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Abstract To accurately understand the deformation behavior of surrounding rock in the jiugongshan No.2 high ground stress tunnel and optimize construction parameters for improved efficiency, on-site monitoring was used to gather data on rock deformation and initial support contact pressure. A WOA-LSTM regression prediction model was proposed, and excavation advance depth was optimized using numerical simulation. The WOA-LSTM regression prediction model demonstrated high accuracy in tunnel deformation monitoring. The absolute errors between predicted and actual values of tunnel settlement and convergence at various measurement points average 2.53− 04 mm and 1.96− 04 mm, with relative errors averaging 2.15% and 2.34%. These results meet the requirements for guiding construction. Additionally, based on the results of numerical simulation calculations, when the step length is 12 m during the construction of high-stress tunnels using the benching method, excavation advances of 2 m and 3 m result in settlement and convergence increases of 35.1% and 63.4%, and 25.5% and 55.2%, respectively, compared to an excavation advance of 1 m. However, no sudden jumps in these values were observed, indicating that with a 3 m excavation advance, the integrity of the surrounding rock remains in good condition, effectively guiding safe and rapid construction methods.

Abstract Background Inflammatory bowel disease (IBD), a chronic inflammatory condition, is caused by several factors involving aberrant immune responses. Genetic factors are crucial in IBD occurrence. Mendelian randomization (MR) can offer a new perspective in understanding IBD’s genetic background. Methods Single nucleotide polymorphisms (SNPs) were considered instrumental variables (IVs). We analyzed the relationship between 731 immunophenotypes, 1,400 metabolite phenotypes, and IBD. The total effect was decomposed into indirect and direct effects, and the ratio of the indirect effect to the total effect was calculated. Results We identified the causal effects of HLA-DR-expressing CD14 + monocytes on IBD through MR analysis. The phenotype “HLA-DR expression on CD14 + monocytes” showed the strongest association among the selected 48 immune phenotypes. Chiro-inositol metabolites mediated the effect of CD14 + monocytes expressing HLA-DR on IBD. An increase in Chiro-inositol metabolites was associated with a reduced risk of IBD occurrence, accounting for 4.97%. Conclusion Our findings revealed a new pathway by which HLA-DR-expressing CD14 + monocytes indirectly reduced the risk of IBD occurrence by increasing the levels of Chiro-inositol metabolites. The results provided a new perspective on the immunoregulatory mechanisms underlying IBD, laying a theoretical foundation for developing new therapeutic targets in the future.

BackgroundTertiary hospitals in China are confronted with significant challenges due to limited spatial capacity and workforce constraints, leading to saturated allocation of medical resources and restricted growth in medical service provision. The incorporation of digital health into medical service process reengineering (MSPR) marks a pivotal transformation and restructuring of conventional health service delivery models. Specifically, the application of MSPR to blood sampling services processes reengineering (BSSPR) holds promise for substantially enhancing the efficiency and quality of medical services through streamlining and optimizing these procedures. However, the comprehensive impact of BSSPR has been infrequently quantified in existing research. ObjectiveThis study aims to investigate the influence of BSSPR on the efficiency and quality of medical services and to elucidate the key informative technological support points underpinning BSSPR. MethodsData were collected from both the new and old laboratory information systems from August 1, 2019, to December 31, 2021. A combination of statistical description, chi-square test, and t test was used to compare check-in time and waiting time of outpatients before and after the implementation of BSSPR. An interrupted time-series design was used to analyze the impact of BSSPR on medical service efficiency and quality, enabling the control of confounding variables, including changes in medical human resources and both long- and short-term temporal trends. ResultsBSSPR had an impact on the efficiency and quality of medical services. Notably, there was a significant increase in the number of patients receiving blood sampling services, with a daily service volume increase of ~150 individuals (P=.04). The average waiting time for patients decreased substantially from 29 (SD 36) to 11 (SD 11) minutes, indicating a marked improvement in patient experience. During the peak period, the number of patients receiving blood sampling services per working hour statistically increased from 9.56 to 16.77 (P

