Search

In this study, methoxypolyethylene glycol acrylate (mPEGA) served as a PEGylated monomer and was grafted onto polyvinylidene fluoride (PVDF) through homogeneous solution gamma irradiation. The grafting process was confirmed using several techniques, including infrared spectroscopy (FTIR), thermodynamic stability assessments, and rotational viscosity measurements. The degree of grafting (DG) was determined via the gravimetric method. By varying the monomer concentration, a range of DGs was achieved in the PVDF-g-mPEGA copolymers. Investigations into water contact angles and scanning electron microscopy (SEM) images indicated a direct correlation between increased hydrophilicity, membrane porosity, and higher DG levels in the PVDF-g-mPEGA membrane. Filtration tests demonstrated that enhanced DGs resulted in more permeable PVDF-g-mPEGA membranes, eliminating the need for pore-forming agents. Antifouling tests revealed that membranes with a lower DG maintained a high flux recovery rate, indicating that the innate properties of PVDF could be largely preserved.

A fast spraying speed, wide working area, and easy operation are the operational advantages of high-clearance boom sprayers. To address the issue of spray boom mechanical vibration affecting the spraying effect, a double-link trapezoidal boom suspension is designed for the 3WPYZ sprayer. This suspension can achieve passive vibration reduction, active balance, and ground profiling. The kinematic model of the boom suspension is established based on D’Alembert’s principle and the principle of multi-body dynamics, and the design factors affecting the stability of the boom are determined. Through orthogonal experimental design and virtual kinematics simulation, the influence of the boom length and orifice diameter of each part on the swing angle and the natural frequency of the boom suspension is investigated. Design-Expert 8.0.6 software is used to analyze and optimize the test results. The optimization results show that, when the connecting boom length LAB is 265 mm, the inner boom suspension boom length LAD is 840 mm, the outer boom suspension boom length LBC is 1250 mm, and the throttle hole diameter d is 4 mm; the maximum swing angle of the boom suspension is reduced by 53.02%. In addition, the natural frequency of the boom is reduced from 1.3143 rad/s to 1.1826 rad/s, and the dynamic characteristic optimization effect is remarkable. The modal analysis results show that the first sixth-order vibration test frequency of the boom sprayer suspension designed in this paper meets the requirements and avoids the influence of external factors. Field tests show that, when the sprayer is excited by the environment at 3.5° to 4°, the boom suspension can reduce the vibration transmitted by the body to a reasonable range. The static analysis shows that the structural design of this study reduces the stress at the connection of the end boom suspension, the maximum displacement, and the maximum stress of the inner boom suspension. The test results of the dynamic characteristics of the implement are basically consistent with the virtual model simulation test results, thus achieving the optimization objectives.

Landslides are a common geological disaster, which cause many economic losses and casualties in the world each year. Drawing up a landslide list and monitoring their deformations is crucial to prevent landslide disasters. Interferometric synthetic aperture radar (InSAR) can obtain millimeter-level surface deformations and provide data support for landslide deformation monitoring. However, some landslides are difficult to detect due to the low-coherence caused by vegetation cover in mountainous areas and the difficulty of phase unwrapping caused by large landslide deformations. In this paper, a method based on multi-direction phase gradient stacking is proposed. It employs the differential interferograms of small baseline sets to directly obtain the abnormal region, thereby avoiding the problem where part of landslide cannot be detected due to a phase unwrapping error. In this study, the Sentinel-1 satellite ascending and descending data from 2018 to 2020 are used to detect landslides around Zhouqu County, China. A total of 26 active landslides were detected in ascending data and 32 active landslides in the descending data using the method in this paper, while the SBAS-InSAR detected 19 active landslides in the ascending data and 25 active landslides in the descending data. The method in this paper can successfully detect landslides in areas that are difficult for the SBAS-InSAR to detect. In addition, the proposed method does not require phase unwrapping, so a significant amount of data processing time can be saved.

The ^18 O( p , α ) ^15 N reaction is of particular importance for influencing the abundances of key isotopes such as ^19 F, ^18 O, and ^15 N. Peculiar abundances for these nuclei are observed from spectra or meteorite grains originating in asymptotic giant branch stars. The ^18 O( p , α ) ^15 N could provide a way to explain the discrepancy between the observations and model predictions. A comprehensive R -matrix analysis has been performed for the ^18 O( p , α ) ^15 N reaction by including additional constraints from other reaction channels; in particular, the ^15 N+ α scattering data were involved in the analysis for the first time. All available data were compiled and used in the R -matrix analysis. The fitted resonance parameters are compared with previous works. A revised determination of reaction rate has been extracted, relying on the present fitting parameters. The uncertainties on the corresponding reaction rates were then obtained by a Monte Carlo analysis.

The physics potential of detecting ^8 B solar neutrinos will be exploited at the Jiangmen Underground Neutrino Observatory (JUNO), in a model-independent manner by using three distinct channels of the charged current (CC), neutral current (NC), and elastic scattering (ES) interactions. Due to the largest-ever mass of ^13 C nuclei in the liquid scintillator detectors and the expected low background level, ^8 B solar neutrinos are observable in the CC and NC interactions on ^13 C for the first time. By virtue of optimized event selections and muon veto strategies, backgrounds from the accidental coincidence, muon-induced isotopes, and external backgrounds can be greatly suppressed. Excellent signal-to-background ratios can be achieved in the CC, NC, and ES channels to guarantee the observation of the ^8 B solar neutrinos. From the sensitivity studies performed in this work, we show that JUNO, with 10 yr of data, can reach the 1 σ precision levels of 5%, 8%, and 20% for the ^8 B neutrino flux, ${\sin }^{2}{\theta }_{12}$ , and ${\rm{\Delta }}{m}_{21}^{2}$ , respectively. Probing the details of both solar physics and neutrino physics would be unique and helpful. In addition, when combined with the Sudbury Neutrino Observatory measurement, the world's best precision of 3% is expected for the measurement of the ^8 B neutrino flux.

Sucrose synthase (SUS) and sucrose phosphate synthase (SPS) are essential in plant sucrose metabolism. The potato is an important crop worldwide, but systematic analyses of the StSUS and StSPS gene families in potatoes are still lacking. Ten sucrose metabolism-related genes were identified in this study. The SUSs and SPSs could each be split into three subgroups through phylogenetic analysis. StSUSIc was the most highly expressed gene in different developmental tissues. Ka/Ks analysis showed that StSUSIb and StSUSIc were subjected to more-significant homozygous selection pressure. Our cis-acting element analysis of the StSUS and StSPS promoter sequences showed four elements: defense- and stress-responsive, hormone-responsive, light-responsive, and transcription factor elements. The expression of StSUS and StSPS genes was found to be regulated by circadian rhythm. In the treatments of 1% to 5% sucrose, glucose, and fructose, the expression of StSUS and StSPS family genes was enhanced by sucrose, but inhibited at high-glucose and fructose concentrations. This study identified six StSUS and four StSPS genes and analyzed their gene structure, conserved motifs, chromosome position, promoter elements, phylogenetic tree, and tissue-specific expression patterns. Our results will motivate more research into the biological process underlying the genes of sucrose metabolism in potatoes.

