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Abstract Corrosion is one of the most common forms of damage to pressure pipes. CIPP liner can improve the mechanical properties of the pipe with corrosion. It is very important to study the mechanical response of corrosion pipes rehabilitated by CIPP liner. In this study, a three-dimensional finite element model of a pressure pipe rehabilitated with CIPP liner under the condition of circular corrosion is established, and the model is evaluated by using the experimental and analytical results. Afterward, the influence of each parameter on the stress and displacement of the liner is analyzed. Finally, the liner stress calculation equation is obtained based on 870 sets of data. The results show that the finite element results are in good agreement with the experimental and analytical results. The maximum stress of the liner first occurs at the center of the corroded circle, and as the corrosion diameter increases, the maximum stress gradually shifts to the edge. The maximum stress of the liner increases first and then tends to be stable with the increase of the corrosion diameter, and the friction coefficient has little effect on the liner stress.

Mental disorders seriously affect people’s health and social stability. This Mendelian randomization (MR) study was designed to investigate the causal relationship between circulating vitamin C (VC) or 25-hydroxyvitamin D (25(OH)D) levels and mental disorders. The data used for the MR analysis were derived from the summary genome-wide association studies (GWAS) database for VC and 25(OH)D and from the FinnGen consortium for fourteen mental disorders. Based on the inverse variance weighted (IVW) method, we found a potential causal association between circulating VC and anxiety disorders (IVW:OR = 1.139, 95% CI: 1.023-1.269, P = 0.018). However, no causal association was found between VC or 25(OH)D and other mental disorders (P > 0.05). In the reverse MR analysis, individuals with Alzheimer’s disease was causally associated with higher concentrations of circulating VC (P = 0.012), while individuals with anxiety disorders had a negative association between the concentrations of 25(OH)D (P = 0.012). However, the current evidence does not support a causal relationship between VC or 25(OH)D and other mental disorders. In addition, there was no causal association between circulating VC and 25(OH)D (P > 0.05). Future studies are needed to confirm these findings and to elucidate the mechanisms of potential causality.

Nursing beds can be widely used in medical institutions and households to provide medical care for patients or disabled individuals. With the increasing demand for nursing, nursing beds are developing towards intelligence and comfort. In this study, the backrest lifting mechanism of nursing beds is selected as the research object. The standards for backrest angle adjustment and the basis for comfort judgment are reviewed, and the research on various adjustment configurations are sorted in order to provide assistance to relevant research institutions in understanding current technologies and assist users in making choices.

Polyurethane grouting trenchless technology has been widely applied to the rehabilitation of concealed defects in engineering structures. The interfacial properties between polyurethane and engineering structures are key factors determining the stability of the composite structure. In practical applications, the interface shapes of different engineering structures vary significantly, and the influence of the interface shape on interfacial properties should not be overlooked. This study focuses on engineering structures with curved interfaces, such as pile foundations, pipelines, and tunnels. Direct shear tests were conducted on polyurethane and concrete composite specimens with curved interfaces. A comparative analysis of the shear behavior between curved and planar composite specimens was performed, and the influence of arc diameter and polyurethane density on the shear behavior of curved and planar composite specimens was investigated. Additionally, SEM (Scanning Electron Microscopy) was used to conduct a microscopic examination of the interfaces with different polyurethane densities after failure, and the microscopic shear mechanisms between polyurethane and concrete materials were explored. The results revealed that the shear behavior of curved specimens was significantly higher than that of planar specimens. The shear strengths of curved specimens with diameters of 400 mm, 500 mm, and 700 mm were approximately 1.50, 1.39, and 1.10 times those of planar specimens, respectively. With increasing polyurethane density, the variation trend of shear strength in curved specimens was similar to that of planar specimens. However, significant differences were observed in the shear modulus, peak displacement, and shear residual strength between curved and planar specimens as the polyurethane density varied. Different diameter curved interface specimens exhibited a similar trend of shear strength variation with polyurethane density, gradually decreasing as the curvature diameter increased, and ultimately approaching that of planar specimens.

