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The inverse analysis of the deformation moduli of high arch dams based on displacement monitoring data is essential for structural safety assessment. In traditional inverse analysis methods, the deformation moduli are identified based on the single‐objective optimization and the hydrostatic component derived from the statistical model. This type of method has two main shortcomings: First, it treats the essential multi‐objective optimization problem as a single‐objective problem; second, the extracted hydrostatic component may be biased due to the multicollinearity of variables in the statistical model. This paper presents a methodology for the inverse analysis of the deformation moduli of high arch dams under a multi‐objective optimization strategy. The methodology employs empirical mode decomposition to extract the aging component from displacement monitoring data. Then, thermomechanical analysis is used to reconstruct the remaining hydrostatic and temperature components, thereby avoiding the biases encountered in solving the statistical model. The adaptive polynomial chaos expansion method is embedded in the NSGA‐III algorithm to establish and solve multi‐objective functions in the inverse analysis. Additionally, a composite decision index considering errors and test information is proposed to determine acceptable deformation moduli from the Pareto solution set. A high arch dam is selected to illustrate this methodology with static and dynamic monitoring data. The results show that the identified deformation moduli have errors of 3.8% and 7.2% in displacement and acceleration, respectively. The proposed methodology can yield deformation modulus values that are more consistent with the physical implications than those of the single‐objective optimization method. [ABSTRACT FROM AUTHOR]

The fourth-order governing equation of Euler-Bernoulli beams necessitates the employment of C1 Hermite shape functions in finite element analysis. However, unlike the C0 finite element shape functions that can be easily formulated as Lagrangian polynomials in a unified manner, the Hermite shape functions of Euler-Bernoulli beam elements are usually constructed case by case. In this work, a simple and unified meshfree path is proposed to develop arbitrary order Hermite shape functions of Euler-Bernoulli beam elements. This approach is realized by proving that the Hermite reproducing kernel meshfree shape functions degenerate to the interpolatory Hermite finite element shape functions under a proper choice of support sizes. The proposed approach provides an explicit formalism for Hermite finite element shape functions, which enables an easy construction of arbitrary order Hermite beam elements. Accordingly, in addition to the conventional cubic Hermite beam elements, explicit shape functions, mass and stiffness matrices for quintic and septic Hermite beam elements are presented. Meanwhile, the frequency errors and general higher order mass matrix formulation for these Hermite beam elements are elaborated as well. These theoretical results are consistently demonstrated by numerical examples with respect to both static and free vibration analysis. [ABSTRACT FROM AUTHOR]

Colorectal cancer (CRC) prevention requires early detection and removal of adenomas. We aimed to develop a computational model for real-time detection and classification of colorectal adenoma. Computationally constrained background based on real-time detection, we propose an improved adaptive lightweight ensemble model for real-time detection and classification of adenomas and other polyps. Firstly, we devised an adaptive lightweight network modification and effective training strategy to diminish the computational requirements for real-time detection. Secondly, by integrating the adaptive lightweight YOLOv4 with the single shot multibox detector network, we established the adaptive small object detection ensemble (ASODE) model, which enhances the precision of detecting target polyps without significantly increasing the model's memory footprint. We conducted simulated training using clinical colonoscopy images and videos to validate the method's performance, extracting features from 1148 polyps and employing a confidence threshold of 0.5 to filter out low-confidence sample predictions. Finally, compared to state-of-the-art models, our ASODE model demonstrated superior performance. In the test set, the sensitivity of images and videos reached 87.96% and 92.31%, respectively. Additionally, the ASODE model achieved an accuracy of 92.70% for adenoma detection with a false positive rate of 8.18%. Training results indicate the effectiveness of our method in classifying small polyps. Our model exhibits remarkable performance in real-time detection of colorectal adenomas, serving as a reliable tool for assisting endoscopists. [ABSTRACT FROM AUTHOR]

