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A broadband online X-ray spectrometer has been designed and commissioned at the SUD beamline of the Shanghai Soft X-ray Free-Electron Laser Facility, which can deliver both SASE and seeded FEL pulses to user experiments, spanning the photon energy range of 50–620 eV. The resolving powers of the spectrometer calibrated via online measurement at 92 eV and 249 eV are ∼20000 and ∼15000, respectively, and the absolute photon energy is characterized by an electron time-of-flight spectrometer. The high energy resolution provided by the spectrometer can differentiate the fine structure in the FEL spectrum, to determine its pulse length.

The Weixinan Sag in the Beibuwan Basin is rich in shale oil resources. However, the reservoirs exhibit rapid phase changes, strong compartmentalization, thin individual layers, and high-frequency vertical variations in the thin interbedded sandstone and mudstone. These factors can restrict the height of hydraulic fracture propagation. Additionally, the low-porosity and low-permeability shale oil reservoirs face challenges such as low production rates and rapid decline. To address these issues, the Plannar3D full 3D fracturing model was used to simulate hydraulic fracture propagation and to study the main controlling factors for fracture propagation in the second member of the Liushagang Formation. Based on the concept of geological–engineering integration, a sweet spot evaluation was conducted to identify reservoirs with relatively better brittleness, reservoir properties, and oil content as the fracturing targets for horizontal wells. The UFM model was then applied to optimize fracturing parameters. This study indicates that the matrix-type oil shale has a high clay mineral content, resulting in a low Young’s modulus and poor brittleness. This makes hydraulic fracture propagation difficult and leads to less effective reservoir stimulation. In contrast, hydraulic fractures propagate more easily in high-brittleness interlayer-type oil shale. Therefore, it is recommended to prioritize the extraction of shale oil from interlayer-type oil shale reservoirs. The difference in interlayer stress is identified as the primary controlling factor for cross-layer fracture propagation in the study area. Based on the concept of geological–engineering integration, a sweet spot evaluation standard was established for the second member of the Liushagang Formation, considering both reservoir quality and engineering quality. Four sweet spot zones of interlayer-type oil shale reservoirs were identified according to this evaluation standard. To achieve uniform fracture initiation, a differentiated segment and cluster design was implemented for certain high-angle sections of well WZ11-6-5d. Interlayer-type oil shale was selected as the fracturing target, and the UFM was used for hydraulic fracture propagation simulation. Fracturing parameters were optimized with a focus on hydraulic fracture characteristics and the estimated ultimate recovery (EUR). The optimization results were as follows: a single-stage length of 50 m, cluster spacing of 15 m, pump injection rate of 10 m3/min, fluid intensity of 25 m3/m, and proppant intensity of 3.5 t/m. The application of these optimized fracturing parameters in field operations resulted in successful fracturing and the achievement of industrial oil flow.

Fruit is a major source of vitamins, minerals, and dietary fiber in people’s daily lives. Leaf diseases caused by climate change and other factors have significantly reduced fruit production. Deep learning methods for segmenting leaf diseases can effectively mitigate this issue. However, challenges such as leaf folding, jaggedness, and light shading make edge feature extraction difficult, affecting segmentation accuracy. To address these problems, this paper proposes a method based on EFS-Former. The expanded local detail (ELD) module extends the model’s receptive field by expanding the convolution, better handling fine spots and effectively reducing information loss. H-attention reduces computational redundancy by superimposing multi-layer convolutions, significantly improving feature filtering. The parallel fusion architecture effectively utilizes the different feature extraction intervals of the convolutional neural network (CNN) and Transformer encoders, achieving comprehensive feature extraction and effectively fusing detailed and semantic information in the channel and spatial dimensions within the feature fusion module (FFM). Experiments show that, compared to DeepLabV3+, this method achieves 10.78%, 9.51%, 0.72%, and 8.00% higher scores for mean intersection over union (mIoU), mean pixel accuracy (mPA), accuracy (Acc), and F_score, respectively, while having 1.78 M fewer total parameters and 0.32 G lower floating point operations per second (FLOPS). Additionally, it effectively calculates the ratio of leaf area occupied by spots. This method is also effective in calculating the disease period by analyzing the ratio of leaf area occupied by diseased spots. The method’s overall performance is evaluated using mIoU, mPA, Acc, and F_score metrics, achieving 88.60%, 93.49%, 98.60%, and 95.90%, respectively. In summary, this study offers an efficient and accurate method for fruit tree leaf spot segmentation, providing a solid foundation for the precise analysis of fruit tree leaves and spots, and supporting smart agriculture for precision pesticide spraying.

Soil, a non-renewable resource, requires continuous monitoring to prevent degradation and support sustainable agriculture. Visible-near-infrared (Vis-NIR) spectroscopy is a rapid and cost-effective method for predicting soil properties. While traditional machine learning methods are commonly used for modeling Vis-NIR spectral data, large datasets may benefit more from advanced deep learning techniques. In this study, based on the large soil spectral library LUCAS, we aimed to enhance regression model performance in soil property estimation by combining Transformer and convolutional neural network (CNN) techniques to predict 11 soil properties (clay, silt, pH in CaCl2, pH in H2O, CEC, OC, CaCO3, N, P, and K). The Transformer-CNN model accurately predicted most soil properties, outperforming other methods (partial least squares regression (PLSR), random forest regression (RFR), support vector machine regression (SVR), Long Short-Term Memory (LSTM), ResNet18) with a 10–24 percentage point improvement in the coefficient of determination (R2). The Transformer-CNN model excelled in predicting pH in CaCl2, pH in H2O, OC, CaCO3, and N (R2 = 0.94–0.96, RPD > 3) and performed well for clay, sand, CEC, P, and K (R2 = 0.77–0.85, 2 < RPD < 3). This study demonstrates the potential of Transformer-CNN in enhancing soil property prediction, although future work should aim to optimize computational efficiency and explore a wider range of applications to ensure its utility in different agricultural settings.