To make measurement of end-wall flow between blade rows in a compact multistage configuration possible, a miniature L-shaped five-hole probe was employed in this paper. This compact tip structure, realized by laser-printing instead of the conventional machining technique, reduces the blockage effect of this intrusive measurement on the flow and ensures high spatial resolution. The zonal method is introduced to extend the usable flow angle range up to 60 degrees. A local least-squares interpolation technique is utilized to acquire flow angle and static/total pressure. In order to improve accuracy for the points located at the sector boundary, the overlap region method is included in the interpolation. Additional test data indicate that the maximum error in flow angle is nearly within 1 degree, and the maximum errors of total pressure and static pressure are 0.56% and 1.9% respectively. The application in a low-speed multistage axial compressor indicates that the zonal method can decrease the number of points exceeding the measurable flow range and is of great significance for the end-wall flow measurement, especially for the near-stall condition. Compared with the traditional method, the proportion of available data for the near-stall state measurement was increased by 18% by using the zonal method.

Based on the transient-performance calculation model of a dual-spool mixed-flow turbofan engine, this article improves the dynamic algorithm of geometric adjustment mechanisms and establishes a transient-performance calculation model suitable for a three-stream adaptive cycle engine (three-stream ACE). Using this model, the transient characteristics of a three-stream ACE were analyzed. The results indicate that the delay in the area of the fan nozzle significantly reduces the surge margin of the front fan during deceleration, while the delay in the angle of the front-fan and aft-fan guide vanes significantly reduces the surge margin of the front fan during acceleration, therefore becoming a limitation of the transient performance of the engine. At the same time, to meet the demand for equal-thrust mode switching, this article also proposes a mode-switching control scheme that solves the problem of engine state oscillation during the mode-conversion process and achieves a smooth conversion with thrust fluctuations within 1%. The research results of this article can guide the optimization design of three-stream ACE transition-state control laws and the design of control system architecture, which has important engineering significance.

Soil quality is a very important indicator used to assess ecosystem restoration states in terms of vegetation recovery and establishment. Evaluating the soil quality of different vegetation restoration types in mountainous areas of Beijing and identifying their influencing factors would provide a scientific basis and be helpful for vegetation restoration in the future. Six vegetation types (or communities), including Platycladus orientalis (L.) Franco pure forest (POP), Pinus tabulaeformis Carr. pure forest (PTP), Platycladus orientalis–Pinus tabulaeformis mixed forest (PPM), Platycladus orientalis coniferous and broadleaved mixed forest (POCB), Pinus tabulaeformis coniferous and broadleaved mixed forest (PTCB), deciduous broadleaved mixed forest (DBMF), and one area of non-afforested land (NF), with similar stand conditions were selected and fourteen factors of soil physical and chemical characteristics were measured and used to establish a total data set (TDS), while a minimum data set (MDS) was obtained by using the principal component analysis (PCA) and Pearson correlation analysis methods. Two scoring methods, linear (L) and non-linear (NL), were used to calculate the soil quality index (SQI), and the key factors influencing soil quality by vegetation were identified by a general linear model (GLM), PCA, and correlation analysis. The results showed that: (1) The screened MDS indicators which showed good relationships with the SQIs in the study areas were total nitrogen (TN), sand content, total potassium (TK), pH, and available water capacity (AWC). The SQI–NLM method has better applicability. (2) The contribution rates of vegetation to different soil factors accounted for 28.644% (TN), 21.398% (sand content), 24.551% (TK), 16.075% (pH), and 9.332% (AWC). (3) TN showed a positive relationship with all vegetation types; the content of TN in PTCB and DBMF was obviously larger than in the other types in the 0–10 cm layer; PPM, PTCB, and POCB affected the sand content, which showed negative correlativity; and DBMF showed positive correlativity with AWC. The mechanism of how different species affect TN, sand content, and AWC should be focused on and taken into consideration in further studies.

Microwave medical sensing and imaging (MMSI) is a highly active research field. In MMSI, electromagnetic inverse scattering (EIS) is a commonly used technique that infers the internal characteristics of the diseased area by measuring the scattered field. It is worth noting that the image formed by EIS often exhibits the super-resolution phenomenon, which has attracted much research interest over the past decade. A classical perspective is that multiple scattering leads to super-resolution, but this is subject to debate. This paper aims to analyze the super-resolution behavior for Born-iterative-type algorithms for the following three aspects. Firstly, the resolution defined by the traditional Rayleigh criterion can only be applied to point scatterers. It does not suit general scatterers. By using the Sparrow criterion and the generalized spread function, the super-resolution condition can be derived for general scatterers even under the Born approximation (BA) condition. Secondly, an iterative algorithm results in larger coefficients in the high-frequency regime of the optical transfer function compared to non-iterative BA. Due to the anti-apodization effect, the spread function of the iterative method becomes steeper, which leads to a better resolution following the definition of the Sparrow criterion mentioned above. Thirdly, the solution from the previous iteration, as the prior knowledge for the next iteration, will cause changes in the total field, which provides additional information outside the Ewald sphere and thereby gives rise to super-resolution. Comprehensive numerical examples are used to verify these viewpoints.

With the rapid development of the internet of things (IoT), hundreds of millions of IoT devices, such as smart home appliances, intelligent-connected vehicles, and wearable devices, have been connected to the network. The open nature of IoT makes it vulnerable to cybersecurity threats. Traditional cryptography-based encryption methods are not suitable for IoT due to their complexity and high communication overhead requirements. By contrast, RF-fingerprint-based recognition is promising because it is rooted in the inherent non-reproducible hardware defects of the transmitter. However, it still faces the challenges of low inter-class variation and large intra-class variation among RF fingerprints. Inspired by fine-grained recognition in computer vision, we propose a fine-grained RF fingerprint recognition network (FGRFNet) in this article. The network consists of a top-down feature pathway hierarchy to generate pyramidal features, attention modules to locate discriminative regions, and a fusion module to adaptively integrate features from different scales. Experiments demonstrate that the proposed FGRFNet achieves recognition accuracies of 89.8% on 100 ADS-B devices, 99.5% on 54 Zigbee devices, and 83.0% on 25 LoRa devices.

Abstract To suppress the charge accumulation on the spacer surface in direct current (DC) gas insulated transmission line (GIL) is an important and emergent issue for the development of a clean, safe and economic smart grid. A design method of the DC spacer is proposed, and a spacer prototype is prepared and evaluated both by simulation and type test. The DC withstand voltage test and polarity reversal test are performed using the new DC spacer compared with a commercialised 220 kV AC spacer. The simulation results indicate that the surface electric field and surface charge of the DC spacer are lower than those of the alternating current (AC) spacer under DC voltage. The test results verify that the surface flashover voltage of this DC spacer is higher than that of the AC spacer. The potential feasibility of the spacer design for HVDC is discussed. It is hoped that the content of this paper can bring new ideas in the development of HVDC gas insulated equipment.

