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The corrosion of pre-passivated Cr10Mo1 steels in simulated concrete pore solution of saturated Ca(OH)2 induced by different corrosive ions were investigated, namely Cl−, SO2- 4, and combination of Cl− and SO2- 4. Electrochemical methods, Pourbaix analysis of Fe–Cr–H2O system and DFT calculation were adopted to characterize corrosion behavior and reveal underlying mechanism. Results showed that while sulfate may induce corrosion at higher threshold value, the scenario of chloride alone leads to lowest corrosion potential, linear polarization resistance and highest corrosion rate, and the presence of SO2- 4 ions mitigate corrosion risk under the coexistence condition of chloride and sulfate. A two-step reaction model of competitive adsorption-catalytic corrosion was proposed based on theoretical analysis and DFT calculation results.

Abstract Innovation is increasingly recognized as a linchpin for CSR transformation within organizations. Beyond mere compliance, businesses are embracing innovation as a strategic imperative to address societal challenges. Using panel-data analysis spanning from 2014 to 2023, this paper investigates the relationship between innovation strategies and Corporate Social Responsibility (CSR) performance, with a special emphasis on the moderating effect of Green Innovation (GI). We examine how panel data analysis shows, green innovation is found to be an important moderator that lessens the possible harm that China’s high-tech may cause to CSR. Results further shows that green innovations can positively moderate relationship between China’s high-tech and CSR. Further, we found several other key variables (state equity, innovation level, market value) to improve firm’s innovations and CSR performance. The findings of this study have important implications for practitioners to give sustainable innovation strategies top priority, and policymakers are advised to encourage ecologically friendly behaviour.

The passivation evolution of mild steels in simulated concrete pore solutions with varying pH were systematically investigated in present study. Based on electrochemical, time-of-flight secondary ion mass spectrometry, and ReaxFF molecular dynamics simulation, a plausible model with high logical coherence and theoretical soundness was proposed to elucidate the underlying passivation mechanism. The results depict that the steels within concrete pore solution with high pH facilitates quick and compact film formation, leading to superior passivation performance. Spontaneously-induced passive film of mild steel demonstrates a dual-layer structure composed of an inner layer rich in Fe(II) and an outer layer rich in Fe(III).

Abstract Background Expression quantitative trait loci (eQTL) studies aim to understand the influence of genetic variants on gene expression. The colocalization of eQTL mapping and GWAS strategy could help identify essential candidate genes and causal DNA variants vital to complex traits in human and many farm animals. However, eQTL mapping has not been conducted in ducks. It is desirable to know whether eQTLs within GWAS signals contributed to duck economic traits. Results In this study, we conducted an eQTL analysis using publicly available RNA sequencing data from 820 samples, focusing on liver, muscle, blood, adipose, ovary, spleen, and lung tissues. We identified 113,374 cis-eQTLs for 12,266 genes, a substantial fraction 39.1% of which were discovered in at least two tissues. The cis-eQTLs of blood were less conserved across tissues, while cis-eQTLs from any tissue exhibit a strong sharing pattern to liver tissue. Colocalization between cis-eQTLs and genome-wide association studies (GWAS) of 50 traits uncovered new associations between gene expression and potential loci influencing growth and carcass traits. SRSF4, GSS, and IGF2BP1 in liver, NDUFC2 in muscle, ELF3 in adipose, and RUNDC1 in blood could serve as the candidate genes for duck growth and carcass traits. Conclusions Our findings highlight substantial differences in genetic regulation of gene expression across duck primary tissues, shedding light on potential mechanisms through which candidate genes may impact growth and carcass traits. Furthermore, this availability of eQTL data offers a valuable resource for deciphering further genetic association signals that may arise from ongoing extensive endeavors aimed at enhancing duck production traits.

A reactive force field for the Fe/Cl system has been developed and the force field was applied to analyze the corrosion process of iron (Fe) in solutions containing chloride ions, aiming to uncover the mechanisms underlying chloride-induced corrosion and oxidation reactions on the Fe surface. Through reactive molecular dynamics simulations, it was found that the corrosion behavior of Fe(100) surface began with the enrichment of chloride ions on the surface, and then the dissolution of iron on the surface was induced under the action of chloride ions to form an effect similar to pitting corrosion, and at the same time, the surface of the iron substrate generated an iron oxide film similar to iron rust at the same time. As the simulation progressed, the thickness of the iron oxide film gradually increased. Concurrently, the corrosion state on the iron surface evolved from localized pitting to extensive corrosion, with the corroded area demonstrating a linear relationship with the progression of simulation time. These results can provide insights into the formation of oxide films and localized initiation of corrosion nucleation on Fe surfaces at the atomic level.

This study systematically investigated the influence of different blending ratios of recycled powder and slag powder on hydration heat evolution and mechanical properties. Various modern microscopic testing techniques were employed to quantitatively characterize hydration products and microstructures, revealing their hydration mechanisms. The results indicate that both recycled powder and slag powder can accelerate the early hydration rate. When recycled powder and slag powder are co-blended, their early hydration rate and cumulative heat release surpass those of specimens with single additions of recycled powder. Moreover, the mechanical properties in the later stage are superior to those of specimens with single additions of recycled powder. At 60d, the PRS70–1–2 in the multi doped recycled powder and slag powder system even exceeds that of the uni doped SL system, but is much higher than that of the uni doped RP system，the compressive strength of the multi doped recycled powder and slag powder system increased by 25.5 %, 37.1 % and 36.9 %, respectively, compared with that of the uni doped RP system. Specimens with single additions of recycled powder and slag powder have a relatively high proportion of harmful and very harmful pores. At 28d, the porosity of the multi doped recycled powder and slag powder system decreased by 19.2 %, 24.2 % and 14.8 %, respectively, compared with that of the uni doped RP system. However, when recycled powder and slag powder are co-blended, the proportion of harmful and very harmful pores decreases, while the proportion of less harmful and harmless pores increases. This leads to an overall reduction in porosity and an improvement in mechanical properties.

In this paper, the passivation evolution and mechanisms of a novel Cr10Mo steel in simulated concrete pore solutions with varying pH levels (12.4, 12.9, and 13.5) are investigated using electrochemical methods, Pourbaix analysis, and ReaxFF molecular dynamics (MD) simulations. The findings reveal that Cr10Mo steel undergoes spontaneous passivation in all simulated solutions, forming a bi-layered passivation film composed of inner Cr2O3 and outer Fe2O3 layers. However, lower pH values promote the formation of chromium oxides/hydroxides, resulting in thicker and more stable passivation films. Conversely, higher pH values diminish open circuit potential and linear polarization resistance, thereby compromising the corrosion resistance of passivated Cr10Mo steel. Experimental X-ray photoelectron spectroscopy observations and ReaxFF MD simulations corroborate this seemingly paradoxical phenomenon. The fundamental mechanism likely involves pH-sensitive selective generation of Cr(OH)3, which transforms into Cr2O3 or Cr2O42-.