The calmodulin-binding transcriptional activator (CAMTA) is a small, conserved gene family in plants that plays a crucial role in regulating growth, development, and responses to various abiotic stress. Given the significance of the CAMTA gene family, various studies have been dedicated to uncovering its functional characteristics. In this study, genome-wide identification and bioinformatics analysis were conducted to explore CAMTAs in Phoebe bournei. A total of 17 CAMTA genes, each containing at least one domain from CG-1, TIG, ANK, or IQ, were identified in the P. bournei genome. The diversity of PbCAMTAs could be varied depending on their subcellular localization. An analysis of protein motifs, domains, and gene structure revealed that members within the same subgroup exhibited similar organization, supporting the results of the phylogenetic analysis. Gene duplications occurred among members of the PbCAMTA gene family. According to the cis-regulatory element prediction and protein–protein interaction network analysis, eight genes were subjected to qRT-PCR under drought, heat, and light stresses. The expression profiles indicated that PbCAMTAs, particularly PbCAMTA2, PbCAMTA12, and PbCAMTA16, were induced by abiotic stress. This study provides profound insights into the functions of CAMTAs in P. bournei.

Postpartum depression (PPD) has a significant impact on the physical and mental health of mothers, potentially leading to symptoms such as low mood, fatigue, and decreased appetite. It may also affect the healthy growth of the infant. The onset of PPD is closely related to abnormalities in inflammation and the immune system. PPD patients exhibit abnormalities in the proportion of peripheral blood immune cells, along with an increase in pro-inflammatory cytokines. Excessive pro-inflammatory cytokines in peripheral blood can disrupt the blood-brain barrier (BBB) by activating astrocytes and reducing transendothelial electrical resistance (TEER), allowing peripheral immune cells or cytokines to enter the brain and trigger inflammation, ultimately leading to the onset of depression. In addition, PPD lacks safe and effective treatment medications. In this study, we collected peripheral blood from both healthy postpartum women and those with PPD, conducted single cell RNA sequencing (scRNA-seq), and used an in-house analytical tool scSTAR to reveal that PPD patients exhibit elevated proportions of peripheral blood cDC2 and Proliferation B cells, which are significantly correlated with IL-1β. Additionally, animal experiments were designed to validate that 919 granules can improve PPD by modulating the levels of peripheral blood IL-1β, providing a potential therapeutic mechanism for PPD treatment.

Vacuum volatilization is a clean and efficient method for metal purification, alloy separation, and comprehensive recovery of secondary resources. The evaporation kinetics of In and In–Sn alloys were investigated to better understand the evaporation mechanism during the vacuum volatilization of In. The evaporation rates of the In and In–Sn alloys at 1173–1373 K and 5 Pa increased significantly with increasing temperature in accordance with the equation ω = e(a+b∙T). The evaporation rates at 1323 K and 5 Pa decreased with increasing crucible depth in accordance with the equation ω = a2+(a1-a2)/(1+e(h-b)/c). For In and In–Sn, the total mass-transfer coefficients of In were obtained at different temperatures and crucible depths. A theoretical kinetic model of In was established and limiting links were obtained vacuum volatilization of In and In–Sn.

In order to solve the prediction problem of water inrush from coal seam floor, a prediction model of water inrush from coal seam floor based on principal component analysis and Logistic regression method was proposed. Through the analysis of the risk factors of floor water inrush, six variables, including the thickness of the aquifers, the pressure of confined water, the fall of the fault, the distance between the fault and the working face, the mining height of the coal seam, and the dip angle of the coal seam, are selected as the initial impact indicators to study the floor water inrush. First, the principal component analysis method is used to reduce the dimensions of the original index data, and the established Logistic regression model is used to analyze and predict the data. Then, five groups of sample data to be tested are used to verify the model. The results show that the comprehensive prediction accuracy of the model for water inrush samples reaches 90% at the highest, and the prediction accuracy reaches 80% when the data to be measured is used for back judgment, which shows that the prediction model has certain reliability and can be used as a new method for predicting water inrush from coal mine floor.

Designing a triply periodic minimal surface (TPMS) lattice structure is a new method for lightweight. Compared with the previous foam- and strut-based structure, the TPMS lattice structure has the advantages of precise control of mechanical properties and convenient modelling. In this paper, under a quasi-static compression load, the effect of solution and aging treatment on the mechanical properties and energy absorption capacity of graded skeleton diamond (GSKD), graded sheet diamond (GSHD), uniform skeleton diamond (USKD) and uniform sheet diamond (USHD) fabricated through selective laser melting (SLM) were studied. The experiment results show that the sheet structures have better mechanical properties (elastic modulus, yield strength, platform stress and energy absorption) than the skeleton structures, and that the uniform structures have a higher energy absorption capacity (WV, εd) than the gradient structures, with the WV,εd of the as-built USHD sample reaching 2.11 times that of the GSKD sample. Moreover, the mechanical properties of each structure have different degrees of sensitivity to heat treatment conditions. Heat treatment has the greatest influence on the platform stress and initial strain of densification of GSKD, on the Young's modulus of USHD and on the energy absorption of USKD.