Abstract Background To investigate the mechanisms of low back pain triggered by the five-repetition sit-to-stand test (5R-STS test) in degenerative lumbar spondylolisthesis (DLS) from radiographic perspective, as well as to determine the most useful diagnostic modalities in the evaluation of segmental instability. Methods We retrospectively performed a study of 78 patients (23 men and 55 women) with symptomatic DLS at L4/5 in our institution between April 2020 and December 2021. Each patient was assessed by using the 5R-STS test and received a series of radiographs including the upright standing, normal sitting, standing flexion–extension radiographs, and supine sagittal MR images. Enrolled patients were divided into two groups based on the 5R-STS test score: severe group and mild group. Translational and angular motion was determined by comparing normal sitting radiograph (N) with upright standing radiograph (U) (Combined, NU), flexion/extension radiographs (FE) as well as normal sitting radiograph (N) with a supine sagittal MR image (sMR) (Combined, N-sMR). Results Overall, 78 patients were enrolled, and there were 31(39.7%) patients in group S and 47(60.3%) patients in group M, with an average age of 60.7 ± 8.4 years. The normal sitting radiograph demonstrated the maximum slip percentage (SP) and the highest kyphotic angle both in group S and group M. Compared with group M, group S revealed significantly higher SP in the normal sitting position (24.1 vs 19.6; p = 0.002). The lumbar slip angular in group S with a sitting position was significantly higher than that in group M (-5.2 vs -1.3; p

Abstract. Background:. During hepatitis B virus (HBV) infection, virus-infected hepatocytes directly cross-present viral antigens and regulate T cell response within the liver microenvironment. However, little is known regarding the regulatory pathways involved in viral antigen presentation in HBV-infected hepatocytes. This study investigated the underlying mechanism of antigen assembly and the HBV antigen-presenting function of major histocompatibility complex (MHC) class I molecules using heat shock protein gp96. Methods:. First, western blotting, flow cytometry, co-immunoprecipitation, GST pull-down, and confocal microscopic assays were performed to determine whether endogenous gp96 affects MHC-I levels via an antigen presentation pathway. Second, the B3Z assay and an AAV/HBV-infected hepatocyte-specific gp96-deficient mouse model were used to determine whether gp96 knockout functionally impaired peptide cross-presentation and produced a weakened antiviral cytotoxic T cell (CTL) response both in vivo and in vitro. Finally, confocal microscopic analysis and the B3Z assay were employed to show that exogenous gp96-associated peptide was present in MHC-I molecules via the endoplasmic reticulum (ER)-Golgi secretory pathway. Results:. Compared with the control, gp96 knockdown significantly reduced the cell surface levels of MHC-I by approximately 75% (P

A small population of Euonymus aquifolium (Celastraceae) with flowering plants was discovered more than 100 kilometers away from its type locality. The incomplete original description of this species is supplemented here with floral materials since it is known from only two gatherings of fruiting specimens. Its 5-merous flowers and two ovules per locule support its position in Euonymus, and this inference is further reinforced by phylogenetic analysis based on the nuclear internal transcribed spacer (ITS) of rDNA. The specific epithet has long been treated as “aquifolius” to agree with the generic gender of Euonymus. But after examination of the protologues of this and other related species described simultaneously by the same authors, as well as their handwritten annotations attached on the type specimens, we conclude that the epithet aquifolium was used as a noun and it should be retained unchanged. Despite this newly discovered population some 100 kilometers away from its type locality, this species is still assessed as Critical Endangered (CR) according to the IUCN Red List Categories and Criteria.

Abstract Exosome-mediated delivery of circular RNAs (circRNAs) is implicated in cancer progression. However, the role of exosomal circRNAs in the chemotherapy resistance of tumours remains poorly understood. Here we identified a novel circRNA, circWDR62. It was found that circWDR62 expression was upregulated in TMZ-resistant glioma cells and TMZ-resistant glioma cell-derived exosomes compared with their controls by using high-throughput microarray analysis and quantitative real-time polymerase chain reaction, and high circWDR62 expression was associated with poor prognosis of glioma. Functionally, downregulation of circWDR62 expression could significantly inhibit the TMZ resistance and malignant progression of glioma. Further mechanistic studies showed that circWDR62 plays a role by sponging miR-370-3p as a competing endogenous RNA. Rescue experiments confirmed that MGMT is the downstream target of the circWDR62/miR-370-3p axis in glioma. In addition, circWDR62 could be transported between TMZ-resistant and TMZ-sensitive glioma cells via exosomes. Exosomal circWDR62 from TMZ-resistant cells conferred TMZ resistance in recipient sensitive cells while also enhancing the proliferation, migration and invasion of these cells. A series of clinical and in vivo trials corroborated that exosomal circWDR62 could promote TMZ chemoresistance and malignant progression of glioma. Our results demonstrate for the first time that exosome-mediated delivery of circWDR62 can promote TMZ resistance and malignant progression via targeting of the miR-370-3p/MGMT axis in vitro and in vivo in glioma, providing a new therapeutic strategy. Moreover, exosomal circWDR62 in human serum may serve as a promising therapeutic target and prognostic marker for glioma therapy.

Abstract Pyroptosis and related gasdermin family proteins play an important role in the tumorigenesis of colorectal cancer (CRC). However, the prognostic roles of pyroptosis-related genes (PRGs) and their relation to infiltrates of immune cells in the pathogenesis of CRC remain unclear. Using this study, we set up a prognostic gene pattern on the basis of 13 PRGs (AIM2, CASP1, CASP5, CASP6, CASP8, CASP9, ELANE, GPX4, GSDMD, NLRP7, NOD2, PJVK, and PRKACA) for CRC patients. A comprehensive bioinformatics analysis based on these genes was then performed. With the good AUC prediction value of the ROC curves, the group with high hazard first had a poorer survival prognosis than the group with low hazard. Second, we found that PRGs were significantly related to inflammation-associated genes and immune-associated genes in CRC. Then, we identified a correlation of PRGs with immune infiltrations in CRC. For instance, the abundances of resting NK cells resting and neutrophils were higher in the low hazard group than in the high hazard group. Overall, this work indicated that PRGs contributed to generate heterogeneity of the tumor microenvironment (TME) in CRC. This prognostic PRG model may provide a starting point for the early diagnosis and medication use of CRC.

Abstract Corneal allograft rejection can be seen in some patients after corneal transplantation. The present study intends to investigate whether JAK2 gene knockout affects corneal allograft rejection through regulation of dendritic cells (DCs)-induced T cell immune tolerance. In order to identify the target gene related to corneal allograft rejection, high-throughput mRNA sequencing and bioinformatics analysis were performed. JAK2 knockout mice were constructed and subjected to corneal allograft transplantation. The incidence of immune rejection was observed, the percentage of CD4+ T cells was detected, and the expression of Th1 cytokine interferon γ (IFN-γ) was determined. Flow cytometry and ELISA were performed to analyze the effects of JAK2 gene knockout on bone marrow-derived DCs (BMDCs). JAK2 was the target gene related to corneal allograft rejection. JAK2 gene knockout contributed to significantly prolonged survival time of corneal grafts in mice and inhibited corneal allograft rejection. The in vitro cell experiment further confirmed that JAK2 gene knockout contributed to the inactivation of CD4+ T cells and induced IFN-γ expression, accompanied by inhibition of DC immune function, development, maturation, and secretion of inflammatory cytokines. Collectively, JAK2 gene knockout inactivates CD4+ T cells to decrease IFN-γ expression, as well as inhibits DC development, maturation, and secretion of inflammatory cytokines, thereby reducing corneal allograft rejection.

Abstract We study damping signatures at the Jiangmen Underground Neutrino Observatory (JUNO), a medium-baseline reactor neutrino oscillation experiment. These damping signatures are motivated by various new physics models, including quantum decoherence, ν 3 decay, neutrino absorption, and wave packet decoherence. The phenomenological effects of these models can be characterized by exponential damping factors at the probability level. We assess how well JUNO can constrain these damping parameters and how to disentangle these different damping signatures at JUNO. Compared to current experimental limits, JUNO can significantly improve the limits on τ 3/m 3 in the ν 3 decay model, the width of the neutrino wave packet σ x , and the intrinsic relative dispersion of neutrino momentum σ rel.

