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Abstract The surrounding rock of tunnels in cold regions are susceptible to the freeze–thaw cycle resulting from the combination of low temperatures and moisture during tunnel service. The phenomenon will not only lead to the expansion of pores and fissures in the surrounding rock of the initial tunnel, but also destroy the integrity of the rock. This destruction will have a serious impact on tunnel structure and rail transit operation safety. At present, the commonly used thermal insulation measures have some problems such as maintenance difficulties, low economic efficiency, and safety hazards. Therefore, it is urgent to develop a kind of tunnel maintenance grouting material with insulation and anti-permeability, which has the characteristics of simple operation, easy preparation and application. We independently developed a composite grouting material composed of polyurethane (PU), epoxy resin (E-51) and acrylic powder (PMMA). Through the material combustion test, magnesium hydroxide was selected as the flame retardant additive. Moreover, we measured the thermal conductivity, water absorption, apparent density, porosity and strength characteristic parameters. The thermal insulation and anti-permeability characteristics of the composites were also analyzed. The results indicated that the thermal conductivity of the new composite grouting material is 6.3% lower than the PU before adding flame retardant. Compared with the PU with flame retardant, the water absorption decreased by 74.4% and the ultimate strength increased by 33.3%. For the area with an average temperature lower than − 10 °C, we recommend the ratio scheme of E-51: 3%; PMMA: 15%. For the area with high water content in the surrounding rock of the tunnel, we recommend the ratio scheme of E-51: 15%; PMMA: 3%. This study provides new ideas for material preparation and tunnel insulation methods for anti-freezing measures in tunnels during their operational period in cold regions.

Abstract Fruit tree identification that is quick and precise lays the groundwork for scientifically evaluating orchard yields and dynamically monitoring planting areas. This study aims to evaluate the applicability of time series Sentinel-1/2 satellite data for fruit tree classification and to provide a new method for accurately extracting fruit tree species. Therefore, the study area selected is the Tarim Basin, the most important fruit-growing region in northwest China. The main focus is on identifying several major fruit tree species in this region. Time series Sentinel-1/2 satellite images acquired from the Google Earth Engine (GEE) platform are used for the study. A multi-scale segmentation approach is applied, and six categories of features including spectral, phenological, texture, polarization, vegetation index, and red edge index features are constructed. A total of forth-four features are extracted and optimized using the Vi feature importance index to determine the best time phase. Based on this, an object-oriented (OO) segmentation combined with the Random Forest (RF) method is used to identify fruit tree species. To find the best method for fruit tree identification, the results are compared with three other widely used traditional machine learning algorithms: Support Vector Machine (SVM), Gradient Boosting Decision Tree (GBDT), and Classification and Regression Tree (CART). The results show that: (1) the object-oriented segmentation method helps to improve the accuracy of fruit tree identification features, and September satellite images provide the best time window for fruit tree identification, with spectral, phenological, and texture features contributing the most to fruit tree species identification. (2) The RF model has higher accuracy in identifying fruit tree species than other machine learning models, with an overall accuracy (OA) and a kappa coefficient (KC) of 94.60% and 93.74% respectively, indicating that the combination of object-oriented segmentation and RF algorithm has great value and potential for fruit tree identification and classification. This method can be applied to large-scale fruit tree remote sensing classification and provides an effective technical means for monitoring fruit tree planting areas using medium-to-high-resolution remote sensing images.