A. sinensis polysaccharide (ASP), one of the effective components of A. sinensis, has been used to treat inflammatory diseases in China. However, its effect on rheumatoid arthritis (RA) is unknown. The purpose of this study was to explore the anti-inflammatory effects and mechanisms of ASP on RA using a rat model of collagen-induced arthritis (CIA). For evaluation of the therapeutic effects of ASP in vitro, the CIA model was used. Our study showed that ASP (100 and 200 μg/mL) dose-dependently inhibited tumor necrosis factor (TNF)-α-induced (10 ng/mL) proliferation, migration, and invasion of fibroblast-like synovial (FLS) cells, promoted apoptosis, and arrested the cell cycle in G0/G1 phase (P

The low bone mineral density due to abnormally activated osteoclasts can induce bone disorders such as osteopenia and osteoporosis. MiR-25-3p modulates sphingosine-1-phosphate receptor 1 (S1PR1) expression to enhance osteoclast motivation. The association between miR-25 rs41274221 polymorphism and osteoporosis susceptibility is unknown. Herein, 300 patients with osteoporosis and 320 healthy controls were genotyped using polymerase chain reaction and Sanger sequencing to explore the role of miR-25 rs41274221 polymorphism in osteoporosis. The odds ratios (ORs) and 95% confidence intervals (CIs) were determined using logistic regression analysis. Additionally, this study also investigated the effect of miR-25 rs41274221 polymorphism on the expression of miR-25 and its target gene S1PR1 through luciferase reporter gene, qRT-PCR, and Western blot. The rs41274221 in miR-25 was found to be positively associated with osteoporosis and can be viewed as a protective factor. Furthermore, miR-25 rs41274221 polymorphism decreased the risk of osteoporosis among smokers. The TargetScan database predictions and dual-luciferase activity demonstrated that S1PR1 may be the target gene of miR-25. MiR-25 downregulated the S1PR1 mRNA and protein expressions. Patients with the AA genotype of rs41274221 polymorphism showed higher S1PR1 expression compared with the GG genotype. In conclusion, miR-25 rs41274221 polymorphism decreases the risk of osteoporosis through modifying the binding with S1PR1 and may serve as a novel biomarker for early diagnosis of osteoporosis.

Abstract Osteoarthritis (OA) is a widespread chronic degenerative joint disease characterized by the degeneration of articular cartilage or inflamed joints. Our findings indicated that treatment with artemisinin (AT) downregulates the protein levels of MMP3, MMP13, and ADAMTS5, which are cartilage degradation-related proteins in OA, and inhibits the expression of inflammatory factors in interleukin-1β (IL-1β)-stimulated chondrocytes. However, the mechanism of the role of AT in OA remains unclear. Here, we performed gene sequencing and bioinformatics analysis in control, OA, and OA + AT groups to demonstrate that several mRNA candidates were enriched in the PI3K/AKT/mTOR signaling pathway, and TNFSF11 was significantly downregulated after AT treatment. TNFSF11 was downregulated in the OA + AT group, whereas it was upregulated in rat OA tissues and OA chondrocytes. Therefore, we confirmed that TNFSF11 was the target gene of AT. In addition, our study revealed that AT relieved cartilage degradation and defection by activating mitochondrial autophagy via inhibiting the PI3K/AKT/mTOR signaling pathway in IL-1β-induced chondrocytes. Furthermore, an OA model was established in rats with medial meniscus destabilization. Injecting AT into the knee joints of OA rat alleviated surgical resection-induced cartilage destruction. Thus, these findings revealed that AT relieves OA by activating mitochondrial autophagy by reducing TNFSF11 expression and inhibiting PI3K/AKT/mTOR signaling.

Abstract Background Osteosarcoma (OS) is a common primary bone malignancy. Long noncoding RNA HCG18 is known to play an important role in a variety of cancers. However, its role in OS and relevant molecular mechanisms are unclear. Methods Real-time quantitative PCR was performed to determine the expression of target genes. Function experiments showed the effects of HCG18 and miR-365a-3p on OS cell growth. Results HCG18 expression was increased in OS cell lines. Moreover, in vitro and in vivo experiments demonstrated that HCG18 knockdown inhibited OS cell proliferation. Mechanistically, HCG18 was defined as a competing endogenous RNA by sponging miR-365a-3p, thus elevating phosphoglycerate kinase 1 (PGK1) expression by directly targeting its 3ʹUTR to increase aerobic glycolysis. Conclusion HCG18 promoted OS cell proliferation via enhancing aerobic glycolysis by regulating the miR-365a-3p/PGK1 axis. Therefore, HCG18 may be a potential target for OS treatment.