To date, there is no clinical scoring system or laboratory indicator that can rule out cerebral venous thrombosis (CVT) or provide diagnostic proof for evaluating post-treatment thrombosis recanalization during follow-up. We therefore explored an imaging method for quantitative assessment of CVT and assessed thrombotic changes during follow-up. A patient presented with severe posterior occipital distension extending to the top of the forehead and an elevated plasma D-dimer (DD2) level. Computed tomography and pre-contrast-enhanced magnetic resonance imaging revealed only a small amount of cerebral hemorrhage. Three-dimensional (3D) T1-weighted (T1W) BrainVIEW pre-contrast-enhanced magnetic resonance scanning showed subacute thrombosis in the venous sinus, and the post-contrast-enhanced scan combined with volume rendering reconstruction showed cerebral thrombosis of the venous sinus and allowed for measurement of the thrombus volume. On days 30 and 60 of post-treatment follow-up, post-contrast-enhanced scans showed progressive reduction of the thrombus volume as well as recanalization and fibrotic flow voids in the chronic thrombosis. 3D T1W BrainVIEW was helpful to observe the size of the thrombi and the situation of venous sinus recanalization during the follow-up after clinical treatment of CVT. This technique can reflect the imaging manifestations of CVT throughout the whole process to guide clinical treatment decisions.

BackgroundCircadian rhythm plays an essential role in various physiological and pathological processes related to cognitive function. The rest-activity rhythm (RAR) is one of the most prominent outputs of the circadian system. However, little is known about the relationships between RAR and different domains of cognitive function in older adults. The purpose of this study was to examine the relationships between RAR and various fields of cognitive function in older Americans.MethodsThis study included a total of 2090 older adults ≥ 60 years old from the National Health and Nutrition Examination Survey (NHANES) in 2011-2014. RAR parameters were derived from accelerometer recordings. Cognitive function was assessed using the word learning subtest developed by the Consortium to Establish a Registry for Alzheimer’s disease (CERAD W-L), the Animal Fluency Test (AFT) and the Digital Symbol Substitution Test (DSST). Linear regression was used to determine the relationships between RAR parameters (IS, IV, RA, L5, M10) and cognitive function scores (CERAD W-L, AFT, DSST).ResultsAfter adjusting for potential confounders, lower IS and M10 were associated with lower CERAD W-L scores (P=0.033 and P=0.002, respectively). Weaker RA and higher L5 were associated with lower AFT scores (P

The cutting hills to back ditches (CHBD) project has been widely implemented since urbanization in hilly areas is steadily rising. The stability of the high-filled slope and the problem of foundation settlement deformation has become one of the vital issues for safe construction. This paper focused on the deformation evolution law and stability assessment of the high-filled deposit slope composed of the soil-rock mixture (S-RM) in the CHBD project, in Shiyan City, Hubei Province as examples. First, large-scale direct shear tests of S-RM with different rock block proportions (RBPs) under different various normal stresses were carried out, and its mechanical properties were analyzed. Next, the finite element method was used to simulate the processes of the step-by-step filling, and the deformation evolution law was analyzed. Then, the limited equilibrium method (LEM) was used to obtain the potential sliding surfaces and the corresponding safety factors of the high-filled slope, and the safety of the construction was assessed. Finally, automated monitoring of the step-by-step settlement and deep soil deformation was computerized for the typical locations, and the long-term stability of the high-filled slope was studied. The results demonstrate that the first layer of backfill in the F area contains the largest incremental settlement displacement in the y-direction, whereas the value in the G area occurs at the site of the fill layer close to the slope surface at each filling timestep. The displacement response value steadily declines with the increasing filling depth and horizontal displacement, presenting a clear spatial influence range, with the site of maximum incremental displacement as the center. After filling, the safety factors of the potential sliding surface in the F and G areas are 2.531 and 1.118, respectively, and the slope is in a stable state. The monitoring data show that the deformation mostly takes place within 10 m of the surface. The study’s findings are thought to offer technical and practical knowledge for the slope risks.

ObjectiveTo explore the shared gene signatures and potential molecular mechanisms of polyarticular juvenile idiopathic arthritis (pJIA) and autoimmune uveitis (AU).MethodThe microarray data of pJIA and AU from the Gene Expression Omnibus (GEO) database were downloaded and analyzed. The GEO2R tool was used to identify the shared differentially expressed genes (DEGs) and genes of extracellular proteins were identified among them. Then, weighted gene co-expression network analysis (WGCNA) was used to identify the shared immune-related genes (IRGs) related to pJIA and AU. Moreover, the shared transcription factors (TFs) and microRNAs (miRNAs) in pJIA and AU were acquired by comparing data from HumanTFDB, hTFtarget, GTRD, HMDD, and miRTarBase. Finally, Metascape and g: Profiler were used to carry out function enrichment analyses of previously identified gene sets.ResultsWe found 40 up-regulated and 15 down-regulated shared DEGs via GEO2R. Then 24 shared IRGs in positivity-related modules, and 18 shared IRGs in negatively-related modules were found after WGCNA. After that, 3 shared TFs (ARID1A, SMARCC2, SON) were screened. And the constructed TFs-shared DEGs network indicates a central role of ARID1A. Furthermore, hsa-miR-146 was found important in both diseases. The gene sets enrichment analyses suggested up-regulated shared DEGs, TFs targeted shared DEGs, and IRGs positivity-correlated with both diseases mainly enriched in neutrophil degranulation process, IL-4, IL-13, and cytokine signaling pathways. The IRGs negatively correlated with pJIA and AU mainly influence functions of the natural killer cell, cytotoxicity, and glomerular mesangial cell proliferation. The down-regulated shared DEGs and TFs targeted shared DEGs did not show particular functional enrichment.ConclusionOur study fully demonstrated the flexibility and complexity of the immune system disorders involved in pJIA and AU. Neutrophil degranulation may be considered the shared pathogenic mechanism, and the roles of ARID1A and MiR-146a are worthy of further in-depth study. Other than that, the importance of periodic inspection of kidney function is also noteworthy.

Selenium plays a vital role in cancer prevention, antioxidation, and the growth of humans and other vertebrates. Excessive selenium can cause liver injury and metabolic disorders, which can lead to hepatic disease, but few studies have shown the effects of excessive selenium on liver development and its mechanism in zebrafish embryos. In this study, liver development and glucolipid metabolism were investigated in selenium-stressed zebrafish embryos. Under selenium treatment, transgenic fabp10a-eGFP zebrafish embryos showed reduced liver size, and wild-type zebrafish embryos exhibited steatosis and altered lipid metabolism-related indexes and glucose metabolism-related enzyme activities. In addition, selenium-stressed embryos exhibited damaged mitochondria and inhibited autophagy in the liver. An autophagy inducer (rapamycin) alleviated selenium-induced liver injury and restored the expression of some genes related to liver development and glucolipid metabolism. In summary, our research evaluated liver developmental toxicity and metabolic disorders under selenium stress, and confirmed that autophagy and oxidative stress might involve in the selenium-induced hepatic defects.