BackgroundDepression can result in changes in eating behavior and decrease the quality of eating. It has been shown that maternal depression during pregnancy can result in malnutrition, which can have adverse effects on the pregnancy and the offspring. There is currently no clear association between depression and diet.MethodsFive hundred and forty-nine pregnant women recruited from Danyang Maternal and Child Health Hospital in Jiangsu Province participated in this study and were administered the Intuitive Eating Scale-2 (IES-2), Edinburgh Post-natal Depression Scale (EPDS), Pregnancy Stress Scale (PPS), Self-rating Anxiety Scale (SAS), and Dietary Guidelines Adherence Index for Pregnant Women during Pregnancy (CDGCI-PW). The nutritional software collected dietary records for three consecutive days in mid-pregnancy to calculate dietary intake and nutrients that support energy production. The mediation analyses were conducted using SPSS 24.0 macro PROCESS.ResultsThe relationship between depressive symptoms during pregnancy and diet quality was moderated primarily by two aspects of eating behavior, “Reliance on Hunger and Satiety Cues” (RHS) and “Body-Food Choice Congruence” (BFC). Depressive symptoms (EPDS scores) showed a negative correlation with RHS, BFC, and RHS, and BFC showed a positive correlation with diet quality, yielding a significant specific indirect effect. The multiple mediation model explained 14.7% of the variance in the diet quality.ConclusionThis study highlights the important role of eating behaviors during pregnancy in the relationship between depressive symptoms (EPDS scores) and diet quality, and provides preliminary evidence for feasible ways pregnant women with depressive symptoms can improve diet quality, promote maternal and child health, and reduce depression.

Abstract Objective We explored the dietary effects of replacing normal dietary staple foods with supplementary nutritional protein powder, dietary fiber, and fish oil on several metabolic parameters. We examined weight loss, glucose and lipid metabolism, and intestinal flora in obese individuals when compared with individuals on a reduced staple food low carbohydrate diet. Methods From inclusion and exclusion criteria, 99 participants (28 kg/m2 ≤ body mass index (BMI) ≤ 35 kg/m2) were recruited and randomly assigned to control and intervention 1 and 2 groups. Physical examinations and biochemical indices were performed/gathered before the intervention and at 4 and 13 weeks post intervention. After 13 weeks, feces was collected and 16s rDNA sequenced. Results After 13 weeks, when compared with controls, body weight, BMI, waist circumference, hip circumference, systolic blood pressure, and diastolic blood pressure values in intervention group 1 were significantly reduced. In intervention group 2, body weight, BMI, waist circumference, and hip circumference were significantly reduced. Triglyceride (TG) levels in both intervention groups were significantly reduced. Fasting blood glucose, glycosylated hemoglobin, glycosylated albumin, total cholesterol, and apolipoprotein B levels in intervention group 1 were decreased, while high density lipoprotein cholesterol (HDL-c) decreased slightly. Glycosylated albumin, TG, and total cholesterol levels in intervention group 2 decreased, while HDL-c decreased slightly, High sensitive C-reactive protein, MPO, Ox-LDL, LEP, TGF-β1, IL-6, GPLD1, pro NT, GPC-4, and LPS levels in both intervention groups were lower when compared with controls. Adiponectin (ADPN) levels in intervention groups were higher when compared with controls. Tumor necrosis factor-α (TNF-α) levels in intervention group 1 were lower when compared with controls. There is no obvious difference in α diversity and β diversity between intestinal flora of 3 groups. Among the first 10 species of Phylum, only the control group and the intervention group 2 had significantly higher Patescibacteria than the intervention group 1. Among the first 10 species of Genus, only the number of Agathobacter in intervention group 2 was significantly higher than that in control group and intervention group 1. Conclusions We showed that an LCD, where nutritional protein powder replaced some staple foods and dietary fiber and fish oil were simultaneously supplemented, significantly reduced weight and improved carbohydrate and lipid metabolism in obese individuals when compared with an LCD which reduced staple food intake.

Deep learning algorithms have achieved encouraging results for pipeline defect segmentation. However, existing defect segmentation methods may encounter challenges in accurately segmenting the complex features of pipeline defects and suffer from low processing speeds. Therefore, in this study, we propose Pipe-Sparse-Net, a pipeline defect segmentation system that combines StyleGAN3 to segment the complex forms of underground drainage pipe defects. First, we introduce a data augmentation algorithm based on StyleGAN3 to enlarge the dataset. Next, we propose Pipe-Sparse-Net, a pipeline segmentation model based on SparseInst, to accurately predict the defect regions in drainage pipes. Experimental results demonstrate that the segmentation accuracy of this model can reach 91.4% with a processing speed of 56.7 frames per second (FPS). To validate the superiority of this method, comparative experiments were conducted against Yolact, Condinst, and Mask R-CNN, and the model achieved a speed improvement of 45% while increasing the accuracy by more than 4%.