Remote sensing ecological index (RSEI) has the advantages of rapid, repeatable and relatively accurate in regional eco-environment quality assessment. Due to the lack of consideration of the interaction of adjacent analysis units in RSEI calculation, there is a few uncertainties in the assessment results. Based on RSEI, the landscape diversity index (LDI) was introduced, which considered the heterogeneity caused by the difference between the assessment unit and the adjacent one, and rebuilt modified remote sensing ecological index (MRSEI) to evaluate the eco-environment quality in the artificial oasis of Ningxia section of Yellow River. The results showed that the area of Fair and Poor grades in the low MRSEI year (2000) was greater than that of other grades, and the area of Moderate and Fair grades was greater than that of other grades in the high MRSEI year (2020). The conversion characteristics of different grades were Poor and Fair grades to adjacent high grades. During the study period, the eco-environment quality of the study area was improved, and the composition and pattern of land use types had a significant impact on MRSEI. Introduction of LDI-improved MRSEI can not only include the heterogeneous effect between the analysis unit and the adjacent one, but also consider the spatial scale effect of LDI to make the evaluation results more credible. However, some evaluation factors of RSEI and MRSEI (e.g., LDI, NDVI, and NDBSI) represent the accumulation of surface status over long-time scales, while others (e.g., Wet and LST) reflects only short-time scale features of the land surface. Therefore, how to eliminate the uncertainty caused by temporal scale mismatch is a challenge for RSEI and MRSEI applications.

Near-surface features have a great influence on runoff and detachment processes by overland flow, but the contributions are still unclear on steep slopes with yellow soil in subtropical humid regions. Field scouring experiments were conducted to investigate how near-surface features affect hydraulic parameters and detachment rate by overland flow. Five treatments and a baseline (disturbed rootless bare cropland) were designed to identify the contributions from stem-leaves, litter, biological soil crusts (BSCs), root systems and non-disturbance, respectively. The results showed that (1) the values of velocity, Reynolds number and Froude number for vegetated slopes were significantly lower than that of baseline, and stem-leaves made a greater contribution (average of 47.30%) to reducing kinetic energy than the other features; (2) the total contribution rate of grassland was 99.38%, and of this total, 1.19, 1.44, 2.49, 49.79 and 44.47% reductions were attributed to the stem-leaves, litter, BSCs, root systems and non-disturbance, respectively. Root system and non-disturbance dominated the detachment rate reduction; (3) with increasing flow rate or slope gradient, the total contribution rate remained between 98% and 100%; and (4) for each treatment, the relationship between detachment rate and hydraulic parameters remained constant, and the stream power was the best predictor to detachment rate. The study results are helpful in evaluating the effects of near-surface features on erosion control and providing reference for government decision-makers to choose appropriate soil conservation and management practices.

Oxygen uptake (VO2) is an important parameter in sports medicine, health assessment and clinical treatment. At present, more and more wearable devices are used in daily life, clinical treatment and health care. The parameters obtained by wearables have great research potential and application prospect. In this paper, an instantaneous VO2 estimation model based on XGBoost was proposed and verified by using data obtained from a medical-grade wearable device (Beijing SensEcho) at different posture and activity levels. Furthermore, physiological characteristics extracted from single-lead electrocardiogram, thoracic and abdominal respiration signal and tri-axial acceleration signal were studied to optimize the model. There were 29 healthy volunteers recruited for the study to collect data while stationary (lying, sitting, standing), walking, Bruce treadmill test and recuperating with SensEcho and the gas analyzer (Metalyzer 3B). The results show that the VO2 values estimated by the proposed model are in good agreement with the true values measured by the gas analyzer (R2 = 0.94 ± 0.03, n = 72,235), and the mean absolute error (MAE) is 1.83 ± 0.59 ml/kg/min. Compared with the estimation method using a separate heart rate as input, our method reduced MAE by 54.70%. At the same time, other factors affecting the performance of the model were studied, including the influence of different input signals, gender and movement intensity, which provided more enlightenment for the estimation of VO2. The results show that the proposed model based on cardio-pulmonary physiological signals as inputs can effectively improve the accuracy of instantaneous VO2 estimation in various scenarios of activities and was robust between different motion modes and state. The VO2 estimation method proposed in this paper has the potential to be used in daily life covering the scenario of stationary, walking and maximal exercise.

Background: The association between inflammatory cysteinyl aspartate protease-5 (CASP5) and the susceptibility to rheumatoid arthritis (RA) remains unclear. This study examined whether the CASP5 rs7939842 polymorphism affects RA risk in Chinese Han individuals. Methods: This study recruited 805 RA patients and 1095 healthy controls to investigate the association between the CASP5 rs7939842 polymorphism and RA risk. Genotype was examined using the 48-Plex SNPscan™ Kit. Plasma CASP5 levels were determined using enzyme-linked immunosorbent assays, and CASP5 gene expression was detected by quantitative polymerase chain reaction in 40 RA patients and 40 healthy controls. Result: The CASP5 rs7939842 polymorphism G allele is a putative risk factor for RA. After stratified analyses, this polymorphism increased the risk of RA among CRP-, ACPA-, RF-, and ESR-positive individuals, as well as individuals with DAS28 ≥ 3.20 and functional class III + IV. Furthermore, the plasma CASP5 levels and CASP5 mRNA expression were higher in RA patients than in healthy controls. Conclusion: The CASP5 rs7939842 polymorphism appears to be associated with an elevated risk of RA in Chinese Han individuals. Blood CASP5 protein and mRNA levels were significantly higher in RA patients than in healthy controls.