We studied the work function of cesium deposition and co-deposition with the electronegative element on the plasma grid (PG) using the first-principles calculations. The impurity particles may exist in the background plasma and vacuum chamber wall, and the work function of the PG will be affected. The results indicate that the minimum work functions of pure cesium deposition on Mo (110), W (110), and Mo (112) are reached at a partial monolayer. They are 1.66 eV (σ = 0.56 θ), 1.69 eV (σ = 0.75 θ), and 1.75 eV (σ = 0.88 θ), respectively. An appropriate co-deposition model consisting of cesium with electronegative elements can further decrease the work function. The coverage of cesium and electronegative elements are both 0.34 θ in all the co-deposition models. The F-Cs co-deposition model where the Cs atom and F atom are aligned along the surface normal obtains the lowest work function. They are 1.31 eV for F-Cs on Mo (110), and 1.23 eV for F-Cs on W (110), respectively. The change in work function is linearly related to the change in dipole moment density with a slope of −167.03 VÅ. For pure cesium deposition, two factors control the change in dipole-moment density, one is the electron transfer between adsorbates and the substrate, and another one is the restructuring of surface atoms. There are two additional factors for the co-deposition model. One is the intrinsic dipole moment of the double layer, the other is the angle between the intrinsic dipole moment and the surface. The latter two factors play important roles in increasing the total dipole moment.

Rett syndrome is a progressive neurodevelopmental disorder that lacks effective treatments. Although deep-brain stimulation can alleviate some symptoms in Rett model mice, this interventional manipulation requires deliberate surgical operations. Here, we report that electro-acupuncture stimulation (EAS) can ameliorate symptoms of an Mecp2-knockout rat model of Rett syndrome from the remote acupoints Baihui (GV 20), Yongquan (KI 1), and Shenmen (HT 7). We find that EAS not only prolongs the survival time of Rett rats, but also improves their behavior ability, including locomotion, motor coordination, and social interaction. Neural activation was observed in the substantia nigra of the midbrain, corpus striatum, and cerebral cortex of wild-type and Rett model rats, as reflected by the increased expression of the c-Fos protein. Hence, EAS provides a potential promising therapeutic tool for treating neurodevelopmental diseases.

In this paper, we consider the robust $ H_{\infty} $ state estimation (SE) problem for a class of discrete time-varying uncertain neural networks (DTVUNNs) with uniform quantization and time-delay under variance constraints. In order to reflect the actual situation for the dynamic system, the constant time-delay is considered. In addition, the measurement output is first quantized by a uniform quantizer and then transmitted through a communication channel. The main purpose is to design a time-varying finite-horizon state estimator such that, for both the uniform quantization and time-delay, some sufficient criteria are obtained for the estimation error (EE) system to satisfy the error variance boundedness and the $ H_{\infty} $ performance constraint. With the help of stochastic analysis technique, a new $ H_{\infty} $ SE algorithm without resorting the augmentation method is proposed for DTVUNNs with uniform quantization. Finally, a simulation example is given to illustrate the feasibility and validity of the proposed variance-constrained robust $ H_{\infty} $ SE method.

Abstract Background Crohn’s disease (CD) is a chronic disease that may have an adverse impact on health-related quality of life (HRQoL). This study aimed to describe the HRQoL of CD patients and assess correlating factors using the EQ-5D-5L in China. Methods We recruited CD patients at Shanghai Renji Hospital from October 2018 to May 2019. The data collected included demographic and clinical information, medical expenditures, and EQ-5D-5L questionnaire responses. The chi-square test or Fisher’s exact test was applied to analyse the proportion of patients in subgroups at each level. After the selection of correlating variables by univariate analysis, multivariate regression analyses were used to explore the correlating factors of HRQoL in CD patients. Results A total of 202 CD inpatients with a mean disease duration of 3.3 years were enrolled in the study. A total of 71.8% of patients were males, and 49.5% of patients were aged between 30 and 49 years. The average EQ-5D-5L utility score was 0.85, with a standard deviation (SD) of 0.12. Males, ileum lesions, remission status, and lower expenditure predicted higher EQ-5D-5L scores. In each EQ-5D-5L dimension, the proportion of patients differed significantly by gender, disease activity and location subgroup. In the multivariate regression models, being in an active CD state and using antibiotics had significantly adverse impacts on HRQoL (p

ABSTRACTBased on externalities in the allocation of interprovincial resources, we examine how geographic location affects firms’ access to resources and thus their information disclosure and stock price crash risk. The results show that border firms have a higher stock price crash risk than non-border firms. Mechanism tests find that border firms have lower available credit, higher financing costs, smaller fiscal subsidies, higher accrual earnings management, lower accounting conservatism, and a more positive tone in the management discussion and analysis section of the annual report. This indicates that resource shortages and aggressive information disclosure are important drivers of their higher stock price crash risk. Additional tests find no border effect in the borders of integrated areas or borders of areas adjacent to municipalities. Accelerating the digital transformation of the government and the information infrastructure construction, and strengthening external governance can partially alleviate the stock price crash risk of border firms.

Abstract Over the last decade, oncolytic virus (OV) therapy has shown its promising potential in tumor treatment. The fact that not every patient can benefit from it highlights the importance for defining biomarkers that help predict patients’ responses. As particular self-amplifying biotherapeutics, the anti-tumor effects of OVs are highly dependent on the host factors for viral infection and replication. By using weighted gene co-expression network analysis (WGCNA), we found matrix remodeling associated 8 (MXRA8) is positively correlated with the oncolysis induced by oncolytic virus M1 (OVM). Consistently, MXRA8 promotes the oncolytic efficacy of OVM in vitro and in vivo. Moreover, the interaction of MXRA8 and OVM studied by single-particle cryo-electron microscopy (cryo-EM) showed that MXRA8 directly binds to this virus. Therefore, MXRA8 acts as the entry receptor of OVM. Pan-cancer analysis showed that MXRA8 is abundant in most solid tumors and is highly expressed in tumor tissues compared with adjacent normal ones. Further study in cancer cell lines and patient-derived tumor tissues revealed that the tumor selectivity of OVM is predominantly determined by a combinational effect of the cell membrane receptor MXRA8 and the intracellular factor, zinc-finger antiviral protein (ZAP). Taken together, our study may provide a novel dual-biomarker for precision medicine in OVM therapy.

Abstract Advanced differentiated thyroid cancer cells are subjected to extreme nutritional starvation which contributes to develop resistance to treatments; however, the underlying mechanism remains unclear. Cells were subjected to serum deprivation by culture in medium containing 0.5% fetal bovine serum. A CCK8 assay, cell death Detection ELISAPLUS kit, and PI staining were conducted to determine cell viability, cell apoptosis, and cell cycle, respectively. NADPH oxidase 4 (NOX4) knockdown–stable cell lines were generated by lentivirus-mediated shRNA knockdown in BCPAP cells and TPC-1 cells. Etoposide and doxorubicin, two chemotherapeutic drugs, as well as lenvatinib were utilized to determine the effect of NOX4 on drug resistance. Lenvatinib-resistant BCPAP cells (LRBCs) were established to confirm this effect. The underlining mechanisms of NOX4 under starvation were explored using western blot. Finally, GLX351322, an inhibitor targeting NOX4, was used to inhibit NOX4-derived ROS in vitro and detect its effect on drug resistance of tumor cells in vivo. NOX4 is overexpressed under serum deprivation in BCPAP or TPC-1 cells. NOX4 knockdown impairs cell viability, increases cell apoptosis, extends G1 phase during cell cycle and modulates the level of energy-associated metabolites in starved cells. When the starved cells or LRBCs are treated with chemotherapeutic drugs or Lenvatinib, NOX4 knockdown inhibits cell viability and aggravates cell apoptosis depending on NOX4-derived ROS production. Mechanistically, starvation activates TGFβ1/SMAD3 signal, which mediates NOX4 upregulation. The upregulated NOX4 then triggers ERKs and PI3K/AKT pathway to influence cell apoptosis. GLX351322, a NOX4-derived ROS inhibitor, has an inhibitory effect on cell growth in vitro and the growth of BCPAP-derived even LRBCs-derived xenografts in vivo. These findings highlight NOX4 and NOX4-derived ROS as a potential therapeutic target in resistance to PTC.

