Numerical analysis of pipe jacking in deep soft soil based on the construction of urban underground sewage pipeline

Pipe jacking construction in complex soil layers and soil conditions remains to be a tough issue, because various factors are supposed to be considered and the jacking parameters needs optimization. The purpose of this paper is to analyze the impact of pipe jacking on surface settlement, soil deformation and pipe-soil interaction in a numerical model of pipe jacking through deep soft soil, which is a simulated construction of urban underground sewage pipeline. The results show that the pipe jacking construction adopted in the deep soft soil layer has little effect on the surrounding soil layers. And the maximum ground settlement is only about 8 mm. The impact of pipe jacking construction in deep soft soil layer on ground settlement is about 6 times the diameter of the jacking pipe along the pipe axis. Finally, the input force needs to be selected according to the condition of the soil layer to ensure the safety of the pipe jacking construction

Numerical analysis of pipe jacking in deep soft soil based on the construction of urban underground sewage pipeline

Pipe jacking construction in complex soil layers and soil conditions remains to be a tough issue, because various factors are supposed to be considered and the jacking parameters needs optimization. The purpose of this paper is to analyze the impact of pipe jacking on surface settlement, soil deformation and pipe-soil interaction in a numerical model of pipe jacking through deep soft soil, which is a simulated construction of urban underground sewage pipeline. The results show that the pipe jacking construction adopted in the deep soft soil layer has little effect on the surrounding soil layers. And the maximum ground settlement is only about 8 mm. The impact of pipe jacking construction in deep soft soil layer on ground settlement is about 6 times the diameter of the jacking pipe along the pipe axis. Finally, the input force needs to be selected according to the condition of the soil layer to ensure the safety of the pipe jacking construction

Functional Haplotypes of the hTERT Gene, Leukocyte Telomere Length Shortening, and the Risk of Peripheral Arterial Disease

Background: The development of peripheral arterial disease (PAD) is heterogeneous even in the presence of similar risk factors. Our aim was to determine whether inter-individual differences in leukocyte telomere length contribute to the susceptibility of PAD. Methods A total of 485 patients with PAD (defined by the ankle-brachial index) and 970 age- and gender-matched controls were recruited from seven rural communities in Henan Province in China. The relative leukocyte telomere length was determined by a quantitative PCR-based method. Two common promoter variants of the hTERT gene were genotyped to assess their effects on telomere length and the risk of PAD. In vivo luciferase assay was performed to study the transcriptional activity. Results: After adjustment for vascular risk factors and genetic variants in the hTERT gene, individuals in the lowest and middle tertiles of telomere length had a significantly higher risk of PAD than did those in the highest tertile (odds ratio [OR] 1.73, 95% confidence interval [CI] 1.29–2.49 in the middle tertile; 3.15, 95%CI 2.31–4.29 in the lowest tertile). Haplotype analysis using the 2 variants (rs2735940 and rs2853669) showed that subjects with the at-risk C-C haplotype had shorter telomere length than those individuals with the T-T haplotype and consistently had 1.30-fold (OR 1.30, 95%CI 1.06–1.58; P = 0.005) increased risk for PAD. The C-C haplotype had 43% lowered transcription activity of hTERT promoter (P<0.001). Conclusion: The associations between the functional haplotype of hTERT gene and telomere length and the risk of atherosclerotic PAD suggested that mean leukocyte telomere length may independently serve as a potential predictor of PAD

Multi-omics analysis reveals the prognostic and tumor micro-environmental value of lumican in multiple cancer types

Background: Lumican (LUM), a proteoglycan of the extracellular matrix, has been reported to be involved in the regulation of immune escape processes, but the data supporting this phenomenon are not sufficient. In this study, we aimed to explore the links among LUM expression, survival, tumor microenvironment (TME), and immunotherapy in 33 cancer types.Methods: Data from several databases, such as UCSC Xena, GTEx, UALCAN, HPA, GEPIA2, TISIDB, PrognoScan, TIMER2, and GEO, as well as published studies, were used to determine the relationship between LUM expression and clinical features, TME, heterogeneity, and tumor stemness.Results: The expression of LUM was statistically different in most tumors versus normal tissues, both at the RNA and protein expression levels. High expression of LUM was typically associated with a poor prognosis in tumors. Additionally, immune scores, six immune cells, four immunosuppressive cells, cancer-associated fibroblasts (CAFs)-associated and immunosuppressive factors, tumor mutation burden (TMB), microsatellite instability (MSI), DNAss, and RNAss were all significantly associated with LUM. Among them, LUM expression displayed a significant positive correlation with CAFs and their factors, and exhibited immunosuppressive effects in six independent immunotherapy cohorts.Conclusion: Multi-omics analysis suggests that LUM may have been a prognostic marker, contributed to immunosuppression in the TME, and decreased the effectiveness of immune checkpoint inhibitors

Optical Model and Optimization for Coherent-Incoherent Hybrid Organic Solar Cells with Nanostructures