Vulnerable atherosclerotic plaques of the artery wall that pose a significant risk of cardio-cerebral vascular accidents remain the global leading cause of morbidity and mortality. Thus, early delineation of vulnerable atherosclerotic plaques is of clinical importance for prevention and treatment. The currently available imaging technologies mainly focus on the structural assessment of the vascular wall. Unfortunately, several disadvantages in these strategies limit the improvement in imaging effect. Nanoparticle technology is a novel diagnostic strategy for targeting and imaging pathological biomarkers. New functionalized nanoparticles that detect hallmarks of vulnerable plaques are promising for advance further control of this critical illness. The review aims to address the current opportunities and challenges for the use of nanoparticle technology in imagining vulnerable plaques.

In this study, CeO2@Zn0.5Cd0.5S heterostructure (Ce@ZCS) is synthesized via a simple two-step hydrothermal method. The effect of CeO2 loading on the visible-light photoactivity of Zn0.5Cd0.5S is mainly investigated. It is found that Ce@ZCS shows a 1.9 times activity as high as ZCS for the MB degradation. The improved activity mainly results from the significant enhanced charge separation by CeO2, in which the electron transfer is obviously promoted by the facile Ce(IV)/Ce(III) cycle. The excited electrons of ZCS is easy to transfer to CeO2, thus obviously increasing the charge separation of ZCS. The accepted electrons by CeO2 may easily be captured by the adsorbed O2 to form O2·−, and then O2·− could combine with H+/H2O to form HO2·, and ·OH. Finally, O2·−, h+ and ·OH are confirmed as the major oxidative species in photocatalytic reaction for Ce@ZCS, and a possible photocatalytic mechanism is proposed. The cheap, efficient Ce@ZCS photocatalyst could be applied for practical waste water treatment. Keywords: Ce(IV)/Ce(III) cycle, CeO2@Zn0.5Cd0.5S, Electron transfer, Photocatalysis

BackgroundWith the development and promotion of wearable devices and their mobile health (mHealth) apps, physiological signals have become a research hotspot. However, noise is complex in signals obtained from daily lives, making it difficult to analyze the signals automatically and resulting in a high false alarm rate. At present, screening out the high-quality segments of the signals from huge-volume data with few labels remains a problem. Signal quality assessment (SQA) is essential and is able to advance the valuable information mining of signals. ObjectiveThe aims of this study were to design an SQA algorithm based on the unsupervised isolation forest model to classify the signal quality into 3 grades: good, acceptable, and unacceptable; validate the algorithm on labeled data sets; and apply the algorithm on real-world data to evaluate its efficacy. MethodsData used in this study were collected by a wearable device (SensEcho) from healthy individuals and patients. The observation windows for electrocardiogram (ECG) and respiratory signals were 10 and 30 seconds, respectively. In the experimental procedure, the unlabeled training set was used to train the models. The validation and test sets were labeled according to preset criteria and used to evaluate the classification performance quantitatively. The validation set consisted of 3460 and 2086 windows of ECG and respiratory signals, respectively, whereas the test set was made up of 4686 and 3341 windows of signals, respectively. The algorithm was also compared with self-organizing maps (SOMs) and 4 classic supervised models (logistic regression, random forest, support vector machine, and extreme gradient boosting). One case validation was illustrated to show the application effect. The algorithm was then applied to 1144 cases of ECG signals collected from patients and the detected arrhythmia false alarms were calculated. ResultsThe quantitative results showed that the ECG SQA model achieved 94.97% and 95.58% accuracy on the validation and test sets, respectively, whereas the respiratory SQA model achieved 81.06% and 86.20% accuracy on the validation and test sets, respectively. The algorithm was superior to SOM and achieved moderate performance when compared with the supervised models. The example case showed that the algorithm was able to correctly classify the signal quality even when there were complex pathological changes in the signals. The algorithm application results indicated that some specific types of arrhythmia false alarms such as tachycardia, atrial premature beat, and ventricular premature beat could be significantly reduced with the help of the algorithm. ConclusionsThis study verified the feasibility of applying the anomaly detection unsupervised model to SQA. The application scenarios include reducing the false alarm rate of the device and selecting signal segments that can be used for further research.

Functionally graded material (FGM) arches may be subjected to a locally radial load and have different material distributions leading to different nonlinear in-plane buckling behavior. Little studies is presented about effects of the type of material distributions on the nonlinear in-plane buckling of FGM arches under a locally radial load in the literature insofar. This paper focuses on investigating the nonlinear in-plane buckling behavior of fixed FGM arches under a locally uniformly distributed radial load and incorporating effects of the type of material distributions. New theoretical solutions for the limit point buckling load and bifurcation buckling loads and nonlinear equilibrium path of the fixed FGM arches under a locally uniformly distributed radial load that are subjected to three different types of material distributions are derived. The comparisons between theoretical and ANSYS results indicate that the theoretical solutions are accurate. In addition, the critical modified geometric slendernesses of FGM arches related to the switches of buckling modes are also derived. It is found that the type of material distributions of the fixed FGM arches affects the limit point buckling loads and bifurcation buckling loads as well as the nonlinear equilibrium path significantly. It is also found that the limit point buckling load and bifurcation buckling load increase with an increase of the modified geometric slenderness, the localized parameter and the proportional coefficient of homogeneous ceramic layer as well as a decrease of the power-law index p of material distributions of the FGM arches.