Background: Cholesterol (CHO) is an essential component of the body. However, high CHO levels in the body can damage bone mass and promote osteoporosis. CHO accumulation can cause osteoblast apoptosis, which has a negative effect on bone formation. The pathogenesis of osteoporosis is a complicate process that includes oxidative stress, endoplasmic reticulum (ER) stress, and inflammation. Geniposide (GEN) is a natural compound with anti-osteoporotic effect. However, the roles of GEN in osteopathogenesis are still unclear. Our previous studies demonstrated that GEN could reduce the accumulation of CHO in osteoblasts and the activation of ER stress in osteoblasts. However, the molecular mechanism of GEN in inhibiting CHO-induced apoptosis in osteoblasts needs to be further investigated. Methods: MC3T3-E1 cells were treated with osteogenic induction medium (OIM). Ethanol-solubilized cholesterol (100 µM) was used as a stimulator, and 10 µM and 25 µM geniposide was added for treatment. The alterations of protein expression were detected by western blot, and the cell apoptosis was analyzed by a flow cytometer. Results: CHO promoted osteoblast apoptosis by activating ER stress in osteoblasts, while GEN alleviated the activation of ER stress and reduced osteoblast apoptosis by activating the GLP-1R/ABCA1 pathway. Inhibition of ABCA1 or GLP-1R could eliminate the protective activity of GEN against CHO-induced ER stress and osteoblast apoptosis. Conclusion: GEN alleviated CHO-induced ER stress and apoptosis in osteoblasts by mediating the GLP-1R/ABCA1 pathway. [ABSTRACT FROM AUTHOR]

This paper presents a two-axis AlScN-based water-immersible MEMS mirror fabricated in an 8-inch MEMS process. Compared with other studies, this device has a larger optical aperture 10 mm in diameter. The resonant frequencies of the device are 1011 Hz in air and 342 Hz in water. The scanning angle reaches ±5° and ±2° at resonant frequencies in air and water, respectively. The cavitation phenomenon is observed when the device is operating in water, which leads the device to electrical failure. To address this issue, a device with reduced resonant frequencies—246 Hz and 152 Hz in air and water—is characterized, through which the bubbles can be effectively prohibited. This MEMS mirror could potentially be used in ultrasound and photoacoustic microscopy applications. [ABSTRACT FROM AUTHOR]

The role of lncRNAs in the pathogenesis of cancer, including colorectal cancer (CRC), has repeatedly been demonstrated. However, very few lncRNAs have been well annotated functionally. Our study identified a novel lncRNA upregulated in CRC, NONHSAT136151, which was correlated with clinical progression. In functional assays, NONHSAT136151 significantly enhanced CRC cell proliferation, migration and invasion. Mechanistically, NONHSAT136151 interacted with RNA‐binding protein (RBP) QKI (Quaking) to interfere with QKI binding to target mRNAs and regulate their expression. As well, FOXP3 may be causally related to the dysregulation of NONHSAT136151 in CRC cells through its transcriptional activity. In conclusion, our findings identified a novel lncRNA regulated by FOXP3 participates in CRC progression through interacting with QKI, indicating a novel lncRNA‐RBP interaction mechanism is involved in CRC pathogenesis. [ABSTRACT FROM AUTHOR]

Background: The relationship between socioeconomic status (SES) inequity and incident age-related macular degeneration (AMD) remains unclear. We aim to investigate whether low SES increases the risk of AMD and to explore the effect of a healthy lifestyle on this association. Methods: This prospective cohort study included 316,663 UK Biobank individuals. SES inequity was identified via latent class analysis using education, household income, and occupational status. Healthy lifestyle score was calculated based on smoking, alcohol drinking, and physical activity (PA). Incident AMD was defined according to diagnosis records. Cox proportional hazards models were used to evaluate the relationship of low SES and AMD. Interrelationships of healthy lifestyle score on SES-AMD association were explored, including modification, mediation, and joint effects. Results: During the average 12.2 years of follow-up, 6,355 AMD cases were diagnosed. Participants with medium SES (hazard ratio: 1.10 [95% confidence interval (CI) 1.01 to 1.21]) and low SES (hazard ratio: 1.22 [95% CI 1.11 to 1.34]) had an increased risk of incident AMD compared to participants with high SES. PA significantly affected this association. Moreover, the association between low SES and AMD was significantly mediated (11.3%, 95% CI: 6.56 to 23.0) by smoking. Similarly, alcohol drinking suppressed (9.59%, 95% CI: 4.00 to 23.2) the association between high SES and AMD. Besides, a significant joint effect of SES and healthy lifestyle score was found. Conclusions: We provide further evidence for the relationship of socioeconomic inequity, healthy lifestyle, and incident AMD. Future public health strategies should aim to reduce socioeconomic inequity to prevent AMD., Competing Interests: Competing interests: The authors declare that they have no competing interests., (Copyright © 2024 Yanlin Qu et al.)