ObjectiveBrain-derived neurotrophic factor (BDNF), a member of the neurotrophic family that plays a vital role in regulating neuronal activity and synaptic plasticity in the brain, affects attention. However, studies investigating the association between BDNF and attention in long-term high-altitude (HA) migrants are limited in the literature. As HA affects both BDNF and attention, the relationship between these factors becomes more complex. Therefore, this study aimed to evaluate the relationship between peripheral blood concentrations of BDNF and the three attentional networks in both behavioral and electrical aspects of the brain in long-term HA migrants.Materials and methodsNinety-eight Han adults (mean age: 34.74 ± 3.48 years, 51 females and 47 males, all have lived at Lhasa for 11.30 ± 3.82 years) were recruited in this study. For all participants, the serum BDNF levels were assessed using enzyme-linked immunosorbent assay; event-related potentials (N1, P1, and P3) were recorded during the Attentional Networks Test, which was used as the measure of three attentional networks.ResultsExecutive control scores were negatively correlated with P3 amplitude (r = −0.20, p = 0.044), and serum BDNF levels were positively correlated with executive control scores (r = 0.24, p = 0.019) and negatively correlated with P3 amplitude (r = −0.22, p = 0.027). Through grouping of BDNF levels and three attentional networks, executive control was found to be significantly higher in the high BDNF group than in the low BDNF group (p = 0.010). Different BDNF levels were associated with both orienting scores (χ2 = 6.99, p = 0.030) and executive control scores (χ2 = 9.03, p = 0.011). The higher the BDNF level, the worse was the executive function and the lower was the average P3 amplitude and vice versa. Females were found to have higher alerting scores than males (p = 0.023).ConclusionThis study presented the relationship between BDNF and attention under HA. The higher the BDNF level, the worse was the executive control, suggesting that after long-term exposure to HA, hypoxia injury of the brain may occur in individuals with relatively higher BDNF levels, and this higher BDNF level may be the result of self-rehabilitation tackling the adverse effects brought by the HA environment.

To solve the problems of low accuracy and false counts of existing models in road damage object detection and tracking, in this paper, we propose Road-TransTrack, a tracking model based on transformer optimization. First, using the classification network based on YOLOv5, the collected road damage images are classified into two categories, potholes and cracks, and made into a road damage dataset. Then, the proposed tracking model is improved with a transformer and a self-attention mechanism. Finally, the trained model is used to detect actual road videos to verify its effectiveness. The proposed tracking network shows a good detection performance with an accuracy of 91.60% and 98.59% for road cracks and potholes, respectively, and an F1 score of 0.9417 and 0.9847. The experimental results show that Road-TransTrack outperforms current conventional convolutional neural networks in terms of the detection accuracy and counting accuracy in road damage object detection and tracking tasks.

Guar gum is recognized as a soluble dietary fiber but its effects on blood lipid levels remain to be established. The purpose of the study was to focus on assessing randomized controlled trials (RCTs) and investigate the effect of guar gum on lipid levels. Seventeen studies were systematically selected and included in the meta-analysis. Decreases in total cholesterol (TC) (standard mean difference (SMD) [95 %CI] = −1.38 [−2.01,−0.74]) and low density lipoprotein cholesterol (LDL-C) (SMD [95 %CI] = −1.67 [−2.52, −0.82]) were significantly more pronounced with guar gum consumption, whereas no difference was observed on high density lipoprotein cholesterol (HDL-C) (SMD [95 %CI] = −0.07 [−0.34, 0.19]) or triglyceride (TG) (SMD [95 %CI] = 0.06 [−0.50, 0.61]), which suggests that guar gum has the potential to promote lipid health and prevent cardiovascular disease (CVD).

Considerable road mileage puts tremendous pressure on pavement crack detection and maintenance. In practice, using a small parameter model for fast and accurate image-based crack segmentation is a challenge. However, current mainstream convolutional neural networks allocate computing resources to the same type of operators, which ignores the impact of different levels of feature extractors on the model performance. In this research, an end-to-end real-time pavement crack segmentation network (RIIAnet) is designed to improve performance by deploying different types of operators in separate layers of the network structure. Based on the extraction characteristics of cracks by convolution, involution, and asymmetric convolution, in the shallow layers the crack segmentation task is matched to extract rich low-level features by the designed asymmetric convolution enhancement module (ACE). Meanwhile, in the deep layers, the designed residual expanded involution module (REI) is used to enhance the high-level semantic features. Furthermore, the existing involution operator that fails to converge during training is improved. The ablation experiment demonstrates that the optimal ratio of the convolution and REI is 1/3 to obtain the optimal resource allocation and ACE improves the performance of the model. Especially compared with seven classical deep learning models of different structures, the results show that the proposed model reaches the highest MIOU, MPA, Recall, and F1 score of 0.7705, 0.9868, 0.8047, and 0.8485, respectively. More importantly, the parameter size of the proposed model is dramatically reduced, which is 0.04 times that of U-Net. In practice, the proposed model can be implemented in images with a high resolution of 2048 × 1024 in real time.