Background: Rheumatoid arthritis (RA) is related to several pivotal susceptibility genes, including cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) and costimulatory molecule (CD80/CD86) genes. Although the connection between polymorphisms of CTLA-4 and CD86 genes in different populations of RA have been studied extensively, the results are controversial.Objective: To clarify the correlation in the Chinese Han population between CTLA-4, CD80/86, and CD28 gene polymorphisms, and RA susceptibility.Methods: A case-control study (574 RA patients and 804 controls) was conducted to determine the correlation between CTLA-4 rs231775 and rs16840252 gene polymorphisms, CD86 rs17281995 gene polymorphisms, and the risk of RA for the Chinese Han population. Furthermore, an additional meta-analysis, including three single nucleotide polymorphisms (SNPs) (CTLA-4 rs231775, CTLA-4 rs3087243, and CTLA-4 rs5742909) from 32 citations, including 43 studies, 24,703 cases and 23,825 controls was performed to elucidate the relationship between known SNPs in the CTLA-4 genes and RA for more robust conclusions.Results: The results showed that CTLA-4 rs231775 gene polymorphism decreased the RA risk (GA vs. AA, OR = 0.77, P = 0.025), whereas CTLA-4 rs16840252 and CD86 rs17281995 gene polymorphisms were not related to RA susceptibility. Stratification analyses by RF, ACPA, CRP, ESR, DAS28, and functional class identified significant associations for CTLA-4 rs231775 and rs16840252 gene polymorphisms in the RF-positive and RF-negative groups. A meta-analysis of the literature on CTLA-4 gene polymorphisms and RA risk revealed that the risk of RA was decreased by CTLA-4 rs231775 gene polymorphisms.Conclusions: The CTLA-4 rs231775 gene polymorphism decreased the risk of RA, whereas CTLA-4 rs16840252 and CD86 rs17281995 gene polymorphisms were not related to RA risk. A meta-analysis indicated that CTLA-4 rs231775 and rs3087243 gene polymorphisms decreased the risk of RA. To support these analytical results, additional clinical cases should be investigated in further studies.

This paper explores the invulnerability of urban agglomeration transportation network under the incomplete information attack strategy. This approach employed the site mapping method to construct the urban agglomeration composite transportation network model, and the network is weighted based on the actual passenger flow. Then the nodes are defined according to the overload conditions. In addition, based on the capacity-load model, the cascading failure model of the urban agglomeration passenger transport network is constructed, and the incomplete information attack strategy and network invulnerability measure index are determined. Finally, the case of Hu-Bao-E-Yu urban agglomeration is simulated to quantify the effects of attack strategies with varied information level, node load factors, and capacity weight and distance weight of the residual connected edge. The results reveal that the network crash speed is positively related to the information span of the attacker unless the information span exceeds 0.9 or accuracy exceeds 0.6. When the information span is low, the information accuracy δ has a critical impact on the network crash speed. Moreover, in the presence of attack, high or low values of node load factor are conducive to the improvement of network invulnerability. As a scale-free network, urban agglomeration transportation network shows strong robustness to random attacks and exhibits vulnerability to deliberate attacks. The capacity weight value α and distance weight value β of residual connected edge have different effects on the network invulnerability under different information span strategies.

CuCrZr alloy has the advantages of good electrical conductivity, thermal conductivity, high hardness, crack resistance and high softening temperature. It is extensively used in important fields such as rail transit, aerospace, thermonuclear fusion and electronic information. Due to its high melting point, reflectivity, thermal conductivity, etc., it is more difficult to manufacture by selective laser melting (SLM). In this work, the effect of SLM process parameters on the characteristics of CuCrZr samples, such as relative density, hardness and tensile properties, has been investigated using orthogonal experiment method. The experimental results show that laser power is the main factor affecting the properties of the alloy. The tensile strength of the alloy increases with an increase in laser power; it first increases and then decreases with an increase in scanning speed. The optimal combination of process parameters in this paper is as follows: laser power is 240 W, scanning speed is 750 mm/s and scanning spacing is 0.07 mm. The relative density, ultimate tensile strength and hardness of the alloy fabricated by best SLM process parameters was 98.79%, 347 MPa, 133.9 HV, respectively.

In this paper, an analytical model of a cable-stayed shallow arch is developed in order to investigate the 1 : 1 internal resonance between modes of a cable and a shallow arch. Integrodifferential equations with quadratic and cubic nonlinearities are used to model the in-plane motion of a simple cable-stayed shallow arch. Nonlinear dynamic responses of a cable-stayed shallow arch subjected to external excitations with simultaneous 1 : 1 internal resonances are investigated. Firstly, the Galerkin method is used to discretize the governing nonlinear integral-partial-differential equations. Secondly, the multiple scales method (MSM) is used to derive the modulation equations of the system under external excitation of the shallow arch. Thirdly, the equilibrium, the periodic, and the chaotic solutions of the modulation equations are also analyzed in detail. The frequency- and force-response curves are obtained by using the Newton–Raphson method in conjunction with the pseudoarclength path-following algorithm. The cascades of period-doubling bifurcations leading to chaos are obtained by applying numerical simulations. Finally, the effects of key parameters on the responses are examined, such as initial tension, inclined angle of the cable, and rise and inclined angle of shallow arch. The comprehensive numerical results and research findings will provide essential information for the safety evaluation of cable-supported structures that have widely been used in civil engineering.