This investigation employed reactive molecular dynamics (ReaxFF-MD) simulations to study nano scale passivation behavior of Fe-Cr alloys in highly alkaline environments. The impact of external electric field strength, temperature, and chromium content on the formation and development of the passive film was revealed, integrating kinetic and thermodynamic analyses to provide a comprehensive understanding. The findings indicate that the application of an electric field markedly accelerated the growth of the passive layer, with charge transfer and ion migration processes being directly modulated by the field. Additionally, variations in temperature induced staged changes in the passivation rate, thereby illuminating the thermodynamic effects on the rates of chemical reactions. Furthermore, increasing the chromium content resulted in a denser and more stable passive film. Chromium in the oxidation state of Cr3+ plays a pivotal role in enhancing the stability and density of the passive layer due to its more stable oxidative state.

Steel slag, as an industrial byproduct obtained from the steel manufacturing industry, may cause land occupation, resource waste, and environmental pollution. The application of steel slag as a material for soil reinforcement in road engineering is very popular due to its potential hydration activity. The unconfined compression strength, microstructure, and transport properties of loess soil with cement, lime and steel slag were investigated. The results show that the loess soil can be reinforced by cement, lime, and steel slag to varying degrees. The reinforcement mechanism of cement for loess soil is realized by pore filling by cement hydration products such as CH, C-S-H and AFt, and their unconfined compression strength is improved by reducing the porosity. The reinforcement mechanism of lime for loess soil is achieved by pore filling by hydration products such as CH and CaCO3, and their strength is improved by a refined pore structure where the porosity has not been significantly reduced. The reinforcement mechanism of steel slag for loess soil is a combined mechanism of cement and lime, including pore filling and refined pores. The pore structure of reinforced soil can be studied at different scales by the MIP, LF NMR, and X-CT test methods. The transport properties including diffusivity and permeability of reinforcing soil can be well explored by Avizo software based on the microstructure obtained from X-CT.

In China, steel slag as a solid waste caused land occupation and environmental pollution, and its utilization ratio is relatively low. To increase the utilization field and ratio of steel slag, hydration behavior and cementitious properties of three types of steel slag were investigated and compared based on test results from an early age to a long-term via multiple techniques. Experimental results suggested that steel slag showed a strong latent hydraulic activity at a later age, and the mechanical strength of steel slag paste specimens (w/b=0.3) could reach 15 MPa at 360 days. Cementitious properties of steel slag were primally depended on the hydration of calcium silicate (C3S and C2S), calcium aluminate (ferrite), glassy phase in steel slag, especially for calcium silicate. The sum amount of calcium silicate in used steel slag was approximately from 21% to 28%, and the amount of C2S was significantly greater than that of C3S. The hydration of C2S and glassy phase resulted in the continuous increase in bound water content of steel slag, and a certain content of C2S still existed in pastes at 360 days. The mechanical strength of steel slag pastes markedly increased at a later age due to more hydrates formed in the microstructure.

The undulating appearance of 3D-printed concrete (3DPC) is an essential feature that impacts the integrity and stability of the multilayer structure, yet the related evaluation parameters have rarely been proposed. This study proposed a quantitative evaluation and parameters through the on-site 3D scan technology to impel a direct and precise understanding of the surface quality of 3DPC, especially concrete with coarse aggregates. Firstly, 8-layer 3DPC walls are produced at four different printer printing rates and then 3D scanned. After point cloud correction, noise reduction, and 2D processing onto acquired points cloud, the evaluation parameters for evaluating 3DPC surface characteristics are defined and calculated. Results indicate that a higher 3D printer printing rate helps reduce surface fluctuation of 3DPC multilayer structures but disfavor the vertical flatness, of which the linear relationship between the parameters and the printing speed of the printer is explored and discussed. Recommendation of 3DPC straight wall structures controlled to surface defects ratio within 2% and slope within 0.2% is suggested. These conclusions provide precise external surface quality control and treatment basements that contribute to improving the practical application of 3DPC.

This research examined consumption-based carbon emission reduction by nuclear energy consumption and environmental tax while considering the context of trade globalization in the highest five emitter nations from 1990 to 2020. This study used various empirical methodologies, including preliminary analysis to check the stationarity and cointegration, the CS-ARDL for long-run analysis, CCEMG, AMG for robustness, and the D-H causality test for short-term pairwise causation. The results indicated that nuclear energy consumption, environmental tax, and trade globalization help to mitigate consumption-based carbon emissions while economic growth and population density boost carbon emissions. Furthermore, the results also found two-way casual connection exists between nuclear energy consumption, population density, and consumption-based carbon emissions. Thus, the results emphasize the need for government policies that encourage nuclear energy and environmental tax as a strategy to reduce carbon emissions and achieve and maintain environmental development.

ABSTRACT: Primary hepatocytes (PH) have been widely used in metabolic and disease-resistance mechanism research. However, hepatocyte isolation (HI) remains challenging in ducks. This study aimed to explore embryonic growth and the effect of embryonic age (EA) on the quantitative and functional characteristics of PH in ducks. For embryonic growth, the size and weight of the embryo and liver were determined from 6 to 28 EA (E6–E28, similar below). As EA increased, the corresponding size and weight grew significantly. Specifically, embryonic length varied from 12.5 mm to 133.0 mm, and liver width varied from 2.0 mm to 26.2 mm. Embryonic weight ranged from 0.259 g to 53.58 g, and liver weight ranged from 0.007 g to 1.765 g. Liver index initially decreased and then increased with a ratio ranging from 1.06 to 3.29%. For quantitative and functional characteristics, they were determined from E6 to E22, as there were no obvious liver features before E6 and few cells obtained after E22. The number of cells isolated in liver increased from E6 to E16 and then sharply decreased from E16 to E22. The viability remained relatively stable from E6 to E10 and then decreased from E12 to E22. The comprehensive intensity of hepatic glycogen was stronger at E8 and E14. Albumin expression increased markedly from E6 to E18 by qPCR, and the overall albumin expression was stronger at E8 and E14 by immunofluorescence assay. Hepatocyte purity exceeded 90% except for E20 and E22. During culture, cell clusters appeared after 24-h culture, which were identified as nonhepatocytes. The growth curve showed an initial increase in cell quantity followed by a decrease, another increase, and then remaining stable. In conclusion, EA had a significant effect on the quantitative and functional characteristics of PH, and the suitable EA for HI were E8 and E14. Considering better operability and quantity, E14 was the optimal EA, laying a solid foundation for further hepatocyte purification, nutrient metabolism, and disease-resistance mechanism explorations in ducks.

ABSTRACT: As the most prevalent pathogen of duck viral hepatitis (DVH), duck hepatitis A virus genotype 3 (DHAV-3) has caused huge economic losses to the duck industry in China. Herein, we obtained whole-transcriptome sequencing data of susceptible (S) and resistant (R) Pekin duckling samples at 0 h, 12 h, and 24 h after DHAV-3 infection. We found that DHAV-3 infection induces 5,396 differentially expressed genes (DEGs), 85 differentially expressed miRNAs (DEMs), and 727 differentially expressed lncRNAs (DELs) at 24 hpi in S vs. R ducks, those upregulated genes were enriched in inflammation and cell communications pathways and downregulated genes were related to metabolic processes. Upregulated genes showed high connectivity with the miR-33, miR-193, and miR-11591, and downregulated genes were mainly regulated by miR-2954, miR-125, and miR-146b. With the construction of lncRNA-miRNA-mRNA axis, we further identified a few aberrantly expressed lncRNAs (e.g., MSTRG.36194.1, MSTRG.50601.1, MSTRG.34328.7, and MSTRG.29445.1) that regulate expression of hub genes (e.g., THBD, CLIC2, IL8, ACOX2, GPHN, SMLR1, and HAO1) by sponging those highly connected miRNAs. Altogether, our findings defined a dual role of ncRNAs in immune and metabolic regulation during DHAV-3 infection, suggesting potential new targets for treating DHAV-3 infected ducks.