Ground Penetrating Radar (GPR) is a shallow geophysical method for detecting and locating subsurface targets. The GPR image echo characteristics of complex underground structures can be obtained by carrying out GPR forward modeling research. The traditional finite-difference time-domain (FDTD) method has low efficiency and accuracy. The alternating direction implicit FDTD (ADI-FDTD) algorithm surmounts the stability limitations of the traditional FDTD method, making it possible to select a larger time step for higher computational efficiency. For circular underground structures, a pseudowave produced by the ladder approximation method can be corrected using the surface conformal technique. This paper proposes a high-efficiency and high-accuracy GPR forward modeling method that combines the ADI-FDTD algorithm and surface conformal technology. The performance of the conformal ADI-FDTD algorithm is verified by a simple two-layer model. Based on the proposed algorithm, the GPR image features of three complex underground structure models are obtained. Finally, a field experiment is used to support the accuracy and usefulness of the conformal ADI-FDTD algorithm. The numerical simulation results and experimental results show that the conformal ADI-FDTD algorithm reduces the pseudodiffraction wave caused by the ladder approximation method and can significantly improve the computing efficiency for complex underground structure models.

The urban drainage system is an important part of the urban water cycle. However, with the aging of drainage pipelines and other external reasons, damages such as cracks, corrosion, and deformation of underground pipelines can cause serious consequences such as urban waterlogging and road collapse. At present, the detection of underground drainage pipelines mostly focuses on the qualitative identification of pipeline damage, and it is impossible to quantitatively analyze pipeline damage. Therefore, a method to quantify the damage volume of concrete pipes that combines surface segmentation and reconstruction is proposed. An RGB-D sensor is used to collect the damage information of the drainage pipeline, and the collected depth frame is registered to generate the pipeline’s surface point cloud. Voxel sampling and Gaussian filtering are used to improve data processing efficiency and reduce noise, respectively, and the RANSAC algorithm is used to remove the pipeline’s surface information. The ball-pivoting algorithm is used to reconstruct the surface of the segmented damage data and pipe’s surface information, and finally to obtain the damage volume. In order to evaluate, we conducted our research on real-world materials. The measurement results show that the method proposed in this paper measures an average relative error of 7.17% for the external damage volume of concrete pipes and an average relative error of 5.22% for the internal damage measurements of concrete pipes.

With the age of pipeline and increase in the volume of urban sewage, the pipeline has different degrees of defects, which can cause safety problems such as road collapse and urban flooding. The service life of drainage pipes is closely related to daily maintenance and inspection, so it is very important to inspect the defects and monitor the operation of drainage pipes regularly. However, the existing research lacks quantitative detection and intelligent management of pipeline defect information. Therefore, the depth camera is used as the sensor to quantitatively detect the volume and area of the pit on the concrete pipe, and a defect information management platform is constructed in this paper. Firstly, combined BIM model with 3D point cloud, this paper proposes a 3D defect information management platform of drainage pipeline. Then, the depth camera is used to collect the damage data and preprocess the data, and a method for calculating the damage volume and surface area of drainage pipeline based on 3D mesh reconstruction of the defect point cloud is proposed. The verification experiment results show that the error between the quantized volume and the real volume is mostly within 10%, and the maximum error is 17.54%, indicating high accuracy. The drainage pipeline information model is created. Finally, the data is uploaded to the information management platform to realize the visualization and informatization of pipeline defects and the later operation and maintenance requirements of the pipeline.

Background:The existing pipeline siltation analysis lacks the analysis of the influence of pipeline siltation intensity on the water level depth of the manhole.Objective:To address these issues, in this study, the high-resolution numerical simulation model of ‘silted pipeline-manhole' was established.Methods:First, a spatial and temporal hydraulic response model of the ‘silted pipeline-manhole' system is constructed. The vibrational differential equation of the ‘silted pipeline-manhole' system is then adopted to quantify the physical boundary constraints on the fluid–solid coupling relationship. The local and global feature search capabilities were enhanced by an embedded self-attention network, which in turn established an intelligent early warning model for manhole water levels in silted pipelines.Results:The results of the test analysis showed that, owing to the blocking effect of siltation, the water level of the manhole at the first end of the silted pipe was high, leading to a decrease in the water level of the manhole at the tail end. The pipe with a transverse siltation intensity of 10% showed an 8.07% reduction in the maximum overflow flow rate, whereas the pipe with a longitudinal siltation intensity of 5.2% exhibited a 15.09% reduction, suggesting that longitudinal siltation intensity has a more significant impact on pipeline failure.Conclusion:The research results provide technical support for the diagnosis of pipeline siltation and flood risk assessment considering the change of water level in the manhole and the inlet and outlet flow velocity of the pipe section.