Abstract Colon adenocarcinoma (COAD) is the second leading cause of cancer death, and there is still a lack of diagnostic biomarkers and therapeutic targets. In this study, bioinformatics analysis of the TCGA database was used to obtain RUNX1, a gene with prognostic value in COAD. RUNX1 plays an important role in many malignancies, and its molecular regulatory mechanisms in COAD remain to be fully understood. To explore the physiological role of RUNX1, we performed functional analyses, such as CCK-8, colony formation and migration assays. In addition, we investigated the underlying mechanisms using transcriptome sequencing and chromatin immunoprecipitation assays. RUNX1 is highly expressed in COAD patients and significantly correlates with survival. Silencing of RUNX1 significantly slowed down the proliferation and migratory capacity of COAD cells. Furthermore, we demonstrate that CDC20 and MCM2 may be target genes of RUNX1, and that RUNX1 may be physically linked to the deubiquitinating enzyme USP31, which mediates the upregulation of RUNX1 protein to promote transcriptional function. Our results may provide new insights into the mechanism of action of RUNX1 in COAD and reveal potential therapeutic targets for this disease.

Abstract Phase-to-height mapping is one of the important processes in three dimensional phase measurement profilometry. But, in traditional phase-to-height mapping method, the measurement accuracy is affected by device attitude, so it needs saving a large amount of mapping equations to achieve high-quality phase-to-height mapping. In order to improve that, this paper proposes an improved phase-to-height mapping method combine with device attitude. Firstly, we get the unwrapped phase of the target. Then, using generalized regression neural network is used to reduce the offset of phase information at the same height due to the randomness of device attitude. Last, the phase-to-height mapping is completed by substituting the unwrapped phase (the difference between having detected object and no detected object) of eliminate the offset into improved phase-to-height mapping method. Experimental results show that the proposed method could achieve high-quality phase-to-height mapping with less mapping equation and less memory space. Compared with the nonlinear phase-to-height mapping method (probabilistic neural network to eliminate phase offset), its accuracy is improved by 44.30%. Compared with the nonlinear phase-to-height mapping method (radial basis function neural network to eliminate phase offset), the accuracy is improved by 39.58%.

Abstract The structural characteristics of plant communities in urban green spaces have a significant impact on their carbon sequestration function. In this study, comprehensive data were collected from 106 plant communities (each 20 m × 20 m) in Zhengzhou Green Expo Park. We assessed aboveground and soil carbon storage, alongside maintenance carbon emissions, to quantify carbon dynamics. Our primary objective was to establish a statistical model that correlates the structural attributes of plant communities with their total annual carbon sequestration. This model aims to provide a quantitative framework for optimizing community structures to maximize carbon sequestration in urban green spaces. The results showed that density and coverage were significantly and positively correlated with aboveground and soil carbon stocks. Density and mean height were significantly and positively correlated with maintenance carbon emissions. Density played a key structural role in regulating the total carbon sequestration of the plant communities, being 27.24 times more effective than coverage. The total annual carbon sequestration of the plant community reached an optimal value of 327.67 kg CO2-eq/y−1 at a density and cover of 0.15 and 1, respectively. This study provides valuable data for increasing the carbon sink ability of urban green spaces through plant structure regulation and supporting low-carbon development strategies in urban management.

Abstract B-cell subsets in peripheral blood (PB) and tumor microenvironment (TME) were evaluated to determine myasthenia gravis (MG) severity in patients with thymoma-associated MG (TMG) and the distribution of B cells in type B TMG. The distribution of mature B cells, including Bm1–Bm5, CD19+ and CD20+ B cells and non-switched (NSMBCs) and switched (SMBCs) memory B cells, were determined in 79 patients with thymoma or TMG. Quantitative relationships between the T and TMG groups and the TMG-low and TMG-high subgroups were determined. NSMBCs and SMBCs were compared in TME and PB. Type B thymoma was more likely to develop into MG, with types B2 and B3 being especially associated with MG worsening. The percentage of CD19+ B cells in PB gradually increased, whereas the percentage of CD20+ B cells and the CD19/CD20 ratio were not altered. The (Bm2 + Bm2′)/(eBm5 + Bm5) index was significantly higher in the TMG-high than in thymoma group. The difference between SMBC/CD19+ and NSMBC/CD19+ B cell ratios was significantly lower in the thymoma than TMG group. NSMBCs assembled around tertiary lymphoid tissue in thymomas of patients with TMG. Few NSMBCs were observed in patients with thymoma alone, with these cells being diffusely distributed. MG severity in patients with TMG can be determined by measuring CD19+ B cells and Bm1-Bm5 in PB. The CD19/CD20 ratio is a marker of disease severity in TMG patients. Differences between NSMBCs and SMBCs in PB and TME of thymomas can synergistically determine MG severity in patients with TMG.