ABSTRACT: The aim of the experiment was to evaluate the status of innate immunity, oxidative status and lipid accumulation in ducklings exhibiting varying susceptibilities to DHAV-3 infection. In the experiment, ducklings with different DHAV-3 susceptibilities were used. Samples were collected at 6, 12, 15, and 24 h post infection (hpi), with 5 samples per time point. Plasma biochemistry, antioxidant enzyme activities, lipid content of liver and kidney were detected in the experiment. Elevated plasma level of total bilirubin, direct bilirubin, and creatinine indicated the injury of liver and kidney in susceptible ducklings (P < 0.05). The histopathological sections showed the injury in kidney. During the infection time, there was an increase in the concentrations of reactive oxygen species and oxidative damage markers (malondialdehyde and nitric oxide) in plasma of susceptible ducklings, particularly at 24 hpi (P < 0.05). Compared with the resistant ducklings, DHAV-3 infection resulted in a significant increase in the plasma total triglyceride (TG) level and a decrease in glucose level in susceptible ducklings. Gene expression of the innate immune response was both investigated in liver and kidney. In resistant ducklings, the expressions levels of pattern recognition receptors RIG-I, MDA5 remained constant. In contrast, the gene expressions peaked at 24 hpi in the susceptible ducklings. DHAV-3 infection promoted the expression of IFN, IL6, IL12β, caspase-8 or caspase-9 in both liver and kidney of susceptible ducklings. In conclusion, DHAV-3 infection led to the mobilization of antioxidant defenses, alterations in lipid metabolism, and oxidative stress in susceptible ducklings during DHAV-3 infection.

Abstract Genomic selection (GS) has great potential to increase genetic gain in poultry breeding. However, the performance of genomic prediction in duck growth and breast morphological (BM) traits remains largely unknown. The objective of this study was to evaluate the benefits of genomic prediction for duck growth and BM traits using methods such as GBLUP, single‐step GBLUP, Bayesian models, and different marker densities. This study collected phenotypic data for 14 growth and BM traits in a crossbreed population of 1893 Pekin duck × mallard, which included 941 genotyped ducks. The estimation of genetic parameters indicated high heritabilities for body weight (0.54–0.72), whereas moderate‐to‐high heritabilities for average daily gain (0.21–0.57) traits. The heritabilities of BM traits ranged from low to moderate (0.18–0.39). The prediction ability of GS on growth and BM traits increased by 7.6% on average compared to the pedigree‐based BLUP method. The single‐step GBLUP outperformed GBLUP in most traits with an average of 0.3% higher reliability in our study. Most of the Bayesian models had better performance on predictive reliability, except for BayesR. BayesN emerged as the top‐performing model for genomic prediction of both growth and BM traits, exhibiting an average increase in reliability of 3.0% compared to GBLUP. The permutation studies revealed that 50 K markers had achieved ideal prediction reliability, while 3 K markers still achieved 90.8% predictive capability would further reduce the cost for duck growth and BM traits. This study provides promising evidence for the application of GS in improving duck growth and BM traits. Our findings offer some useful strategies for optimizing the predictive ability of GS in growth and BM traits and provide theoretical foundations for designing a low‐density panel in ducks.

The city wall is a military defense building of an ancient city and a unique landscape architecture of a modern country that has extremely important historical, artistic, and scientific values. Most ancient Chinese walls were built of bricks and have been severely damaged and degraded by environmental and human influences. To protect these historical building monuments, it is necessary to determine scientifically the material properties of the bricks used in the ancient walls. In this study, the physical and mechanical properties, chemical element composition, mineral composition, micromorphology, and pore structure of 20 ancient fired clay bricks from four different regions, including white and blue wall bricks from Nanjing, blue wall bricks from Xi'an and Linqing, and the Great Wall bricks from Beijing, were compared using various modern analysis and testing methods. The results show that talc could be one of the raw materials to produce white bricks and the firing temperature of some white bricks could exceed 1200 ℃. The ancient blue bricks were mainly composed of quartz and feldspar, whereas the ancient white bricks were mainly composed of quartz and long prismatic and rod-like enstatite. The solid density and compressive strength of the white bricks were higher than that of the blue bricks. The proportion of pores larger than 10 µm in all ancient bricks is less than 10%. The pores smaller than 0.1 µm is less than 6% at higher firing temperatures. The results of this study can provide scientific guidance for the restoration and conservation of fired clay bricks of ancient city wall.

Abstract Background Carcass traits are crucial for broiler ducks, but carcass traits can only be measured postmortem. Genomic selection (GS) is an effective approach in animal breeding to improve selection and reduce costs. However, the performance of genomic prediction in duck carcass traits remains largely unknown. Results In this study, we estimated the genetic parameters, performed GS using different models and marker densities, and compared the estimation performance between GS and conventional BLUP on 35 carcass traits in an F2 population of ducks. Most of the cut weight traits and intestine length traits were estimated to be high and moderate heritabilities, respectively, while the heritabilities of percentage slaughter traits were dynamic. The reliability of genome prediction using GBLUP increased by an average of 0.06 compared to the conventional BLUP method. The Permutation studies revealed that 50K markers had achieved ideal prediction reliability, while 3K markers still achieved 90.7% predictive capability would further reduce the cost for duck carcass traits. The genomic relationship matrix normalized by our true variance method instead of the widely used $$\sum {2p}_{i}(1-{p}_{i})$$ ∑ 2 p i ( 1 - p i ) could achieve an increase in prediction reliability in most traits. We detected most of the bayesian models had a better performance, especially for BayesN. Compared to GBLUP, BayesN can further improve the predictive reliability with an average of 0.06 for duck carcass traits. Conclusion This study demonstrates genomic selection for duck carcass traits is promising. The genomic prediction can be further improved by modifying the genomic relationship matrix using our proposed true variance method and several Bayesian models. Permutation study provides a theoretical basis for the fact that low-density arrays can be used to reduce genotype costs in duck genome selection.

The shales of the Taiyuan Formation and Shanxi Formation in the North China Basin have good prospects for shale gas exploration and development. In this study, Well KP1 at the northern margin of the North China Basin was used as the research object for rock mineral, organic geochemical, and elemental geochemical analyses. The results show that brittle minerals in the shales of the Taiyuan Formation and Shanxi Formation are relatively rare (50%). The average TOC content is 3.68%. The organic matter is mainly mixed and sapropelic. The source rocks of the Taiyuan Formation and Shanxi Formation are mainly felsic, and the tectonic background lies in the continental island arc area. The primary variables that influenced the enrichment of organic materials during the sedimentary stage of the Taiyuan Formation were paleosalinity and paleoproductivity. Paleosalinity acted as the primary regulator of organic matter enrichment during the sedimentary stage of the Shanxi Formation.