The investigation of damage development is essential for the design and optimization of hybrid structures. This paper provides a reference for the structural design of brittle-ductile hybrid LVI-resistant laminates through analyzing the damage development mechanism of carbon/Kevlar fabric-reinforced composite laminates. The effects of Kevlar fabric hybrid ply and intercalation on the damage development of carbon/Kevlar composite laminates under low-velocity impact (LVI) were investigated using quasi-static indentation (QSI). It was found that an increase in the Kevlar hybrid ratio significantly reduced the peak load and stiffness of these laminates (the maximum decreases in strength and stiffness were 46.03% and 41.43%, respectively), while laminates with identical hybrid ratios but different plying configurations maintained a comparable stiffness under QSI, with differences of less than 5%. Interestingly, Kevlar fibers exhibited irregular fractures as the yarn was splitting, while carbon fibers presented neat breaks, which indicated material-specific failure modes. Notably, the introduction of Kevlar hybridization beyond pure Kevlar configurations (KKKK) resulted in a decrease in the percentage of fiber damage (CCCC, CCCK, CCKK, and KCCK accounted for 80%, 79.8%, 70%, and 60% of fiber damage, respectively), attributed to an increase in resin cracks and lower levels of Kevlar yarn breakage. The internal damage diameter of specimens was accurately predicted from the diameter of visible damage on the QSI surface. Compared with CCCC and CCKK setups, which are affected by resin cracks formed via the carbon surface on the loading side propagating along the yarn direction (including the yarn settling direction), KCCK demonstrated less delamination between the first and second ply.

Background: Low lung function is associated with an increased risk of age-related diseases. However, the relationship between age-related macular degeneration (AMD), the leading cause of blindness, and lung function remains unclear. We aimed to investigate whether low lung function increases the risk of AMD and the potential mechanisms behind this association., Methods: We conducted a prospective cohort analysis of 409 230 UK Biobank participants with completed lung function after excluding individuals with AMD. We used Cox proportional hazards models to estimate the risk of AMD incidence and mediation models to explore potential mechanisms driven by inflammatory markers, erythrocyte-related measures, and metabolites., Results: Overall, 6477 AMD cases were diagnosed across an average of 12.4 years of follow-up. Participants with low lung function had an increased risk of developing AMD compared to those with high lung function (forced vital capacity: adjusted hazard ratio (aHR) = 1.20 (95% confidence interval (CI) = 1.07-1.34); forced expiratory volume in one second: aHR = 1.32 (95% CI = 1.18-1.47); peak expiratory flow: aHR = 1.32 (95% CI = 1.20-1.45)). Inflammatory markers and erythrocyte-related measures mediated this relationship, acting as a pathway through which low lung function influenced AMD. The interactions of body mass index (BMI), sex, and smoking were significant and the effect of lung function on AMD was higher in men, obese, and smoking populations., Conclusions: The increased risk of AMD was associated with low lung function, with inflammatory and erythrocyte-related markers mediating this relationship. This suggests that improvements in lung function could reduce the risk of AMD, thereby promoting health and longevity., Competing Interests: Disclosure of interest: The authors completed the ICMJE Disclosure of Interest Form (available upon request from the corresponding author) and disclose no relevant interests., (Copyright © 2024 by the Journal of Global Health. All rights reserved.)