Abstract To explore the psychological experience and emotional needs of returning to family and society after treatment in an adolescent with cancer. A phenomenological research design was employed to conduct a semi-structured interview with nine cancer adolescents in the convalescence stage. Colaizzi’s seven-step analysis was used for the data analysis. Three themes of the psychological experience of an adolescent with cancer in convalescence were summarized: continuous negative emotions, emotionally intense behavior, and discomfort of returning to society. The psychological experience of an adolescent with cancer in convalescence returning to family and community is sensitive and complex. Medical staff, families, and schools should provide personalized care according to their different psychological characteristics and emotional needs so that they can return to family and society smoothly.

Abstract Osteosarcoma (OS) is one of the most prevalent bone tumors in adolescents, and the correlation between aging and OS remains unclear. Currently, few accurate and reliable biomarkers have been determined for OS prognosis. To address this issue, we carried out a detailed bioinformatics analysis based on OS with data from the Cancer Genome Atlas data portal and Human Aging Genomic Resources database, as well as in vitro experiments. A total of 88 OS samples with gene expression profiles and corresponding clinical characteristics were obtained. Through univariate Cox regression analysis and survival analysis, 10 aging-associated survival lncRNAs (AASRs) were identified to be associated with the overall survival of OS patients. Based on the expression levels of the 10 AASRs, the OS patients were classified into two clusters (Cluster A and Cluster B). Cluster A had a worse prognosis, while Cluster B had a better prognosis. Then, 5 AASRs were ultimately included in the signature through least absolute shrinkage and selection operator-Cox regression analysis. Kaplan‒Meier survival analysis verified that the high-risk group exhibited a worse prognosis than the low-risk group. Furthermore, univariate and multivariate Cox regression analyses confirmed that the riskScore was an independent prognostic factor for OS patients. Subsequently, we discovered that the risk signature was correlated with the properties of the tumor microenvironment and immune cell infiltration. Specifically, there was a positive association between the risk model and naïve B cells, resting dendritic cells and gamma delta T cells, while it was negatively related to CD8+ T cells. Finally, in vitro experiments, we found that UNC5B-AS1 inhibited OS cells from undergoing cellular senescence and apoptosis, thereby promoting OS cells proliferation. In conclusion, we constructed and verified a 5 AASR-based signature, that exhibited excellent performance in evaluating the overall survival of OS patients. In addition, we found that UNC5B-AS1 might inhibit the senescence process, thus leading to the development and progression of OS. Our findings may provide novel insights into the treatment of OS patients.

Abstract Non-syndromic cleft lip with or without cleft palate (NSCL/P) is a common congenital facial malformation with a complex, incompletely understood origin. Long noncoding RNAs (lncRNAs) have emerged as pivotal regulators of gene expression, potentially shedding light on NSCL/P's etiology. This study aimed to identify critical lncRNAs and construct regulatory networks to unveil NSCL/P's underlying molecular mechanisms. Integrating gene expression profiles from the Gene Expression Omnibus (GEO) database, we pinpointed 30 dysregulated NSCL/P-associated lncRNAs. Subsequent analyses enabled the creation of competing endogenous RNA (ceRNA) networks, lncRNA-RNA binding protein (RBP) interaction networks, and lncRNA cis and trans regulation networks. RT-qPCR was used to examine the regulatory networks of lncRNA in vivo and in vitro. Furthermore, protein levels of lncRNA target genes were validated in human NSCL/P tissue samples and murine palatal shelves. Consequently, two lncRNAs and three mRNAs: FENDRR (log2FC = − 0.671, P = 0.040), TPT1-AS1 (log2FC = 0.854, P = 0.003), EIF3H (log2FC = − 1.081, P = 0.041), RBBP6 (log2FC = 0.914, P = 0.037), and SRSF1 (log2FC = 0.763, P = 0.026) emerged as potential contributors to NSCL/P pathogenesis. Functional enrichment analyses illuminated the biological functions and pathways associated with these lncRNA-related networks in NSCL/P. In summary, this study comprehensively delineates the dysregulated transcriptional landscape, identifies associated lncRNAs, and reveals pivotal sub-networks relevant to NSCL/P development, aiding our understanding of its molecular progression and setting the stage for further exploration of lncRNA and mRNA regulation in NSCL/P.