The properties of a large number of concrete infrastructures in China are deteriorating year by year, raising the need for repairing and strengthening these infrastructures. By introducing waterborne polymers into a cement concrete system, brittle cracks and easy bonding performance defects of concrete can be compensated for to form a long-life, semi rigid, waterborne polymer-modified cementitious repair material with a promising development prospect. This paper investigates the modification effect of polymer emulsions on ordinary cement mortar. Our research mainly focused on the physical and mechanical properties, durability, microstructure and application status of waterborne polymer-modified cementitious composites. Literature studies show that with the increase in waterborne polymer content (0 wt%~20 wt%), the performance of cement mortar significantly improves, which in turn expands its application range. Compared with ordinary cement mortar, the introduction of waterborne polymers blocks some of the pores in the cement to a certain extent, thus improving its permeability, freeze–thaw resistance and durability. Finally, this paper describes the application of waterborne polymer–cementitious composites in western saline soil environments, as well as discusses the prospects of their development.

UAVs have been widely used in deformation monitoring because of their high availability and flexibility. However, the quality of UAV images is affected by changing attitude and surveying environments, resulting in a low monitoring accuracy. Cross-shaped markers are used to improve the accuracy of UAV monitoring due to their distinct center contrast and absence of eccentricity. However, existing methods cannot rapidly and precisely detect these markers in UAV images. To address these problems, this paper proposes an adaptive Radon-transform-based marker detection and localization method for UAV displacement measurements, focusing on two critical detection parameters, namely, the radius of marker information acquisition and the edge width of the cross-shaped scoring template. The experimental results show that the marker detection rate is 97.2% under different combinations of flight altitudes, radius ratios of marker information acquisition, and marker sizes. Furthermore, the root mean square error of detection and localization is 0.57 pixels, significantly surpassing the performance and accuracy of other methods. We also derive the critical detection radius and appropriate parameter combinations for different heights to further improve the practicality of the method.

Silica aerogel used in cement composites to prepare novel thermal superinsulation material has been gradually applied in buildings and can effectively reduce building energy consumption. In this paper, the geometric voxel construction method is used to heterogeneity model the thermal conductivity of a cement-based diatomite/silica aerogel composite (DSAC), and thermal conductivity simulations are carried out using a heat conduction model framework analogous to an electrical resistance model framework. The simulation results show that the simulated thermal conductivities of cementitious DSAC materials with different DSAC composite contents agree well with the corresponding experimental values. The saturated thermal conductivity of the cementitious DSAC material is 2.5 times the dry thermal conductivity at 28 d. This shows that the thermal conductivity model proposed in this paper can effectively predict the effective thermal conductivity of cementitious DSAC materials and can provide strong support for the material design and performance prediction of cementitious DSAC materials.

Terrestrial laser scanning (TLS) is an efficient tool to capture the point cloud for facade modeling. However, it is not easy to obtain the position by Global Navigation Satellite System (GNSS) as occluded by high buildings, which would lead to a problem in orienting the TLS data to a target coordinate system. In this article, we propose a coarse-to-fine registration method for reliably orienting the TLS data using a digital line graph (DLG). The orientation is completed by horizontal plane registration and elevation registration parts. The proposed method is composed of five steps: 1) using the proposed method to extract the corner points from the building outline of DLG; 2) using the proposed method based on RANSAC algorithm to extract the corner points and the facade point clouds of the TLS data; 3) coarse alignment of the two extracted sets of corner points using four-point congruent set algorithm; 4) fine registration by 2D-ICP algorithm; and 5) completing elevation registration using elevation control points. Three datasets are employed to perform the experiments, and the results confirm that the proposed method is reliable and efficient in achieving the registration of DLG and TLS data. After comparing with two other typical registration methods, it is found that the proposed method performs better.

Deep Neural Network (DNN)-based point cloud semantic segmentation has presented significant breakthrough using large-scale labeled aerial laser point cloud datasets. However, annotating such large-scaled point clouds is time-consuming. Self-Supervised Learning (SSL) is a promising approach to this problem by pre-training a DNN model utilizing unlabeled samples followed by a fine-tuned downstream task involving very limited labels. The traditional contrastive learning for point clouds selects the hardest negative samples by solely relying on the distance between the embedded features derived from the learning process, potentially evolving some negative samples from the same classes to reduce the contrastive learning effectiveness. This work proposes a hard-negative sample-aware self-supervised contrastive learning algorithm to pre-train the model for semantic segmentation. We designed a k-means clustering-based Absolute Positive And Negative samples (AbsPAN) strategy to filter the possible false-negative samples. Experiments on two typical ALS benchmark datasets demonstrate that the proposed method is more appealing than supervised training schemes without pre-training. Especially when the labels are severely inadequate (10% of the ISPRS training set), the results obtained by the proposed HAVANA method still exceed 94% of the supervised paradigm performance with full training set.

Contrastive learning allows us to learn general features for downstream tasks without the need for labeled data by leveraging intrinsic signals within remote sensing images. Existing contrastive learning methods encourage invariant feature learning by bringing positive samples defined by random transformations in feature spaces closer, where transformed samples of the same image at different intensities are considered equivalent. However, remote sensing images differ from natural images in their top-down perspective results in the arbitrary orientation of objects and in that the images contain rich in-plane rotation information. Maintaining invariance to rotation transformations can lead to the loss of rotation information in features, thereby affecting angle information predictions for differently rotated samples in downstream tasks. Therefore, we believe that contrastive learning should not focus only on strict invariance but encourage features to be equivariant to rotation while maintaining invariance to other transformations. To achieve this goal, we propose an invariant–equivariant covariant network (Co-ECL) based on collaborative and reverse mechanisms. The collaborative mechanism encourages rotation equivariance by predicting the rotation transformations of input images and combines invariant and equivariant learning tasks to jointly supervise the feature learning process to achieve collaborative learning. The reverse mechanism introduces a reverse rotation module in the feature learning stage, applying reverse rotation transformations with equal intensity to features in invariant learning tasks as in the data transformation stage, thereby ensuring their independent realization. In experiments conducted on three publicly available oriented object detection datasets of remote sensing images, our method consistently demonstrated the best performance. Additionally, these experiments on multi-angle datasets demonstrated that our method has good robustness on rotation-related tasks.

There are two common problems in the application of rubber aggregate concrete (RAC). One problem is that the rubber aggregate floats easily, which leads to a reduction in the workability of the mixture and delamination of the matrix. Another problem is that the mechanical properties of RAC are greatly reduced after hardening due to the poor interfacial bonding between rubber and the cement matrix (R–C). In this study, a novel modification method of waste rubber powder (WRP) combining mechanochemistry action, ultrasonic energy accumulation and the coating effect was proposed. The particle size distribution, specific surface area, hydrophilicity, morphology and structure of rubber were characterized by a laser particle size analyser, scanning electron microscopy (SEM), etc. The distribution of WRP in the cement-based materials was determined. The interfacial bonding and microstructure of R–C were analysed by SEM. The compressive and flexural strengths of cement-based materials with different contents of rubber were studied. The results showed that the R–C interface was significantly improved, and rubber particles were uniformly distributed in the cement mortar. The particle size of rubber particles showed a standard normal distribution, the surface cracks and pores were filled and coated, and the hydrophilic angle decreased from 94.6° to 68.0°. The cracks and voids of the R–C interface disappeared, and the compressive and flexural strengths of the mortar increased by 70% and 50%, respectively. The R–C interface and the distribution of rubber particles were found to play a major role in influencing the mechanical properties of RAC.

