisms were investigated. With the increase in Mn content, the typical rhombohedral phase of 0.75BF–0.25BT ceramics changed to the coexistence of pseudo‐cubic and rhombohedral phases. Mn modification enhanced the aging behavior and thermal stability of ceramics obviously. The aging rates of d33 and kp for 0.75BF‐0.25BT ceramics with 1.0 mol% Mn are 1.3% and 1.1%, respectively, which are only 1/4 those values for the undoped ceramics. The variation of εr of 0.75BF‐0.25BT ceramics with 1.0 mol% Mn is half of undoped ceramics under 500℃. The depoling temperature of 0.75BF‐0.25BT ceramics with 1.0 mol% Mn was 450℃, which is about 200℃ higher than that of undoped ceramics. The enhanced aging behavior results from the decreased defect concentrations, and the better thermal stability is owing to the significantly improved poling state due to the enhanced resistivity, large grain size, and decreased crystal distortion by Mn modification. These results reflect that a proper amount of Mn doping is an effective way to enhance the aging behavior and electric thermal stability. [ABSTRACT FROM AUTHOR]

Background: Currently, automatic esophagus segmentation remains a challenging task due to its small size, low contrast, and large shape variation. We aimed to improve the performance of esophagus segmentation in deep learning by applying a strategy that involves locating the object first and then performing the segmentation task. Methods: A total of 100 cases with thoracic computed tomography scans from two publicly available datasets were used in this study. A modified CenterNet, an object location network, was employed to locate the center of the esophagus for each slice. Subsequently, the 3D U-net and 2D U-net_coarse models were trained to segment the esophagus based on the predicted object center. A 2D U-net_fine model was trained based on the updated object center according to the 3D U-net model. The dice similarity coefficient and the 95% Hausdorff distance were used as quantitative evaluation indexes for the delineation performance. The characteristics of the automatically delineated esophageal contours by the 2D U-net and 3D U-net models were summarized. Additionally, the impact of the accuracy of object localization on the delineation performance was analyzed. Finally, the delineation performance in different segments of the esophagus was also summarized. Results: The mean dice coefficient of the 3D U-net, 2D U-net_coarse, and 2D U-net_fine models were 0.77, 0.81, and 0.82, respectively. The 95% Hausdorff distance for the above models was 6.55, 3.57, and 3.76, respectively. Compared with the 2D U-net, the 3D U-net has a lower incidence of delineating wrong objects and a higher incidence of missing objects. After using the fine object center, the average dice coefficient was improved by 5.5% in the cases with a dice coefficient less than 0.75, while that value was only 0.3% in the cases with a dice coefficient greater than 0.75. The dice coefficients were lower for the esophagus between the orifice of the inferior and the pulmonary bifurcation compared with the other regions. Conclusion: The 3D U-net model tended to delineate fewer incorrect objects but also miss more objects. Two-stage strategy with accurate object location could enhance the robustness of the segmentation model and significantly improve the esophageal delineation performance, especially for cases with poor delineation results. [ABSTRACT FROM AUTHOR]

In recent years, the virtual synchronous generator (VSG) concept has been widely studied to integrate renewable energy sources. However, instability occurs due to the implementation of the dc-link voltage controllers under the weak grid, and its mechanism remains unclear, which is investigated in this article. At first, the wideband dq-frame impedance models of the VSGs with the dc-link voltage controllers for two cases are established. Then, the stability analyses of the VSGs are compared based on these impedance models. It is revealed that the interaction dynamics between the dc-link voltage loop and the active loop lead to the negative resistor behavior of the q–q channel impedances for both VSGs, which induces the emerging oscillations of the system in a weak grid. Besides, as a useful design guideline, the parameter design of the VSGs is proposed to enhance the system stability. Finally, the experimental results obtained from a 100-kW prototype system show good agreement with simulated results, validating the impedance models and theoretical analysis. [ABSTRACT FROM AUTHOR]

Understanding the adaptive changes in maize kernels under high-temperature stress during grain formation stage is critical for developing strategies to alleviate the negative effects on yield and quality. In this study, we subjected waxy maize (Zea mays L. sinensis Kulesh) to four different temperature regimes from 1–15 d after pollination (DAP), namely normal day/normal night (control), hot day/normal night, normal day/hot night, and hot day/hot night. Compared to the control, the three high-temperature treatments inhibited kernel development and starch deposition. To understand how the kernels responded to high-temperature stress, their transcriptomes, proteomes, and metabolomes were studied at 10 DAP and 25 DAP. This showed that genes and proteins related to kernel development and starch deposition were up- and down-regulated, respectively, at 10 DAP, but this pattern was reversed at 25 DAP. Metabolome profiling under high-temperature stress showed that the accumulation patterns of metabolites at 10 DAP and 25 DAP were inversely related. Our multiomics analyses indicated that the response to high-temperature stress of signaling pathways mediated by auxin, abscisic acid, and salicylic acid was more active at 10 DAP than at 25 DAP. These results confirmed that high-temperature stress during early kernel development has a carry-over effect on later development. Taken together, our multiomics profiles of developing kernels under high-temperature stress provide insights into the processes that underlie maize yield and quality under high-temperature conditions. [ABSTRACT FROM AUTHOR]