Abstract In this paper, the near-field lightwave characteristics of an arrayed silicon nano-cone-tip optical antenna (NOA) covered by a common metal film, which can be viewed as a featured quasi quantum dot (QD), are carefully investigated. A dipole net-charge distribution closely correlated with the surface lightwaves excited over the antennas by incident lasers with a central wavelength of 633 nm, is clearly observed. An obvious Coulomb-like blockade from the apex apparently influencing the net-charge converging over the surface of NOA, is verified, which can also be predicted by the simulations according to surface standing waves across the apex node. The antinodes of the surface net-charge instantaneous distribution are already pushed away from the normal location owing to the apex Coulomb-like blockade, so as to present a distorted waveform different from traditional standing wave modes. The tip proximity effect leading to a relatively weak net-charge converging over surrounding planar facet and adjacent NOAs, is also discovered.

Abstract Image perturbation is a promising technique to assess radiomic feature repeatability, but whether it can achieve the same effect as test–retest imaging on model reliability is unknown. This study aimed to compare radiomic model reliability based on repeatable features determined by the two methods using four different classifiers. A 191-patient public breast cancer dataset with 71 test–retest scans was used with pre-determined 117 training and 74 testing samples. We collected apparent diffusion coefficient images and manual tumor segmentations for radiomic feature extraction. Random translations, rotations, and contour randomizations were performed on the training images, and intra-class correlation coefficient (ICC) was used to filter high repeatable features. We evaluated model reliability in both internal generalizability and robustness, which were quantified by training and testing AUC and prediction ICC. Higher testing performance was found at higher feature ICC thresholds, but it dropped significantly at ICC = 0.95 for the test–retest model. Similar optimal reliability can be achieved with testing AUC = 0.7–0.8 and prediction ICC > 0.9 at the ICC threshold of 0.9. It is recommended to include feature repeatability analysis using image perturbation in any radiomic study when test–retest is not feasible, but care should be taken when deciding the optimal feature repeatability criteria.

Abstract This paper proposes a functionally reconfigurable integrated structure of a Fabry–Perot (FP) antenna and wideband liquid absorber. First, a two-layer partial reflecting surface (PRS) has been designed. Then, a patch antenna is used to act as the source antenna. By combining the source antenna with the PRS, an FP antenna has been designed. What’s more, taking full advantage of the reflective properties of PRS, a liquid broadband absorber is then designed. Last, the integrated structure with two functions has been realized. It can be used as the FP antenna or the liquid absorber through the extraction and injection of ethanol. In this way, it is effective to switch between stealth and detection states which can be used in different electromagnetic environments. The PRS is elaborately tailored to serve as both a component of the FP antenna and the metal ground of the broadband liquid absorber. Then the integrated structure is realized by combining the FP antenna with the liquid absorber. The PRS is composed of patches on the top layer of the substrate and the square loop on the bottom. The liquid absorber is composed of a 3-D printed container, 45% ethanol layer and the PRS is used to serve as the metal ground. The formula of Mie resonance theory has been extended and used to design the liquid absorber. The gain of the antenna is 19.7 dBi when the ethanol is extracted. When the ethanol is injected, a wideband liquid absorber is achieved. The absorption band (S 11