Abstract The safety of automotive Adaptive Cruise Control (ACC) system is of great significance to prevent fatigue driving, improve driving comfort, reduce accident rate and promote the development of intelligent transportation and autonomous driving technology. However, the current safety analysis of ACC lacks consideration of the temporal dynamic property, so it is necessary to establish a set of safety analysis methods to consider the temporal characteristics. This paper proposes a new safety analysis method based on MBSA framework and introduces temporal features. Altarica3.0 is a high-level modeling language for safety analysis, and its basic mathematical form is Guardian Transformation System (GTS). In this paper, we outline an analysis approach that converts failure behavioral models (GTS) to temporal fault trees (TFTs), which can be analyzed using Pandora a recent technique for introducing temporal logic to fault trees. However, like classical fault tree analysis, TFT analysis requires a lot of manual effort, which makes it time consuming and expensive. In order to improve the safety of the system, the proposal extends Bayesian Networks with Pandora and results to dependability analysis with temporal relationships to provide more reliable basis for safety design. As a typical case study, the safety analysis method proposed in this paper is applied to the safety analysis of adaptive cruise system, and the results show the effectiveness of the proposed method. Furthermore, it also provides new technologies for the automation and intelligence of safety analysis for smart internet of vehicle.

Abstract. The California Chinese Medicine and Acupuncture Research Association, founded on March 25, 1974, is the first Chinese medicine organization registered with the state government in California. It was established after more than a year of arduous preparation and had 15 founding members. Over time, it evolved into the biggest organization of Chinese medicine and acupuncture in California. And in 2015, it became the American Association of Chinese Medicine and Acupuncture with more than 500 members.

Smart dielectric materials with bioinspired and autonomous functions are expected to be designed and fabricated for next-generation electrical insulation. Similar to organisms, such dielectrics with self-adaptive, self-reporting, and self-healing capabilities can be employed to avoid, diagnose, and repair electrical damage to prevent catastrophic failure and even a blackout. Compared with traditional dielectrics, the utilization of smart materials not only increases the stability and durability of power apparatus but also reduces the costs of production and manufacturing. In this review, researches on self-adaptive, self-reporting, and self-healing dielectrics in the field of electrical insulation, and illuminating studies on smart polymers with autonomous functions in other fields are both introduced. The principles, methods, mechanisms, applications, and challenges of these materials are also briefly presented.

Metastable austenitic stainless steels (ASSs) have excellent ductility but low strength, so that their usage as load-bearing components is significantly limited. Rolling is an effective method of increasing strength, whereas the effect of rolling temperature on microstructural evolution, the hydrogen embrittlement (HE) sensitivity and fracture mechanisms is still unclear. In present study, the effect of cold/warm rolling on detailed microstructural characteristics of 304 ASS was quantitatively investigated, and the corresponding HE sensitivity was evaluated via slow strain rate test (SSRT). The results suggest that cold-rolling led to high strength but poor plasticity and deteriorated HE sensitivity, while warm-rolled samples provided combination of high strength and ductility and also superior HE resistance. Compared with 18% α′-martensite in cold -rolled steel, warm-rolled specimens consisted of complete austenite, less twins and lower dislocation density，moreover, the favorable {112} ND and {110} ND textures replaced the harmful {001} ND texture. Based on in-situ EBSD observation during SSRT, the HE sensitivity was governed by the combined effect of pre-deformation microstructures and the dynamic microstructural evolution. Advanced method of time-of-flight secondary ion mass spectrometry was used to observe the distribution of hydrogen, and the hydrogen content of specimens was determined by the gas chromatograph thermal desorption analysis method. An exceedingly small amount of hydrogen entered the warm-rolled samples, while a large amount of hydrogen was trapped at grain boundaries of cold-rolled sample, leading to complete intergranular fracture. Therefore, warm rolling is an effective pathway for obtaining high combination of strength and ductility together with excellent HE sensitivity.

Ship classification using the synthetic aperture radar (SAR) images has a significant role in remote sensing applications. Aiming at the problems of excessive model parameters numbers and high energy consumption in the traditional deep learning methods for the SAR ship classification, this paper provides an energy-efficient SAR ship classification paradigm that combines spiking neural networks (SNNs) with Siamese network architecture, for the first time in the field of SAR ship classification, which is called the Siam-SpikingShipCLSNet. It combines the advantage of SNNs in energy consumption and the advantage of the idea in performances that use the Siamese neuron network to fuse the features from dual-polarized SAR images. Additionally, we migrated the feature fusion strategy from CNN-based Siamese neural networks to the SNN domain and analyzed the effects of various spiking feature fusion methods on the Siamese SNN. Finally, an end-to-end error backpropagation optimization method based on the surrogate gradient has been adopted to train this model. Experimental results tested on the OpenSARShip2.0 dataset have demonstrated the correctness and effectiveness of the proposed SAR ship classification strategy, which has the advantages of the higher accuracy, fewer parameters and lower energy consumption compared with the mainstream deep learning method of the SAR ship classification.

Using the temperature and seepage field-coupling module within COMSOL Multiphysics software, we examined freezing behavior and its evolving patterns in curved underground freezing pipes. This study employed transient states, with the Darcy’s law and porous-media heat-transfer options activated in the Physical Field Interface of the Physical Field and Variable Selection column. The models were created to establish numerical models of freezing reinforcement for both single and multiple pipes with various curvatures. These models were designed to simulate the evolving temperature and seepage fields of soil under diverse freezing conditions. Subsequently, this research utilized the models to simulate the freezing and consolidation conditions of a shallowly buried tunnel within the context of shallow tunnel conditions. The study reveals that after freezing a single pipe using water flow, the change in thickness of the frozen wall in curved pipes is notably smaller than that in straight pipes. This difference is particularly pronounced in the upstream section. Specifically, at a distance of −2000 mm from the main surface, the change in thickness of the frozen wall in straight pipes exceeds that in s = 7 curved pipes by approximately 350 mm. The smaller the long arc ratio s, the greater the arc of the freezing tube and the better the water-blocking effect. In the multi-pipe freezing model, the s = 7 curved pipes exhibit a frozen-wall thickness approximately 120 mm greater than that of straight pipes at a distance of −2000 mm from the main surface. Under the condition of a shallow buried concealed excavation with surging water, a pipe with a long arc ratio s = 7 arc freezing at 46 d attains a permafrost curtain thickness that is equivalent to that achieved by the straight pipe freezing at 58 d. This reduction in thickness shortens the working period by 12 days, resulting in a more efficient process. The successful application of the freezing method in the water-rich aquifer is expected to be a valuable reference for similar projects in the future.