HBV-miR-3 is encoded by HBV and takes part in pathogenesis of HBV-related liver disease. Whether HBV-miR-3 has a relationship with HBV replication and is predictive of PegIFN-α treatment response is still unknown. HBV-miR-3 quantification is based on qRT-PCR. The relationship of HBV-miR-3 and HBV replication, and predictive value of HBV-miR-3 were evaluated in a cohort of 650 HBeAg positive patients from a multi-center, randomized phase III clinical trial for the study of PegIFN-a2b. HBV-miR-3 is significantly positively related to HBVDNA, HBVpgRNA, HBeAg and HBsAg at baseline and at all the different time points during PegIFN-α treatment. Both univariate regression analyses and multivariate logistic regression analyses showed HBV-miR-3 is a predictor of HBeAg seroconversion in the patients treated with PegIFN-α at weeks of 0, 12, and 24. 70.0% of patients with HBV-miR-3 < 3log at week 12 achieved HBeAg seroconversion, otherwise, with HBV-miR-3 > 6log at week 12 no patient obtained HBeAg seroconversion. Conbination of HBV-miR-3 and HBeAg is more strongly predictive of HBeAg seroconversion (83.64%) at week 12. HBV-miR-3 is new biomarker for HBV replication and positively correlated to HBV replication. HBV-miR-3 is also an early predictor of HBeAg seroconversion in the patients treated with PegIFN-α., (© 2024. The Author(s).)

Prostate cancer (PRAD) is one of the common malignant tumors of the urinary system. In order to predict the treatment results for PRAD patients, this study proposes to develop a risk profile based on endoplasmic reticulum stress (ERS). Based on the Memorial Sloan-Kettering Cancer Center (MSKCC) cohort and the Gene Expression Omnibus database (GSE70769), we verified the predictive signature. Using a random survival forest analysis, prognostically significant ERS-related genes were found. An ERS-related risk score (ERscore) was created using multivariable Cox analysis. In addition, the biological functions, genetic mutations and immune landscape related to ERscore are also studied to reveal the underlying mechanisms related to ERS in PRAD. We further explored the ERscore-related mechanisms by profiling a single-cell RNA sequencing (scRNA-seq) dataset (GSE137829) and explored the oncogenic role of ASNS in PRAD through in vitro experiments. The risk signature composed of eight ERS-related genes constructed in this study is an independent prognostic factor and validated in the MSKCC and GSE70769 data sets. The scRNA-seq data additionally revealed that several carcinogenic pathways were noticeably overactivated in the group with high ERS scores. As one of the prognostic genes, ASNS will significantly inhibit the proliferation, migration and invasion abilities of PRAD cells after its expression is interfered with. In conclusion, this study developed a novel risk-specific ERS-based clinical treatment strategy for patients with PRAD.

Airborne surface and underwater human pose recognition are crucial for various safety and surveillance applications, including the detection of individuals in distress or drowning situations. However, airborne optical cameras struggle to achieve simultaneous imaging of the surface and underwater because of limitations imposed by visible-light wavelengths. To address this problem, this study proposes the use of light detection and ranging (LiDAR) to simultaneously detect humans on the surface and underwater, whereby human poses are recognized using a neural network designed for irregular data. First, a temporal point-cloud dataset was constructed for surface and underwater human pose recognition to enhance the recognition of comparable movements. Subsequently, radius outlier removal (ROR) and statistical outlier removal (SOR) were employed to alleviate the impact of noise and outliers in the constructed dataset. Finally, different combinations of secondary sampling methods and sample sizes were tested to improve recognition accuracy using PointNet++. The experimental results show that the highest recognition accuracy reached 97.5012%, demonstrating the effectiveness of the proposed human pose detection and recognition method., (© 2024. The Author(s).)

Recently studies have shown the potential of weakly supervised multi-object tracking and segmentation, but the drawbacks of coarse pseudo mask label and limited utilization of temporal information remain to be unresolved. To address these issues, we present a framework that directly uses box label to supervise the segmentation network without resorting to pseudo mask label. In addition, we propose to fully exploit the temporal information from two perspectives. Firstly, we integrate optical flow-based pairwise consistency to ensure mask consistency across frames, thereby improving mask quality for segmentation. Secondly, we propose a temporally adjacent pair-based sampling strategy to adapt instance embedding learning for data association in tracking. We combine these techniques into an end-to-end deep model, named BoxMOTS, which requires only box annotation without mask supervision. Extensive experiments demonstrate that our model surpasses current state-of-the-art by a large margin, and produces promising results on KITTI MOTS and BDD100K MOTS. The source code is available at https://github.com/Spritea/BoxMOTS.