Abstract A kind of gold-coated glass nano-cone-tips (GGNCTs) is developed as an arrayed optical antenna for highly receiving and converging incident lightwaves. A local light field enhancement factor (LFEF) of ~ 2 × 104 and maximum light absorption of ~ 98% can be achieved. The near-field lightwave measurements at the wavelength of 633 nm show that the surface net charges over a single GGNCT make a typical dipole oscillation and the energy transmits along the wave vector orientation, thus leading to a strong local light field enhancement. An effective detection method by near-field coupling an arrayed GGNCT and complementary metal–oxide–semiconductor (CMOS) sensor for highly efficient imaging detection is proposed. The lightwave detection at several wavelengths, including typical 473 nm, 532 nm, 671 nm, and 980 nm, shows a notable characteristic that a better capability of the net charge distribution adjusting and localized aggregating can be obtained at the absorption peak of the GGNCT developed and a stronger signal detection achieved. The research lays a foundation for further developing a light detector with an ideal optoelectronic sensitivity and broad spectral suitability, which is based on integrating GGNCTs as an arrayed optical antenna with common sensors.

Abstract We investigate the tracking control problem for a non-strict feedback nonlinear system with external disturbance and time-varying asymmetric full state constraints. Firstly, the unknown nonlinear term with external disturbance in the system are estimated by fuzzy logic system. The backstepping method is applied to the design of adaptive fuzzy controller. However, to prevent that the constraints are overstepped by introducing an improved log-type time-varying asymmetric barrier Lyapunov function (TABLF) in each step of backstepping design. Secondly, the dynamic surface control (DSC) is introduced in the designed algorithm to solve the computational explosion problem of controller caused by the derivative of control law. The proposed control scheme can speed up the tracking speed of the system. Compared with the previous work, it is verified that the combination of DSC and TABLF can obtain good performance within the constraint range, and can ensure fast and stable tracking convergence under external disturbance. Finally, two simulation examples verify the performance of the adaptive controller.

Abstract Culex pipiens pallens is an important vector of lymphatic filariasis and epidemic encephalitis. Mosquito control is the main strategy used for the prevention of mosquito-borne diseases. Bacillus thuringiensis israelensis (Bti) is an entomopathogenic bacterium widely used in mosquito control. In this study, we profiled the microbiota and transcriptional response of the larvae of Cx. pipiens pallens exposed to different concentrations of Bti. The results demonstrated that Bti induced a significant effect on both the microbiota and gene expression of Cx. pipiens pallens. Compared to the control group, the predominant bacteria changed from Actinobacteria to Firmicutes, and with increase in the concentration of Bti, the abundance of Actinobacteria was gradually reduced. Similar changes were also detected at the genus level, where Bacillus replaced Microbacterium, becoming the predominant genus in Bti-exposed groups. Furthermore, alpha diversity analysis indicated that Bti exposure changed the diversity of the microbota, possibly because the dysbiosis caused by the Bti infection inhibits some bacteria and provides opportunities to other opportunistic taxa. Pathway analysis revealed significant enhancement for processes associated with sphingolipid metabolism, glutathione metabolism and glycerophospholipid metabolism between all Bti-exposed groups and control group. Additionally, genes associated with the Toll and Imd signaling pathway were found to be notably upregulated. Bti infection significantly changed the bacterial community of larvae of Cx. pipiens pallens.