Bridges have a special place in transportation infrastructures and road networks due to their direct relationship with other places. These structures have the purpose of maintaining the traffic loads of the highway, crossing any obstacle, and performing effective communication between two destinations. Costs associated with bridge maintenance continue to be expensive due to their widespread use and stringent inspection requirements. Many researchers have been working on methods to use machine-learning (ML) techniques to forecast specific situations rather than physically checking bridges as part of the maintenance process in recent years. The practical value of the models has, however, been severely constrained by issues such relatively poor model evaluation results, unstable model performances, and the ambiguous application of established models in real-world scenarios. This work showed a thorough method of bridge condition prediction model building from feature engineering to model evaluation, along with a clear procedure of applying the produced model to actual usage, using data from the United States National Bridge Inventory (NBI) and the Adaboost algorithm. Multiple ML model assessment metrics’ findings revealed that the given model outperformed the majority of earlier studies in terms of values and stability. The case study demonstrated that there is a 30% reduction in the number of bridges that need to be inspected. This study serves as a crucial resource for the practical application of ML approaches in the forecast of the status of civil infrastructure. Additionally, it shows that boosted ML models may be a superior option as modeling algorithms advance. To explore the main influencing aspects of bridge conditions, a predictor importance analysis is also offered.

In the field of shield tunnels, the occurrence of uneven longitudinal settlement in segment linings has presented persistent challenges, including heightened risks of localized damage and water leakage. While the adoption of a secondary lining has been proposed as a viable solution to these issues, the question of how to select an appropriate construction time for the secondary lining, one that enables it to fully harness its load-bearing capacity while optimizing the tunnel’s overall stress and deformation characteristics, continues to be a pressing concern. To address this issue, this study established a three-dimensional longitudinal refined numerical model of double-layer-lined shield tunnel. In addition, the deformation degree of the segment lining was used as a time indicator to define the construction time for the secondary lining. Subsequently, an analysis of the impact of the construction time of the secondary lining on the longitudinal mechanical properties of the double-layer-lined shield tunnel is conducted through an assessment of tunnel longitudinal deformation and structural stress. The research findings indicated that the construction of the secondary lining improved the longitudinal deformation resistance of shield tunnels. Simultaneously, it led to a significant increase in the longitudinal shear forces within the segment lining and a notable reduction in longitudinal bending moments. Moreover, the construction time of the secondary lining played a pivotal role in these alterations. Considering the longitudinal force situations and load-bearing characteristics of the double-layer lining structure, it was determined that the optimal construction time for the secondary lining fell within the range of 20% to 40% of the total construction duration. In this scenario, the deformation and internal forces within the segment lining remained within permissible limits. Additionally, both the segment lining and the secondary lining were able to fully utilize their load-bearing capacities, ensuring the economic and safety aspects of the tunnel.

Due to the outstanding penetrating detection performance of low-frequency electromagnetic waves, through-wall radar (TWR) has gained widespread applications in various fields, including public safety, counterterrorism operations, and disaster rescue. TWR is required to accomplish various tasks, such as people detection, people counting, and positioning in practical applications. However, most current research primarily focuses on one or two tasks. In this paper, we propose a multitask network that can simultaneously realize people counting, action recognition, and localization. We take the range–time–Doppler (RTD) spectra obtained from one-dimensional (1D) radar signals as datasets and convert the information related to the number, motion, and location of people into confidence matrices as labels. The convolutional layers and novel attention modules automatically extract deep features from the data and output the number, motion category, and localization results of people. We define the total loss function as the sum of individual task loss functions. Through the loss function, we transform the positioning problem into a multilabel classification problem, where a certain position in the distance confidence matrix represents a certain label. On the test set consisting of 10,032 samples from through-wall scenarios with a 24 cm thick brick wall, the accuracy of people counting can reach 96.94%, and the accuracy of motion recognition is 96.03%, with an average distance error of 0.12 m.

Background and Objectives: Non-alcoholic steatohepatitis (NASH) is a significant risk factor for hepatocellular carcinoma (HCC) development. Timely treatment during the NASH stage is essential to minimize the possibility of disease progression to HCC. Cuproptosis is a newly identified form of cellular death that could impact the progression of various diseases and cancers. Materials and Methods: Transcriptome and single-cell sequencing datasets were utilized to investigate the role of cuproptosis-related genes (CRGs) in NASH progression to HCC. FDX1, LIPT1, and PDHP were identified as CRGs in NASH patients, and FDX1, DBT, GCSH, SLC31A1, and DLAT were identified as CRGs in patients with NASH progressing to HCC. FDX1 was found to play a significant role in both NASH patients and patients with NASH progressing to HCC. This study constructed cuproptosis-related clusters (CRCs) using the Nonnegative Matrix Factorization algorithm, and they were linked to fatty acid metabolism and the PPAR signaling pathway in both NASH CRCs and HCC CRCs. The Weighted Correlation Network Analysis algorithm identified CRP, CRC, TAT, CXCL10, and ACTA1 as highly relevant genes in NASH CRCs and HCC CRCs. The expression of FDX1 was validated in both mouse models and human NASH samples. Results: The investigation highlights FDX1 as a pivotal CRG in both NASH and NASH progression to HCC. The comprehensive characterization of CRGs sheds light on their potential biofunctional importance in the context of NASH and HCC. Our experimental results show that FDX1 expression was significantly increased in NASH patients. Conclusions: The present study identified key CRGs, revealing their potential impact on NASH and HCC. Meanwhile, targeting FDX1 may prevent the progression of NASH to HCC.

Due to the inherent characteristics of synthetic aperture radar (SAR) imaging, SAR ship features are not obvious and the category distribution is unbalanced, which makes the task of ship recognition in SAR images quite challenging. To address the above problems, a two-level feature-fusion ship recognition strategy combining the histogram of oriented gradients (HOG) features with the dual-polarized data in the SAR images is proposed. The proposed strategy comprehensively utilizes the features extracted by the HOG operator and the shallow and deep features extracted by the Siamese network in the dual-polarized SAR ship images, which can increase the amount of information for the model learning. First, the Siamese network is used to extract the shallow and deep features from the dual-polarized SAR images, and then the HOG feature of the dual-polarized SAR images is also extracted. Furthermore, the bilinear transformation layer is used for fusing the HOG features from dual-polarized SAR images, and the grouping bilinear pooling process is used for fusing the dual-polarized shallow feature and deep feature extracted by the Siamese network, respectively. Finally, the catenation operation is used for fusing the dual-polarized HOG features and dual-polarized shallow feature and deep feature, respectively, which are used for the recognition of the SAR ship targets. Experimental results tested on the OpenSARShip2.0 dataset demonstrate the correctness and effectiveness of the proposed strategy, which can effectively improve the recognition performance of the ship targets by fusing the different level features of the dual-polarized SAR images.

With the rapid development of autonomous driving and robotics applications in recent years, visual Simultaneous Localization and Mapping (SLAM) has become a hot research topic. The majority of visual SLAM systems relies on the assumption of scene rigidity, which may not always hold true in real applications. In dynamic environments, SLAM systems, without accounting for dynamic objects, will easily fail to estimate the camera pose. Some existing methods attempt to address this issue by simply excluding the dynamic features lying in moving objects. But this may lead to a shortage of features for tracking. To tackle this problem, we propose OTE-SLAM, an object tracking enhanced visual SLAM system, which not only tracks the camera motion, but also tracks the movement of dynamic objects. Furthermore, we perform joint optimization of both the camera pose and object 3D position, enabling a mutual benefit between visual SLAM and object tracking. The results of experiences demonstrate that the proposed approach improves the accuracy of the SLAM system in challenging dynamic environments. The improvements include a maximum reduction in both absolute trajectory error and relative trajectory error by 22% and 33%, respectively.