Abstract Owing to its designability and intrinsic fluorescence, non‐conjugated hyperbranched polysiloxane (HBPSi) has attracted widespread attention in biological filed, while it is still severely restricted by low fluorescence efficiency. So, in this paper, we introduced disulfide into HBPSi improving their luminescence properties and synthesized different molecular weight HBPSi (P1, P2, and P3). Surprisingly, P1 exhibited ultrahigh quantum yield up to 47.81%. Meanwhile, experiments applied with theoretical calculations were employed to explore the fluorescence mechanism, which is attributed to efficient restricting of non‐radiative decay by clusteroluminogens formed with the cooperation of hyperbranched structure and double hydrogen bonding. In addition, the biocompatibility of P1 was verified by co‐culture with MC3T3‐E1 and P1 lighted up mouse fibroblast cells without fluorescent dyes. This work designed a novel fluorescent polymer with ultrahigh fluorescence quantum yield and cell imaging ability, which is promising in visualization diagnosis and treatment of tumor.

Although psoriasis is classified as a T cell-mediated inflammatory disease, the contribution of myeloid cells to the pathogenesis of psoriasis is not fully understood. In the present study, we demonstrated that the expression of the anti-inflammatory cytokine interleukin-35 (IL-35) was significantly increased in patients with psoriasis with a marked increase in the number of myeloid-derived suppressor cells (MDSCs). Similar results were obtained in an imiquimod-induced psoriasis mouse model. IL-35 reduced the total number of MDSCs and their subtypes in the spleens and psoriatic skin lesions, ameliorating psoriasis. IL-35 also reduced the expression of inducible nitric oxide synthase in MDSCs, although it had no significant effect on interleukin-10 expression. Adoptive transfer of MDSCs from imiquimod-challenged mice aggravated the disease and weakened the effect of IL-35 in the recipient mice. In addition, mice transferred with MDSCs isolated from inducible nitric oxide synthase knockout mice had milder disease than those with wild-type MDSCs. Furthermore, wild-type MDSCs reversed the effects of IL-35, while MDSCs isolated from inducible nitric oxide synthase knockout mice did not affect IL-35 treatment. In summary, IL-35 may play a critical role in the regulation of iNOS-expressing MDSCs in the pathogenesis of psoriasis, highlighting IL-35 as a novel therapeutic strategy for patients with chronic psoriasis or other cutaneous inflammatory diseases.

Abstract Background Skin pigmentation is a broadly appearing phenomenon of most animals and humans in nature. Here we used a bird model to investigate why melanin spot deposits on the skin. Results Our result showed that growth age and the sunlight might induce melanin deposition in bird beak skin which was determined by genetic factors. GWAS helped us to identify two major loci affecting melanin deposition, located on chromosomes 13 and 25, respectively. The fine mapping works narrowed the candidate regions to 0.98 Mb and 1.0 Mb on chromosomes 13 and 25. The MITF and POU2F3 may be the causative genes and synergistically affect melanin deposition during duck beak skin. Furthermore, our data strongly demonstrated that the pathway of melanin metabolism contributes to melanin deposition on the skin. Conclusions We demonstrated that age and sunlight induce melanin deposition in bird beak skin, while heredity is fundamental. The MITF and POU2F3 likely played a synergistic effect on the regulation of melanin synthesis, and their mutations contribute to phenotypic differences in beak melanin deposition among individuals. It is pointed out that melanin deposition in the skin is related to the pathway of melanin metabolism, which provided insights into the molecular regulatory mechanisms and the genetic improvement of the melanin deposition in duck beak.

The segmentation of airborne laser scanning (ALS) point clouds remains a challenge in remote sensing and photogrammetry. Deep learning methods, such as KPCONV, have proven effective on various datasets. However, the rigid convolutional kernel strategy of KPCONV limits its potential use for 3D object segmentation due to its uniform approach. To address this issue, we propose an Integrated Point Convolution (IPCONV) based on KPCONV, which utilizes two different convolution kernel point generation strategies, one cylindrical and one a spherical cone, for more efficient learning of point cloud data features. We propose a customizable Multi-Shape Neighborhood System (MSNS) to balance the relationship between these convolution kernel point generations. Experiments on the ISPRS benchmark dataset, LASDU dataset, and DFC2019 dataset demonstrate the validity of our method.

With the continuous improvement in the volume and spatial resolution of remote sensing images, the self-supervised contrastive learning paradigm driven by a large amount of unlabeled data is expected to be a promising solution for large-scale land cover classification with limited labeled data. However, due to the richness and scale diversity of ground objects contained in remote sensing images, self-supervised contrastive learning encounters two challenges when performing large-scale land cover classification: (1) Self-supervised contrastive learning models treat random spatial–spectral transformations of different images as negative samples, even though they may contain the same ground objects, which leads to serious class confusion in land cover classification. (2) The existing self-supervised contrastive learning models simply use the single-scale features extracted by the feature extractor for land cover classification, which limits the ability of the model to capture different scales of ground objects in remote sensing images. In this study, we propose a contrastive learning network with Geography Feature space joint negative sample Correction (GFCNet) for land cover classification. To address class confusion, we propose a Geography Feature space joint negative sample Correction Strategy (GFCS), which integrates the geography space and feature space relationships of different images to construct negative samples, reducing the risk of negative samples containing the same ground object. In order to improve the ability of the model to capture the features of different scale ground objects, we adopt a Multi-scale Feature joint Fine-tuning Strategy (MFFS) to integrate different scale features obtained by the self-supervised contrastive learning network for land cover classification tasks. We evaluate the proposed GFCNet on three public land cover classification datasets and achieve the best results compared to seven baselines of self-supervised contrastive learning methods. Specifically, on the LoveDA Rural dataset, the proposed GFCNet improves 3.87% in Kappa and 1.54% in mIoU compared with the best baseline.

Detection small moving targets in infrared sequences with accuracy and low computation time is challenging work in infrared search and tracking systems. A frequent approach for this task is to strengthen small weak targets and diminish the clutter of background. However, the background and small targets’ pixel values are close to each other and thus only a few background suppressing models are suitable to infrared small target segmentation. To efficiently resolve the problem that most of the classic approaches cannot manage low signal to noise ratio and weak objects without details, a novel spatial-temporal local difference measure is introduced for moving objects segmentation in infrared sequences. First of all, to strengthen targets, a new local vector dissimilarity measure is employed to demonstrate the difference between the weak target and their surrounding backgrounds and calculate the spatial saliency feature figure. Then the local sample consensus of succession images is used to compute the temporal varying feature figure. Afterward, the combined saliency feature map is measured by taking spatial and temporal feature images into account. Finally, the small moving targets are segmented employing an adaptive threshold approach. Abundant quantitative and qualitative experimental results have demonstrated that the introduced approach is remarkable and has a superior accuracy in terms of performance on both public and real datasets in comparison to the state-of-the-art spatial and temporal models.