Background: Kernel development and starch formation are the primary determinants of maize yield and quality, which are considerably influenced by drought stress. To clarify the response of maize kernel to drought stress, we established well-watered (WW) and water-stressed (WS) conditions at 1–30 days after pollination (dap) on waxy maize (Zea mays L. sinensis Kulesh). Results: Kernel development, starch accumulation, and activities of starch biosynthetic enzymes were significantly reduced by drought stress. The morphology of starch granules changed, whereas the grain filling rate was accelerated. A comparative proteomics approach was applied to analyze the proteome change in kernels under two treatments at 10 dap and 25 dap. Under the WS conditions, 487 and 465 differentially accumulated proteins (DAPs) were identified at 10 dap and 25 dap, respectively. Drought induced the downregulation of proteins involved in the oxidation–reduction process and oxidoreductase, peroxidase, catalase, glutamine synthetase, abscisic acid stress ripening 1, and lipoxygenase, which might be an important reason for the effect of drought stress on kernel development. Notably, several proteins involved in waxy maize endosperm and starch biosynthesis were upregulated at early-kernel stage under WS conditions, which might have accelerated endosperm development and starch synthesis. Additionally, 17 and 11 common DAPs were sustained in the upregulated and downregulated DAP groups, respectively, at 10 dap and 25 dap. Among these 28 proteins, four maize homologs (i.e., A0A1D6H543, B4FTP0, B6SLJ0, and A0A1D6H5J5) were considered as candidate proteins that affected kernel development and drought stress response by comparing with the rice genome. Conclusions: The proteomic changes caused by drought were highly correlated with kernel development and starch accumulation, which were closely related to the final yield and quality of waxy maize. Our results provided a foundation for the enhanced understanding of kernel development and starch formation in response to drought stress in waxy maize. [ABSTRACT FROM AUTHOR]

During sintering of the silica-based ceramic core of turbine blades, a phenomenon called "nonuniform sintering" occurs that negatively affects the thermal and mechanical properties of the core. Standard samples of silica-based core were prepared by an injection molding method and sintered with alumina backfilling powder with different sodium contents. The effect of sodium content on the nonuniform sintering of silica-based cores and the thermal and mechanical properties was evaluated. Results show that the sintering level and the content of α-cristobalite in the surface layer are significantly higher than that of the sample interior. A considerable number of microcracks are found in the surface layer due to the β to α-phase transition of cristobalite. As the sodium content in the alumina powder decreases, the level of the nonuniform sintering and the amount of crystallized cristobalite in the surface layer decrease, which is beneficial to the thermal expansion and flexural strength at ambient temperature. The flexural strength and thermal deformation at high temperature are improved by reducing the surface cracks, but deteriorated with the decrease of the cristobalite crystallization when the surface cracks are macroscopically invisible. [ABSTRACT FROM AUTHOR]

Background: Accumulation of alpha-synuclein (α-syn) is a main pathological hallmark of Parkinson's and related diseases, which are collectively known as synucleinopathies. Growing evidence has supported that the same protein can induce remarkably distinct pathological progresses and disease phenotypes, suggesting the existence of strain difference among α-syn fibrils. Previous studies have shown that α-syn pathology can propagate from the peripheral nervous system (PNS) to the central nervous system (CNS) in a "prion-like" manner. However, the difference of the propagation potency from the periphery to CNS among different α-syn strains remains unknown and the effect of different generation processes of these strains on the potency of seeding and propagation remains to be revealed in more detail. Methods: Three strains of preformed α-syn fibrils (PFFs) were generated in different buffer conditions which varied in pH and ionic concentrations. The α-syn PFFs were intramuscularly (IM) injected into a novel bacterial artificial chromosome (BAC) transgenic mouse line that expresses wild-type human α-syn, and the efficiency of seeding and propagation of these PFFs from the PNS to the CNS was evaluated. Results: The three strains of α-syn PFFs triggered distinct propagation patterns. The fibrils generated in mildly acidic buffer led to the most severe α-syn pathology, degeneration of motor neurons and microgliosis in the spinal cord. Conclusions: The different α-syn conformers generated in different conditions exhibited strain-specific pathology and propagation patterns from the periphery to the CNS, which further supports the view that α-syn strains may be responsible for the heterogeneity of pathological features and disease progresses among synucleinopathies. [ABSTRACT FROM AUTHOR]