Abstract ZnO microvaristors/epoxy resin composite has drawn great attention from academia and industry for its adjustable non‐linear conductivity, high mechanical strength, and good ageing resistance. However, the sedimentation of ZnO microvaristors in epoxy resin during preparation is the key problem, which limits its application in engineering. In this study, a novel method of wet winding with polyester fibre cloth is proposed to prepare the ZnO microvaristors/epoxy resin composite. The anti‐settling effect of ZnO microvaristors in the composite is verified by scanning electron microscopy (SEM) and thermal gravimetric analysis (TGA). The microstructure shows that ZnO microvaristors distribute uniformly in the composite, and the content difference of ZnO microvaristors at the top and bottom part is only 0.4%. The composite shows typical non‐linear conductivity, and the threshold electric field and the non‐linear coefficient decrease with the content of ZnO microvaristors, while the conductivity in the insulating state shows an increasing trend. To verify the field grading effect of the composite with non‐linear conductivity (CNC), a finite element model of a needle‐plate electrode, simulating the condition of a conductive tip in a solid insulated system, is set up. CNC can adaptively grade the electric field, which reduces the surface electric field of the needle tip by 86.6% and the highest electric field in the system by 82.1%. This wet winding method solidifies the industrial application of CNC in high‐voltage power equipment.

How to prevent and control the leakage at shield tail during the replacement of shield tail brush is critical for shield tunnel construction. Herein, an annular freezing reinforcement method during the replacement of shield tail brush was proposed, and the optimal position for one annular freezing pipeline, if adopted, was analysed through numerical modelling. In addition, the development law of the temperature field of the annular freezing soil curtain was also studied. The results show that the drilling method is flexible for annular freezing reinforcement during the replacement of the shield tail brush. Besides, it also has little effect on the durability of segments and strong construction practicability, as well as good, safe and reliable reinforcement effect, particularly good water-stop effect. Specifically, the best pipeline position is 0.3 m over the shield tail, where the best freezing effect can be provided, satisfying the design requirements. The final soil temperature at the gap between the shield tails will rise about 9 ℃ if the radius of the annular freezing pipeline increases by 0.3 m. Moreover, the －1 ℃ isotherm reaches the shield tail gap after 6-day freezing at the optimal pipeline position, with the water sealed initially by the freezing soil curtain, and the －10 ℃ isotherm reaches the shield tail gap after 10-day freezing, so that the freezing effect of the freezing soil curtain is strengthened. Therefore, arranging an annular freezing pipeline at the optimal position can greatly improve the water sealing performance and safety, which could provide some reference for the development of related projects in the future.

A microbial starter culture is expected to improve the quality of traditional fermented fish products. Lactobacillus plantarum was selected for grass carp fermentation due to its high proteolytic activity. To investigate its effects on muscle proteolysis of dried fermented fish, the protein profile and microbial community were analysed by using proteomics and metabolomics. The myofibrillar protein and collagen profiles showed remarkable variation after processing, changes that were related to the development of flavour and texture in fish samples. The starter culture had a marked effect on the microbial composition. Macrococcus and Staphylococcus were the dominant genera, with a relative abundance of 24.79% and 12.53%, respectively. There were significant correlations (P

Recently, a series of collaborative representation (CR) methods have attracted much attention for hyperspectral images classification. In this article, two CR-based dynamic ensemble selection (DES) methods using multiview kernel collaborative subspace clustering (MVKCSC) and random subspace MVKCSC (RSMVKCSC) are proposed. In order to combine spectral and spatial information to construct a region of competence (RoC), the multiview learning strategy is used in the general DES method. Compared with traditional clustering methods, the MVC can more effectively utilize multifeature information. Moreover, a new method of constructing the Laplacian matrix using kernel CR coefficients is proposed for clustering based on subspace clustering and CR theory. This method is called MVKCSC, which can obtain the clustering results by using kernel CR self-representation coefficients. In addition, to increase the diversity of samples, the random subspace method (RSM) and MVKCSC are combined for RMVKCSC. Moreover, the algorithm can obtain better clustering results by constraining samples and features simultaneously. The effectiveness of the proposed methods is validated using three hyperspectral data sets with few samples. The experimental results show that both DES-MVKCSC and DES-RSMVKCSC outperform their single classifier counterparts. In particular, the proposed methods provide superior performance compared with the state-of-the-art DES methods.

Augmented Reality serious games have become an emerging solution to positively influence the learning experience for children born in the digital age. However, systematic and empirically tested design guidelines for AR serious games remain largely unexplored. In this study, we investigated the design guidelines by designing and developing four AR serious games with different mechanics inspired by the psychological needs within Self-determination Theory, following with four user studies respectively. In the first study, we explored the AR game concepts by conducting participatory design sessions. In the second study, we investigated how children react to different types of interactions and feedback mechanics in AR serious games with 32 participants. Then, we scrutinized the effect of social interactions in AR serious games on children with 24 participants. Lastly, we designed an AR game with four different versions, tested pathways to immerse children to explore and play in an AR fantasy world with 81 participants. Generally, this research explored the concepts, prototypes, and results of incorporating AR with serious games for children. We realized multiple AR prototypes inspired by SDT and generalized a set of design guidelines, which are intended to help future related designs in AR serious games.

Losing a loved one through death is known to be one of the most challenging life events. To help the bereaved and their therapists monitor and better understand the factors that contribute to Prolonged Grief Disorder (PGD), we co-designed and studied a web-based explainable AI screening system named “Grief Inquiries Following Tragedy (GIFT).” We used an initial iteration of the system to collect PGD-related data from 611 participants. Using this data, we developed a model that could be used to screen and explain the different factors contributing to PGD. Our results showed that a Random Forest model using Bereavement risk and outcome features performed best in detecting PGD (AUC=0.772), with features such as a negative intepretation of grief and the ability to integrate stressful life events contributing strongly to the model. Afterwards, five grief experts were asked to provide feedback on a mock-up of the results generated by the GIFT model, and discuss the potential value of the explanatory AI model in real-world PGD care. Overall, the grief experts were generally receptive towards using such a tool in a clinical setting and acknowledged the benefit of offering a personalized result to the users based on the explainable AI model. Our results also showed that, in addition to the explainability of the model, the grief experts also preferred a more “empathetic” and “actionable” AI system, especially, when designing for patient end-users.

Cross-domain polarimetric synthetic aperture radar interpretation is urgently needed, due to the rapid data growth and label scarcity. However, the class distribution shift problems hinder the reuse of labeled samples among cross-domain images. Most of the existing domain adaptations can only handle the cross-domain case of same categories between source and target domains, while the categories of the target domain are usually more abundant than those of the source domain. To improve the usability of labeled samples among cross-domain images, an unsupervised generalized zero-shot domain adaptation (uGZSDA) based on scattering component semantics (SCSs) is proposed. By using SCSs and limited labeled samples (seen categories) in the source domain, more land cover types (seen and unseen categories) in the unlabeled target domain can be inferred. First, a stacked autoencoder (SAE) extracts source/target-domain features, and SCSs of typical land covers are constructed by cross-domain databases and statistical scattering components. Second, combining SAE features and source-domain samples, the most likely seen class samples in the target domain are selected by probability sorting, and the SAE is retrained by obtained selected seen samples. Third, the unseen class samples in the target domain are inferred by the retrained SAE, classification probability, and semantic similarity. Finally, the selected seen and inferred unseen class samples in the target domain are used to further retrain the SAE, and the target domain is classified by the retrained SAE and the classifier. The proposed uGZSDA is verified among 16 cross-domain PolSAR datasets. Using SCS and two to three types of seen samples from the source domain, the accuracies of seven types of land covers in the unlabeled target domain can reach 76–83.96%.