Abstract Background As a major economic trait in poultry, egg production efficiency attracts widespread interest in breeding and production. However, limited information is available about the underlying genetic architecture of egg production traits in ducks. In this paper, we analyzed six egg production-related traits in 352 F2 ducks derived from reciprocal crosses between mallard and Pekin ducks. Results Feed conversation ratio (FCR) was positively correlated with feed intake but negatively correlated with egg-related traits, including egg weight and egg production, both phenotypically and genetically. Estimates of pedigree-based heritability were higher than 0.2 for all traits investigated, except hip-width. Based on whole-genome sequencing data, we conducted genome-wide association studies to identify genomic regions associated with these traits. In total, 11 genomic regions were associated with FCR. No genomic regions were identified as significantly associated with hip-width, total feed intake, average daily feed intake, and total egg production. Analysis of selective sweeps between mallard and Pekin ducks confirmed three of these genomic regions on chromosomes 13, 3 and 6. Within these three regions, variants in candidate genes that were in linkage disequilibrium with the GWAS leader single nucleotide polymorphisms (SNPs) (Chr13:2,196,728, P = 7.05 × 10–14; Chr3:76,991,524, P = 1.06 × 10–12; Chr6:20,356,803, P = 1.14 × 10–10) were detected. Thus, we identified 31 potential candidate genes associated with FCR, among which the strongest candidates are those that are highly expressed in tissues involved in reproduction and nervous system functions of ducks: CNTN4, CRBR, GPR63, KLHL32, FHL5, TRNT1, MANEA, NDUFAF4, and SCD. Conclusions For the first time, we report the identification of genomic regions that are associated with FCR in ducks and our results illustrate the genomic changes that occurred during their domestication and are involved in egg production efficiency.

Masked image modeling (MIM) is a learning method in which the unmasked components of the input are utilized to learn and predict the masked signal, enabling learning from large amounts of unannotated data. However, due to the scale diversity and complexity of features in remote sensing images (RSIs), existing MIMs face two challenges in the RSI scene classification task: (1) If the critical local patches of small-scale objects are randomly masked out, the model will be unable to learn its representation. (2) The reconstruction of MIM relies on the visible local contextual information surrounding the masked regions and overemphasizing this local information will potentially lead the model to disregard the global semantic information of the input RSI. Regarding the above considerations, we proposed a global semantic integrated self-distilled complementary masked image model (GSC-MIM) for RSI scene classification. To prevent information loss, we proposed an information-preserved complementary masking strategy (IPC-Masking), which generates two complementary masked views for the same image to resolve the problem of masking critical areas of small-scale objects. To incorporate global information into the MIM pre-training process, we proposed the global semantic distillation strategy (GSD). Specifically, we introduced an auxiliary network pipeline to extract the global semantic information from the full input RSI and transfer the knowledge to the MIM by self-distillation. The proposed GSC-MIM is validated on three publicly available datasets of AID, NWPU-RESISC45, and UC-Merced Land Use, and the results show that the proposed method's Top-1 accuracy surpasses the baseline approaches in three datasets by up to 4.01, 3.87, and 5.26%, respectively.

As a critical developmental stage in vertebrates, the vertebral column formation process is under strict control; however, we observed variations in the number of cervical vertebrae in duck populations in our previous study. Here, we further explored the variations in the number of vertebrae in two duck populations: 421 Pekin duck × mallard F2 ducks and 850 Pekin ducks. Using resequencing data of 125 Pekin ducks with different numbers of cervical vertebrae and 352 Pekin duck × mallard F2 ducks with different numbers of thoracic vertebrae, we detected whole-genome copy number variations (CNVs) and implemented a genome-wide association study (GWAS) to identify the genetic variants related to the traits. The findings verified the existence of variations in the number of cervical vertebrae in duck populations. The number of cervical vertebrae in most ducks was 15, while that in a small number of the ducks was 14 or 16. The number of cervical vertebrae had a positive influence on the neck production, and one cervical vertebra addition could increase 11 g or 2 cm of duck neck. Genome-wide CNV association analysis identified six CNVs associated with the number of cervical vertebrae, and the associated CNV regions covered 15 genes which included WNT10A and WNT6. These findings improve our understanding of the variations in the number of vertebrae in ducks and lay a foundation for future duck breeding.

Remote sensing image change detection (RS-CD) has made impressive progress with the help of deep learning techniques. Small object change detection (SoCD) still faces many challenges. On the one hand, when the scale of changing objects varies greatly, deep learning models with overall accuracy as the optimization goal tend to focus on large object changes and ignore small object changes to some extent. On the other hand, the RS-CD model based on deep convolutional networks needs to perform multiple spatial pooling operations on the feature map to obtain deep semantic features, which leads to the loss of small object feature-level information in the local space. Therefore, we propose a Siamese transformer change detection network with a multiscale window via an adaptive fusion strategy (SWaF-Trans). To solve the problem of ignoring small object changes, we compute self-attention in windows of different scales to model changing objects at the corresponding scales and establish semantic information links through a moving window mechanism to capture more comprehensive small object features in small-scale windows, thereby enhancing the feature representation of multiscale objects. To fuse multiscale features and alleviate the problem of small object feature information loss, we propose a channel-related fusion mechanism to model the global correlation between channels for display and adaptively adjust the fusion weights of channels to enable the network to capture more discriminative features of interest and reduce small object feature information loss. Experiments on the CDD and WHU-CD datasets show that SWaF-Trans exceeds eight advanced baseline methods, with absolute F1 scores as high as 97.10% and 93.90%, achieving maximum increases of 2% and 5.6%, respectively, compared to the baseline methods.

Abstract Hard yet flexible coatings with multi‐functionalities are useful for foldable displays and marine industries but rare. In this study, a highly cross‐linked multifunctional hybrid coating with ceramic‐like hardness and polymer‐like flexibility is reported. The coating is prepared via a step‐by‐step strategy, where two types of epoxy‐oligosiloxane nanoclusters are first synthesized by sol‐gel chemistry, and amine‐terminated curing agents are used to cross‐link them at room temperature. The coating is highly transparent (>92% transmittance), hard (6‐7H), and flexible (10 mm bending diameter) because of the unique combination of siloxane nanoclusters and polymer networks. Meanwhile, since the coating contains fouling‐resistant telomer and low‐surface‐tension liquid lubricant polydimethylsiloxane (PDMS), it exhibits excellent anti‐biofouling and self‐cleaning properties. The results indicate that the mechanical and antifouling properties of the coating can be easily tuned and prove that the step‐by‐step strategy is a promising and universal method. The novel coatings can meet the needs of applications in foldable displays, marine industries, and other fields.

Abstract The previous researches on the degradation process of concrete under sulfate attack mainly focus on non-damaged concrete. It may lead to an excessive evaluation of the durability of the structure, which is detrimental to the safety of the structure. In this paper, three different damage degrees of concrete specimens with non-damaged (D 0) and initial damage of 10% (D 1) and 20% (D 2) were prefabricated and subjected to sulfate attack and wetting–drying cycles. With the increase of sulfate attack cycles (0, 30, 60, 90, 120, 150 cycles), the changes in mass loss, relative dynamic modulus of elasticity, and the stress–strain curve were studied. The results show that the mass of the D 0 specimen had been increasing continuously before 150 sulfate attack cycles. The mass of D 1 and D 2 had been increasing before 60 cycles, and decreasing after 60 cycles. At 150 cycles, the mass loss of D 0, D 1, D 2 were − 1.054%, 0.29% and 3.20%, respectively. The relative dynamic modulus of elasticity (RDME) of D 0 specimen increases continuously before 90 sulfate attack cycles. After 90 cycles, the RDME gradually decreases. However, for D 1 and D 2 specimens, the RDME began to decrease after 30 cycles. The damage degree has an obvious influence on the compressive strength and elastic modulus. For the D 0 specimen, the compressive strength and elastic modulus increased continuously before 90 cycles and decreased after 90 cycles. The compressive strength and elastic modulus of D 1 and D 2 specimens began to decrease after 30 cycles. The stress–strain curves of concrete with different initial damage degrees were established, and the fitting results were good. Finally, based on the analysis of experimental data, the degradation mechanism of concrete with initial damage under the sulfate wetting–drying cycle was discussed.