Abstract Coronavirus 2019 (COVID-19) is a new acute respiratory disease that has spread rapidly throughout the world. In this paper, a lightweight convolutional neural network (CNN) model named multi-scale gated multi-head attention depthwise separable CNN (MGMADS-CNN) is proposed, which is based on attention mechanism and depthwise separable convolution. A multi-scale gated multi-head attention mechanism is designed to extract effective feature information from the COVID-19 X-ray and CT images for classification. Moreover, the depthwise separable convolution layers are adopted as MGMADS-CNN’s backbone to reduce the model size and parameters. The LeNet-5, AlexNet, GoogLeNet, ResNet, VGGNet-16, and three MGMADS-CNN models are trained, validated and tested with tenfold cross-validation on X-ray and CT images. The results show that MGMADS-CNN with three attention layers (MGMADS-3) has achieved accuracy of 96.75% on X-ray images and 98.25% on CT images. The specificity and sensitivity are 98.06% and 96.6% on X-ray images, and 98.17% and 98.05% on CT images. The size of MGMADS-3 model is only 43.6 M bytes. In addition, the detection speed of MGMADS-3 on X-ray images and CT images are 6.09 ms and 4.23 ms for per image, respectively. It is proved that the MGMADS-3 can detect and classify COVID-19 faster with higher accuracy and efficiency.

Abstract This study aimed to identify potential novel drug candidates and targets for Parkinson’s disease. First, 970 genes that have been reported to be related to PD were collected from five databases, and functional enrichment analysis of these genes was conducted to investigate their potential mechanisms. Then, we collected drugs and related targets from DrugBank, narrowed the list by proximity scores and Inverted Gene Set Enrichment analysis of drug targets, and identified potential drug candidates for PD treatment. Finally, we compared the expression distribution of the candidate drug-target genes between the PD group and the control group in the public dataset with the largest sample size (GSE99039) in Gene Expression Omnibus. Ten drugs with an FDR

Abstract We aimed to compare the demographic, clinical and laboratory characteristics between IgG4-related kidney disease (IgG4-RKD+) and extrarenal IgG4-related disease (IgG4-RKD−) in a large Chinese cohort, as well as describing the radiological and pathological features of IgG4-RKD+. We retrospectively analyzed the medical records of 470 IgG4-related disease (IgG4-RD) patients at Peking University People’s Hospital from January 2004 to January 2020. The demographic, clinical, laboratory, radiological and pathological characteristics between IgG4-RKD+ and IgG4-RKD− were compared. Twenty IgG4-RD patients who had definite etiology of renal impairment including diabetes, hypertension and etc. were excluded. Among the remained 450 IgG4-RD patients, 53 were diagnosed with IgG4-RKD+ . IgG4-RKD+ patients had older age at onset and at diagnosis. Male to female ratio of IgG4-RKD+ patients is significantly higher. In the IgG4-RKD+ group, the most commonly involved organs were salivary gland, lymph nodes and pancreas. It was found that renal function was impaired in approximately 40% of IgG4-RKD+ patients. The most common imaging finding is multiple, often bilateral, hypodense lesions. Male sex, more than three organs involved, and low serum C3 level were risk factors for IgG4-RKD+ in IgG4-RD patients. These findings indicate potential differences in pathogenesis of these two phenotypes.

Abstract Leaf photosynthetic capacity is mainly constrained by nitrogen (N) and phosphorus (P). Little attention has been given to the photosynthetic capacity of mature forests with high calcium (Ca) and magnesium (Mg) in the Karst critical zone. We measured light-saturated net photosynthesis (A sat), photosynthetic capacity (maximum carboxylation rate [V cmax], and maximum electron transport rate [J max]) as well as leaf nutrient contents (N, P, Ca, Mg, potassium [K], and sodium [Na]), leaf mass per area (LMA), and leaf thickness (LT) in 63 dominant plants in a mature subtropical forest in the Karst critical zone in southwestern China. Compared with global data, plants showed higher A sat for a given level of P. V cmax and J max were mainly co-regulated by N, P, Mg, and LT. The ratios of V cmax to N or P, and J max to N or P were significantly positively related to Mg. We speculate that the photosynthetic capacity of Karst plants can be modified by Mg because Mg can enhance photosynthetic N and P use efficiency.