Embedding nanostructures in organic solar cells (OSCs) is a well-known method to improve the absorption efficiency of the device by introducing the plasma resonance and scattering effects without increasing the active layer thickness. The introduction of nanostructures imposes greater demands on the optical analysis method for OSCs. In this paper, the generalized rigorous coupled-wave analysis (GRCWA) is presented to analyze and optimize the performance of coherent-incoherent hybrid organic solar cells (OSCs) with nanostructures. Considering the multiple reflections of light scattered within the glass substrate by the device, the correction vector g is derived, then the modified expressions for the field and absorption distribution in OSCs are provided. The proposed method is validated by comparing the simulated results of various structures with results obtained by the generalized transfer matrix method (GTMM) and the &ldquo;equispaced thickness method&rdquo; (ETM). The results demonstrate that the proposed method can reduce the number of simulations by at least half compared to the ETM while maintaining accuracy. With the proposed method, we discussed the device performance depending on the geometrical parameters of nanostructures, and the optimization and analysis are accomplished for single and tandem OSCs. After optimization based on the proposed method, the performance of OSCs are significantly improved, which further demonstrates the practicality of the method

Sound-Based Construction Activity Monitoring with Deep Learning

Automated construction monitoring assists site managers in managing safety, schedule, and productivity effectively. Existing research focuses on identifying construction sounds to determine the type of construction activity. However, there are two major limitations: the inability to handle a mixed sound environment in which multiple construction activity sounds occur simultaneously, and the inability to precisely locate the start and end times of each individual construction activity. This research aims to fill this gap through developing an innovative deep learning-based method. The proposed model combines the benefits of Convolutional Neural Network (CNN) for extracting features and Recurrent Neural Network (RNN) for leveraging contextual information to handle construction environments with polyphony and noise. In addition, the dual threshold output permits exact identification of the start and finish timings of individual construction activities. Before training and testing with construction sounds collected from a modular construction factory, the model has been pre-trained with publicly available general sound event data. All of the innovative designs have been confirmed by an ablation study, and two extended experiments were also performed to verify the versatility of the present model in additional construction environments or activities. This model has great potential to be used for autonomous monitoring of construction activities

Using technology-based learning tool to train facial expression recognition and emotion understanding skills of Chinese pre-schoolers with autism spectrum disorder

Objectives: Given the pervasiveness of emotional and behavioral deficits of individuals with Autism Spectrum Disorders (ASD), there is a pressing need for effective interventions to address their difficulties on Facial Expression Recognition and Emotion Understanding (FER/EU). Qunatiandi, a structured, app-based intervention program that is designed for Chinese children with ASD was utilized in this study. Three young children (two girls and one boy; age M = 4.94 years) completed an 8-week one-on-one intervention in a rehabilitation center setting. It was hypothesized that the three children would show greater progress in their FER/EU. Methods: In this study, a modified multiple probe across the program phases design was used; the dependent variable was the percentage of unprompted correct receptive identification responses for FER/EU tests during instruction and probes. Data were taken during baseline, the endpoint of instruction sessions, and a maintenance stage followed by intervention termination. Results: Findings of the study revealed that all participants demonstrated significant improvements in social acuity, gains were mostly achieved on emotion distinguishing and understanding (above 80% of accuracy). A similar scoring pattern was also found in the maintenance probe phase. Conclusion: The study is one of only a few early intervention projects to improve FER/EU skills for children with ASD using an app-based intervention. The results demonstrated that children with ASD can experience increases in emotion distinguishing and understanding skills. Maintenance probe results showed that the interventional effect can be maintained for a period of time after intervention

MicroRNA-216a Promotes Endothelial Inflammation by Smad7/IκBα Pathway in Atherosclerosis

Background. The endothelium is the first line of defence against harmful microenvironment risks, and microRNAs (miRNAs) involved in vascular inflammation may be promising therapeutic targets to modulate atherosclerosis progression. In this study, we aimed to investigate the mechanism by which microRNA-216a (miR-216a) modulated inflammation activation of endothelial cells. Methods. A replicative senescence model of human umbilical vein endothelial cells (HUVECs) was established, and population-doubling levels (PDLs) were defined during passages. PDL8 HUVECs were transfected with miR-216a mimics/inhibitor or small interfering RNA (siRNA) of SMAD family member 7 (Smad7). Real-time PCR and Western blot assays were performed to detect the regulatory role of miR-216a on Smad7 and NF-κB inhibitor alpha (IκBα) expression. The effect of miR-216a on adhesive capability of HUVECs to THP-1 cells was examined. MiR-216a and Smad7 expression in vivo were measured using human carotid atherosclerotic plaques of the patients who underwent carotid endarterectomy (n=41). Results. Luciferase assays showed that Smad7 was a direct target of miR-216a. Smad7 mRNA expression, negatively correlated with miR-216a during endothelial aging, was downregulated in senescent PDL44 cells, compared with young PDL8 HUVECs. MiR-216a markedly increased endothelial inflammation and adhesive capability to monocytes in PDL8 cells by promoting the phosphorylation and degradation of IκBα and then activating NF-κB signalling pathway. The effect of miR-216a on endothelial cells was consistent with that blocked Smad7 by siRNAs. When inhibiting endogenous miR-216a, the Smad7/IκBα expression was rescued, which led to decreased endothelial inflammation and monocytes recruitment. In human carotid atherosclerotic plaques, Smad7 level was remarkably decreased in high miR-216a group compared with low miR-216a group. Moreover, miR-216a was negatively correlated with Smad7 and IκBα levels and positively correlated with interleukin 1 beta (IL1β) expression in vivo. Conclusion. In summary, our findings suggest a new mechanism of vascular endothelial inflammation involving Smad7/IκBα signalling pathway in atherosclerosis