The effect of CNTs on the mechanical and damping properties of macro-defect-free (MDF) cements was studied, and polyvinyl alcohol (PVA) fibers were also studied as a contrast. It was found that the compressive strength of MDF cements was not significantly affected by the two types of fibers. The CNTs enhanced the flexural strength of MDF, while PVA fibers made negative contribution. The strengthening mechanism of flexural strength of MDF cements by CNTs can be summarized as fiber bridging, crack deflection and fiber slippage. For the damping properties, the proper contents of CNTs and PVA fibers improved the loss factor significantly. The interface transition zone (ITZ) between the PVA fibers and matrix was large, which was favorable for fiber slippage. The damping property of MDF cements with CNTs was mainly due to the slippage between the inner tubes of the CNTs rather than the slippage between the CNTs and matrix.

In this article, the tensile strength, melting properties, and fiber-forming properties of natural continuous basalt fibers, such as andesite, andesite basalt, and tholeiitic basalt, are investigated as a function of their chemical and mineral compositions. The results indicate that when the basalt glass melts are homogeneous, the tensile strength is mainly determined by the chemical composition as well as the mineral components, which will affect the melting properties and fiber-forming properties. By optimizing the melting properties and fiber-forming properties, a high filament tensile strength of 3390 MPa was achieved for the basalt andesite with regions of tholeiitic basalt with an SiO2 weight percentage of 49%–57%.

Background subtraction is commonly employed in foreground object detection in urban traffic scenes. Most of the current color or texture feature-based background subtraction models are easily contaminated by sudden and gradual illumination variations in urban traffic scenes. To resolve this deficiency, an adaptive local median texture feature, which extracts the adaptive distance threshold employing the median information in a predefined local region of a pixel and Weber's law, is introduced. In addition, a sample consensus-based model that evolved from portable visual background extractor is proposed using an adaptive local median texture feature. Then, the foreground is labeled by comparing the input video frames feature with the model. Moreover, to adapt the dynamic background, the random update scheme is used to update the model. Extensive experimental results on the public Change Detection data set of 2014 (CDnet2014) and the real-world urban traffic videos demonstrate that our background subtraction method is superior to the other state-of-the-art texture-feature-based methods. The qualitative and quantitative results show the encouraging efficiency of the proposed technique to deal with sudden and gradual illumination variations in real-world urban traffic scenes.

The development of Internet technology and cloud computing has promoted the rapid development of self-media technology. The self-media technology has better people-friendliness compared to the traditional media communication mode, so it has gained more popularity compared to the traditional media mode. For professional self-media teams, the popularity and clicks of self-media content are very critical. It needs to make corresponding predictions and judgments according to the content and transmission path of the self-media. However, self-media is transmitted in the form of video, which involves a huge amount of data. This team of self-media staff is a more difficult and tedious task. This study uses the atrous convolution and long short-term memory neural network to predict the video content, sound features, and propagation path of self-media technology. Atrous convolution is more suitable for research objects with more data. The research results show that the atrous convolution and LSTM methods have better feasibility and credibility in predicting three special characteristics of self-media. Compared with a single atrous convolution, the feature prediction errors of the three kinds of self-media are smaller by using the atrous convolution and LSTM hybrid method. The largest prediction error is 2.39%, and this part of the error is mainly due to the sound characteristics of self-media technology.

Computer vision-based displacement measurement techniques are increasingly used for structural health monitoring. However, the vision sensors employed are easily affected by optical turbulence when capturing images of the structure, resulting in displacement measurement errors that significantly reduce the accuracy required in engineering applications. Hence, this paper develops a multi-measurement point method to address this problem by mitigating optical-turbulence errors with spatial randomness. Then, the effectiveness of the proposed method in mitigating optical-turbulence errors is verified by static target experiments, in which the RMSE correction rate can reach up to 82%. Meanwhile, the effects of target size and the number of measurement points on the proposed method are evaluated, and the optimal target design criteria are proposed to improve our method’s performance in mitigating optical-turbulence errors under different measurement conditions. Additionally, extensive dynamic target experiments reveal that the proposed method achieves an RMSE correction rate of 69% after mitigating the optical-turbulence error. The experimental results demonstrate that the proposed method improves the visual displacement measurement accuracy and retains the detailed information of the displacement measurement results.

Recycled powder is a kind of powder particle with a particle size of less than 75 μm produced in the process of preparing recycled aggregate from construction waste with concrete and brick as the main components. It has the potential to replace part of cement as an auxiliary cementitious material. This has important engineering application value for promoting the full-component and high-quality utilization of construction waste, which meets the needs of national sustainable development. Based on the physical and chemical characteristics of recycled powder, the preparation process and basic properties of the recycled powder were systematically analyzed. Based on the low activity of recycled powder, different methods of its activity excitation were described in detail. In addition, some existing problems in the current research were also prospected.

When using digital images to obtain the displacement of a structure, noise is always a factor that greatly affects the accuracy of the displacement results. To overcome this problem, a phase-correlation improvement method, based on phase filtering by phase standard deviation (PSD), is proposed. We use PSD to remove the severe noise interference area in the cross-power spectrum matrix, then the singular value decomposition (SVD) is used to convert the two-dimensional phase to one-dimensional to reduce the difficulty of phase unwrapping. Finally, straight-line fitting is used to obtain the high-precision displacement results. Experiments were carried out using both simulated data and real data. For the simulated data, the absolute accuracy of the proposed method is around 0.3 pixels, while, for the real data, the absolute accuracy of the proposed method is 0.018 mm. The experimental results show that the method can effectively resist noise interference and still obtain accurate displacement estimation results in the case of severe noise.