Background: To enhance the accuracy of hepatocellular carcinoma (HCC) diagnosis using contrast-enhanced (CE) US, the American College of Radiology developed the CEUS Liver Imaging Reporting and Data System (LI-RADS). However, the system still exhibits limitations in distinguishing between HCC and non-HCC lesions. Purpose: To investigate the viability of employing machine learning methods based on quantitative parameters of contrast-enhanced ultrasound for distinguishing HCC within LR-M nodules. Materials and methods: This retrospective analysis was conducted on pre-treatment CEUS data from liver nodule patients across multiple centers between January 2013 and June 2022. Quantitative analysis was performed using CEUS images, and the machine learning diagnostic models based on quantitative parameters were utilized for the classification diagnosis of LR-M nodules. The performance of the model was assessed using the area under the receiver operating characteristic curve (AUC) and compared with the performance of four radiologists. Results: The training and internal testing datasets comprised 168 patients (median age, 53 years [IQR, 18 years]), while the external testing datasets from two other centers included 110 patients (median age, 54 years [IQR, 16 years]). In the internal independent test set, the top-performing Random Forest model achieved an AUC of 0.796 (95%CI: 0.729–0.853) for diagnosing HCC. This model exhibited a sensitivity of 0.752 (95%CI: 0.750–0.755) and a specificity of 0.761 (95%CI: 0.758–0.764), outperforming junior radiologists who achieved an AUC of 0.619 (95%CI: 0.543–0.691, p

Objectives: Patients with intermediate or advanced hepatocellular carcinoma (HCC) require repeated disease monitoring, prognosis assessment and treatment planning. In 2018, a novel machine learning methodology “survival path” (SP) was developed to facilitate dynamic prognosis prediction and treatment planning. One year after, a deep learning approach called Dynamic Deephit was developed. The performance of the two state-of-art models in dynamic prognostication have not been compared. Methods: We trained and tested the SP and Dynamic DeepHit models in a large cohort of 2511 HCC patients using time-series data. The time-series data were converted into data of time slices, with an interval of three months. The time-dependent c-index for OS at given prediction time ( t = 1, 6, 12, 18 months) and evaluation time (∆ t = 3, 6, 9, 12, 18, 24, 36, 48 months) were compared. Results: The comparison between SP model and Dynamic DeepHit-HCC model showed the latter had significant better performance at the time of initial admission. The time-dependent c-index of Dynamic DeepHit-HCC model gradually decreased with the extension of time (from 0.756 to 0.639 in the training set; from 0.787 to 0.661 in internal testing set; from 0.725 to 0.668 in multicenter testing set); while the time-dependent c-index of SP model displayed an increased trend (from 0.665 to 0.748 in the training set; from 0.608 to 0.743 in internal testing set; from 0.643 to 0.720 in multicenter testing set). When the prediction time comes to 6 months or later since initial treatment, the survival path model outperformed the dynamic DeepHit model at late evaluation times (∆ t > 12 months). Conclusions: This research highlighted the unique strengths of both models. The SP model had advantage in long term prediction while the Dynamic DeepHit-HCC model had advantages in prediction at near time points. Fine selection of models is needed in dealing with different scenarios.

Abstract Although most people living with HIV (PLWH) receiving antiretroviral therapy (ART) achieve continuous viral suppression, some show detectable HIV RNA as low-level viremia (LLV) (50–999 copies/mL). Drug resistance mutations (DRMs) in PLWH with LLV is of particular concern as which may lead to treatment failure. In this study, we investigated the prevalence of LLV and LLV-associated DRMs in PLWH in Zhengzhou City, China. Of 3616 ART-experienced PLWH in a long-term follow-up cohort from Jan 2022 to Aug 2023, 120 were identified as having LLV. Of these PLWH with LLV, we obtained partial pol and integrase sequences from 104 (70 from HIV-1 RNA and 34 from proviral DNA) individuals. DRMs were identified in 44 individuals. Subtyping analysis indicated that the top three subtypes were B (48.08%, 50/104), CRF07_BC (31.73%, 33/104), and CRF01_AE (15.38%, 16/104). The proportions of nucleoside reverse transcriptase inhibitors (NRTIs), non-nucleoside reverse transcriptase inhibitors (NNRTIs), protease inhibitors (PIs), and integrase strand transfer inhibitors (INSTIs) associated DRMs were 23.83% (24/104), 35.58% (37/104), 5.77% (6/104), and 3.85% (4/104), respectively, which contributed to an overall prevalence of 42.31% (44/104). When analyzed by individual DRMs, the most common mutation(s) were V184 (18.27%, 19/104), followed by V179 (11.54%, 12/104), K103 (9.62%, 10/104), Y181 (9.62%, 10/104), M41 (7.69%, 8/104), and K65R (7.69%, 8/104). The prevalence of DRMs in ART-experienced PLWH with LLV is high in Zhengzhou City and continuous surveillance can facilitate early intervention and provision of effective treatment.