M2-type tumor-associated macrophages (TAMs) infiltration contributes to cancer malignant progression. However, the mechanisms for controlling recruitment and M2 polarization of macrophages by cancer cells are largely unclear. NADPH oxidase 4 (NOX4) is abundantly expressed in non-small cell lung cancer (NSCLC) and mediates cancer progression. NOXs are in close relation with cancer-related inflammation, nevertheless, whether tumoral NOXs influence microenvironmental macrophages remains undentified. This study found that there was a close association between NOX4 expression and macrophage chemotaxis in patients with NSCLC analyzed using TCGA RNA-sequencing data. NOX4 in NSCLC cells (A549 and Calu-1 cell lines) efficiently enhanced murine peritoneal macrophage migration and induces M2 polarization. Immunohistochemical analysis of clinical specimens confirmed the positive correlation of NOX4 and CD68 or CD206. The mechanical study revealed that tumoral NOX4-induced reactive oxygen species (ROS) stimulated various cytokine production, including CCL7, IL8, CSF-1 and VEGF-C, via PI3K/Akt signaling-dependent manner. Blockade of the function of these cytokines reversed NOX4 effect on macrophages. Specifically, the results showed that tumoral NOX4-educated M2 macrophages exhibited elevated JNK activity, expressed and released HB-EGF, thus facilitating NSCLC proliferation in vitro. Pretreatment of macrophages with JNK inhibitor blocked tumoral NOX4-induced HB-EGF production in M2 macrophages. Finally, in a xenograft mouse model, overexpression of NOX4 in A549 cells enhanced the tumor growth. Elimination of ROS by NAC or inhibition of NOX4 activity by GKT137831 suppressed tumor growth accompanied by reduction in macrophage infiltration and the percentage of M2 macrophages. In conclusion, our study indicates that tumoral NOX4 recruits M2 TAMs via ROS/PI3K signaling-dependent various cytokine production, thus contributing NSCLC cell growth. Keywords: NOX4, Macrophages, NSCLC, M2 polarization, Chemotaxis

In this paper, we present an analytical prediction for nonlinear buckling of elastically supported functionally graded graphene platelet reinforced composite (FG-GPLRC) arches with asymmetrically distributed graphene platelets (GPLs). The effective material properties of the FG-GPLRC arch are formulated by the modified Halpin–Tsai micromechanical model. By using the principle of virtual work, analytical solutions are derived for the limit point buckling and bifurcation buckling of the FG-GPLRC arch subjected to a central point load (CPL). Subsequently, the buckling mode switching phenomenon of the FG-GPLRC arch is presented and discussed. We found that the buckling modes of the FG-GPLRC arch are governed by the GPL distribution pattern, rotational restraint stiffness, and arch geometry. In addition, the number of limit points in the nonlinear equilibrium path of the FG-GPLRC arch under a CPL can be determined according to the bounds of successive inflexion points. The effects of GPL distribution patterns, weight fractions, and geometric configurations on the nonlinear buckling behavior of elastically supported FG-GPLRC arches are also comprehensively discussed.

This paper presents an analytical study on the multiple equilibria and buckling of pinned-fixed functionally graded graphene nanoplatelet-reinforced composite (FG-GPLRC) arches under central point load. It is assumed that graphene nanoplatelets (GPLs) in each GPLRC layer are uniformly distributed and randomly oriented with its concentration varying layer-wise along the thickness direction. The Halpin–Tsai micromechanics-based model is used to estimate the effective elastic modulus of GPLRC. The non-linear equilibrium path and buckling load of the pinned-fixed FG-GPLRC arch are subsequently derived by employing the principle of virtual work. The effects of GPLs distribution, weight fraction, size and geometry on the buckling load are examined comprehensively. It is found that the buckling performances of FG-GPLRC arches can be significantly improved by using GPLs as reinforcing nanofillers. It is also found that the non-linear equilibrium path of the pinned-fixed FG-GPLRC arch have multiple limit points and non-linear equilibrium branches when the arch is with a special geometric parameter.

Coastal salt marshes are valuable and critical components of tidal landscapes, currently threatened by increasing rates of sea level rise, wave-induced lateral erosion, decreasing sediment supply, and human pressure. Halophytic vegetation plays an important role in salt-marsh erosional and depositional patterns and marsh survival. Mapping salt-marsh halophytic vegetation species and their fractional abundance within plant associations can provide important information on marsh vulnerability and coastal management. Remote sensing has often provided valuable methods for salt-marsh vegetation mapping; however, it has seldom been used to assess the fractional abundance of halophytes. In this study, we developed and tested a novel approach to estimate fractional abundance of halophytic species and bare soil that is based on Random Forest (RF) soft classification. This approach can fully use the information contained in the frequency of decision tree “votes” to estimate fractional abundance of each species. Such a method was applied to WorldView-2 (WV-2) data acquired for the Venice lagoon (Italy), where marshes are characterized by a high diversity of vegetation species. The proposed method was successfully tested against field observations derived from ancillary field surveys. Our results show that the new approach allows one to obtain high accuracy (6.7% < root-mean-square error (RMSE) < 18.7% and 0.65 < R2 < 0.96) in estimating the sub-pixel fractional abundance of marsh-vegetation species. Comparing results obtained with the new RF soft-classification approach with those obtained using the traditional RF regression method for fractional abundance estimation, we find a superior performance of the novel RF soft-classification approach with respect to the existing RF regression methods. The distribution of the dominant species obtained from the RF soft classification was compared to the one obtained from an RF hard classification, showing that numerous mixed areas are wrongly labeled as populated by specific species by the hard classifier. As for the effectiveness of using WV-2 for salt-marsh vegetation mapping, feature importance analyses suggest that Yellow (584–632 nm), NIR 1 (near-infrared 1, 765–901 nm) and NIR 2 (near-infrared 2, 856–1043 nm) bands are critical in RF soft classification. Our results bear important consequences for mapping and monitoring vegetation-species fractional abundance within plant associations and their dynamics, which are key aspects in biogeomorphic analyses of salt-marsh landscapes.