Background and objective Lung cancer rates among women in rural Xuanwei and Fuyuan counties in eastern Yunnan province, China, are among the highest in the world, even though almost all women are non-smokers, and they tend to develop lung cancer at a younger age than other locations by roughly 5 yr-10 yr. This study investigated the survival of lung cancer patients among female never-smokers. Methods The female never-smokers, who had lived for many years in Xuanwei and Fuyuan counties, with lung cancer newly-diagnosed between July 2006 to March 2010, were followed up through the end of 2016. Age-standardized relative survival for all cases was calculated using local life table. The Kaplan-Meier method and Log-rank test were used to analyze the relationship between the variables and the prognosis in univariate analysis. Cox regression analysis was employed in the multivariate analysis. Results Among 1,250 total subjects, 1,075 died and the remaining 175 were censored during the follow-up, with a median follow-up period of 69 months (95%CI: 61.9-76.0). Overall, the mean age was (54.8 ±10.9) yr, with variable clinical stages: 3.5% of cases were stage I, 8.7% stage II, 20.7% stage III, 29.7% stage IV, and 37.4% stage unknown. The 645 patients(51.6%) with cyto-histological diagnosis contains 303 with Squamous cell carcinoma, and 231 with adenocarcinoma, 24 with small cell, 43 with other specified type and 39 with unknown histological type. Only 215 (17.2%) patients received surgery, 487 (39.0%) were treated without surgery, and 548 (43.8%) did not receive any specific anticancer therapy. The 5-year observed survival rate and age-standardized relative survival were 8.9% (95%CI: 7.0-10.6), and 10.1% (95%CI: 3.7-20.5) respectively, with a median survival of 13.2 months. The 5-year survival rates were 41.1% for stage I, 22.4% for stage II, 5.3% for stage III, 1.3% for stage IV, 11.2% for missing stage, 17.9% for adenocarcinoma, and 5.6% for squamous cell carcinoma respectively. Surgery significantly improved 5-year survival rate compared with non-surgery (34.8% vs 3.2%, P

Abstract Background Salinomycin is a monocarboxylic polyether antibiotic and is a potential chemotherapy drug. Our previous studies showed that salinomycin inhibited cell growth and targeted CSCs in prostate cancer. However, the precise target of salinomycin action is unclear. Methods In this work, we analyzed and identified differentially expressed genes (DEGs) after treatment with or without salinomycin using a gene expression microarray in vitro (PC-3 cells) and in vivo (NOD/SCID mice xenograft model generated from implanted PC-3 cells). Western blotting and immunohistochemical staining were used to analyze the expression of ATP2A3 and endoplasmic reticulum (ER) stress biomarkers. Flow cytometry was used to analyze the cell cycle, apoptosis and intracellular Ca2+ concentration. Results A significantly upregulated gene, ATPase sarcoplasmatic/endoplasmatic reticulum Ca2+ transporting 3 (ATP2A3), was successfully identified. In subsequent studies, we found that ATP2A3 overexpression could trigger ER stress and exert anti-cancer effects in PC-3 and DU145 cells. ATP2A3 was slightly expressed, but the ER stress biomarkers showed strong staining in prostate cancer tissues. We also found that salinomycin could trigger ER stress, which might be related to ATP2A3-mediated Ca2+ release in PC-3 cells. Furthermore, we found that salinomycin-triggered ER stress could promote apoptosis and thus exert anti-cancer effects in prostate cancer cells. Conclusion This study demonstrates that ATP2A3 might be one of the potential targets for salinomycin, which can inhibit Ca2+ release and trigger ER stress to exert anti-cancer effects.

The development of liver fibrosis is closely related to the gut microbiota, and the “gut-liver axis” is the most important connection between the two. ethyl acetate extract of Cichorium pumilum Jacq (CGEA) is an herbal extract consisting mainly of sesquiterpenoids. The anti-inflammatory and hepatoprotective effects of CGEA have been reported, but the anti-fibrotic effects of CGEA via intestinal microbes and the “gut-liver axis” cycle have rarely been reported. In this study, we observed that CGEA not only directly attenuated inflammatory factor levels in inflamed mice, but also attenuated liver inflammation as well as liver fibrosis degeneration in rats with liver fibrosis caused by colitis. We observed in vitro that CGEA significantly promoted the growth of Bifidobacterium adolescentis. Similarly, fecal 16S rDNA sequencing of liver fibrosis rats showed that CGEA intervention significantly altered the composition of the intestinal microbiota of liver fibrosis rats. CGEA increased the abundance of intestinal microbiota, specifically, CGEA increased the ratio of Firmicutes to Bacteroidetes, CGEA could significantly increase the levels of Ruminococcus. In addition, CGEA intervention significantly protected intestinal mucosal tissues and improved intestinal barrier function in rats. Lactucin is the main sesquiterpenoid in CGEA, and HPLC results showed its content in CGEA was up to 6%. Lactucin has been reported to have significant anti-inflammatory activity, and in this study, we found that Lactucin decreased p38 kinases (p38), phosphorylation of the extracellular signal-regulated kinase (ERK) and protein kinase B (AKT) protein phosphorylation in lipopolysaccharide (LPS)-activated RAW264.7 cells, thereby reducing mRNA expression and protein expression of pro-inflammatory factors inducible nitric oxide synthase (iNOS) and cyclooxygenase-2 (COX-2), and inhibiting the release of inflammatory factors interleukin (IL)-6 and nitric oxide (NO), exerting anti-inflammatory effects. In summary, the prevention of liver fibrosis caused by intestinal inflammation by CGEA may be achieved by regulating the intestinal microbiota and restoring the intestinal barrier thereby improving the “gut-liver axis” circulation, reducing liver inflammation, and ultimately alleviating liver fibrosis. Notably, the direct anti-inflammatory effect of CGEA may be due to its content of Lactucin, which can exert anti-inflammatory effects by inhibiting the phosphorylation of Mitogen-activated protein kinase (MAPK) and Akt signaling pathways.

Cold-induced thermogenesis plays an important role in the survival of lambs exposed to low air temperatures. The liver produces and mediates heat production in mammals; however, to date, little is known about the role of liver genes in cold-induced thermogenesis in lambs. In this study, the difference in the liver transcriptome between Altay and Hu ewe lambs was compared. Because of different backgrounds of the two breeds, we hypothesized that the transcriptome profiles of the liver would differ between breeds when exposed to cold. Cold-exposed Altay lambs activated 8 candidate genes (ACTA1, MYH1, MYH2, MYL1, MYL2, TNNC1, TNNC2, and TNNT3) involved in muscle shivering thermogenesis; 3 candidate genes (ATP2A1, SLN, and CKM) involved in muscle nonshivering thermogenesis related to the Ca2+ signal and creatine cycle; and 6 candidate genes (PFKM, ALDOC, PGAM2, ENO2, ENO3, and ENO4) involved in enhancing liver metabolism. In contrast, the liver may not act as the main tissue for thermogenesis in cold-exposed Hu lambs. We concluded that Altay lambs rely on liver-mediated shivering and nonshivering thermogenesis by muscle tissue to a greater extent than Hu lambs. Results from this study could provide a theoretical foundation for the breeding and production of cold-resistant lambs.

Owing to the limited field of view (FOV) and depth of field (DOF) of a conventional camera, it is quite difficult to employ a single conventional camera to simultaneously measure high-precision displacements at many points on a bridge of dozens or hundreds of meters. Researchers have attempted to obtain a large FOV and wide DOF by a multi-camera system; however, with the growth of the camera number, the cost, complexity and instability of multi-camera systems will increase exponentially. This study proposes a multi-point displacement measurement method for bridges based on a low-cost Scheimpflug camera. The Scheimpflug camera, which meets the Scheimpflug condition, can enlarge the depth of field of the camera without reducing the lens aperture and magnification; thus, when the measurement points are aligned in the depth direction, all points can be clearly observed in a single field of view with a high-power zoom lens. To reduce the impact of camera motions, a motion compensation method applied to the Scheimpflug camera is proposed according to the characteristic that the image plane is not perpendicular to the lens axis in the Scheimpflug camera. Several tests were conducted for performance verification under diverse settings. The results showed that the motion errors in x and y directions were reduced by at least 62% and 92%, respectively, using the proposed method, and the measurements of the camera were highly consistent with LiDAR-based measurements.