Relative orientation estimation between the hand and its fingers is important in many applications, such as virtual reality (VR), augmented reality (AR) and rehabilitation. It is still quite a big challenge to do the estimation by only exploiting inertial measurement units (IMUs) because of the integration drift that occurs in most approaches. When the hand is functionally used, there are many instances in which hand and finger tips move together, experiencing almost the same angular velocities, and in some of these cases, almost the same accelerations are measured in different 3D coordinate systems. Therefore, we hypothesize that relative orientations between the hand and the finger tips can be adequately estimated using 3D IMUs during such designated events (DEs) and in between these events. We fused this extra information from the DEs and IMU data with an extended Kalman filter (EKF). Our results show that errors in relative orientation can be smaller than five degrees if DEs are constantly present and the linear and angular movements of the whole hand are adequately rich. When the DEs are partially available in a functional water-drinking task, the orientation error is smaller than 10 degrees.

Long non-coding RNAs recently were identified as key mediators of cancer metastasis. This study provided evidence that long non-coding RNA MALAT1 was up-regulated in breast cancer tissues and cell lines. MALAT1 promoted cancer cell invasion through inducing epithelial–mesenchymal transition. Interestingly, we revealed there was a reciprocal repression between MALAT1 and miR-204. ZEB2 was identified as a downstream target of miR-204 and MALAT1 exerted its function mainly through the miR-204/ZEB2 axis. Our findings suggested that MALAT1 may serve as a new diagnostic biomarker and therapy target for breast cancer.

This paper presents a corrosion fatigue cyclic failure test for X80 steel, which has arc sprayed with an Al−Zn coating in natural seawater under different stress levels. We found that the Al−Zn coating can significantly improve the corrosion fatigue resistance and slow the crack initiation of X80 steel. The effect of the Al−Zn coating on the corrosion fatigue crack initiation is mainly attributed to its physical isolation, cathodic protection and residual prestress while the effect on crack propagation is due to its inhibition of the formation and evolution of secondary cracks. Moreover, according to the test results, a new life prediction model for corrosion fatigue based on the damage evolution law is proposed and the effect of corrosion−fatigue coupling damage in the proposed model is also considered.

This paper investigates the free vibration and compressive buckling characteristics of functionally graded graphene nanoplatelets reinforced composite (FG-GPLRC) beams containing open edge cracks by using the finite element method. The beam is a multilayer structure where the weight fraction of graphene nanoplatelets (GPLs) remains constant in each layer but varies along the thickness direction. The effective Young’s modulus of each GPLRC layer is determined by the modified Halpin-Tsai micromechanics model while its Poisson’s ratio and mass density are predicted according to the rule of mixture. The effects of GPLs distribution pattern, weight fraction, geometry, crack depth ratio (CDR), slenderness ratio as well as boundary conditions on the fundamental frequency and critical buckling load of the FG-GPLRC beam are studied in detail. It was found that distributing more GPLs on the top and bottom surfaces of the cracked FG-GPLRC beam provides the best reinforcing effect for improved vibrational and buckling performance. The fundamental frequency and critical buckling load are also considerably affected by the geometry and dimension of GPL nanofillers.

The buckling behavior of functionally graded graphene platelet-reinforced composite (FG-GPLRC) shallow arches with elastic rotational constraints under uniform radial load is investigated in this paper. The nonlinear equilibrium equation of the FG-GPLRC shallow arch with elastic rotational constraints under uniform radial load is established using the Halpin-Tsai micromechanics model and the principle of virtual work, from which the critical buckling load of FG-GPLRC shallow arches with elastic rotational constraints can be obtained. This paper gives special attention to the effect of the GPL distribution pattern, weight fraction, geometric parameters, and the constraint stiffness on the buckling load. The numerical results show that all of the FG-GPLRC shallow arches with elastic rotational constraints have a higher buckling load-carrying capacity compared to the pure epoxy arch, and arches of the distribution pattern X have the highest buckling load among four distribution patterns. When the GPL weight fraction is constant, the thinner and larger GPL can provide the better reinforcing effect to the FG-GPLRC shallow arch. However, when the value of the aspect ratio is greater than 4, the flakiness ratio is greater than 103, and the effect of GPL’s dimensions on the buckling load of the FG-GPLRC shallow arch is less significant. In addition, the buckling model of FG-GPLRC shallow arch with elastic rotational constraints is changed as the GPL distribution patterns or the constraint stiffness changes. It is expected that the method and the results that are presented in this paper will be useful as a reference for the stability design of this type of arch in the future.