Isoflavonoids, the major secondary metabolites within the flavonoid biosynthetic pathway, play important roles in plant defense and exhibit free radical scavenging properties in mammals. Recent advancements in understanding the synthesis, transport, and regulation of isoflavonoids have identified their biosynthetic pathways as promising targets for metabolic engineering, offering potential benefits such as enhanced plant resistance, improved biomass, and restoration of soil fertility. This review provides an overview of recent breakthroughs in isoflavonoid biosynthesis, encompassing key enzymes in the biosynthetic pathway, transporters influencing their subcellular localization, molecular mechanisms regulating the metabolic pathway (including transcriptional and post-transcriptional regulation, as well as epigenetic modifications). Metabolic engineering strategies aimed at boosting isoflavonoid content in both leguminous and non-leguminous plants. Additionally, we discuss emerging technologies and resources for precise isoflavonoid regulation. This comprehensive review primarily focuses on model plants and crops, offering insights for more effective and sustainable metabolic engineering approaches to enhance nutritional quality and stress tolerance.

Summary: Accurate tumor diagnosis by pathologists relies on identifying specific morphological characteristics. However, summarizing these unique morphological features in tumor classifications can be challenging. Although deep learning models have been extensively studied for tumor classification, their indirect and subjective interpretation obstructs pathologists from comprehending the model and discerning the morphological features accountable for classifications. In this study, we introduce a new approach utilizing Style Generative Adversarial Networks, which enables a direct interpretation of deep learning models to detect significant morphological characteristics within datasets representing patients with deficient mismatch repair/microsatellite instability-high gastric cancer. Our approach effectively identifies distinct morphological features crucial for tumor classification, offering valuable insights for pathologists to enhance diagnostic accuracy and foster professional growth.

As the main contributor of carbon emissions, the low-carbon transition of the industrial sector is important for achieving the goal of carbon dioxide peaking. Hydrogen-enabled industrial energy systems (HIESs) are a promising way to achieve the low-carbon transition of industrial energy systems, since the hydrogen can be well coordinated with renewable energy sources and satisfy the high and continuous industrial energy demand. In this paper, the long-term capacity expansion planning problem of the HIES is formulated from the perspective of industrial parks, and the targets of carbon dioxide peaking and the gradual decommissioning of existing equipment are considered as constraints. The results show that the targets of carbon dioxide peaking before different years or with different emission reduction targets can be achieved through the developed method, while the economic performance is ensured to some extent. Meanwhile, the overall cost of the strategy based on purchasing emission allowance is three times more than the cost of the strategy obtained by the developed method, while the emissions of the two strategies are same. In addition, long-term carbon reduction policies and optimistic expectations for new energy technologies will help industrial parks build more new energy equipment for clean transformation.

The linear and nonlinear dynamics of a bolted cylindrical shell under a point excitation were experimentally investigated. The tests have been carried out through methods of the hammer test and sweeping frequency test. This paper aims to discover the effect of bolt joints on shell vibration, including the effects of bolt number, tightening torque, and excitation levels. The natural characteristics were analyzed by utilizing natural frequency and mode shapes. The nonlinear dynamic characteristics were analyzed through amplitude-frequency curves. The resonance frequency, resonance amplitude, and damping ratio under different tightening torques and excitation levels were investigated. Results show that: the number of bolts can not only change the value and order of the natural frequencies but also the shapes of the mode; The low tightening torque and larger excitation levels strongly lead to more complex nonlinear dynamics of shell structures.

Abstract Bolt connection is one of the main fixing methods of cylindrical shell structures. A typical bolted connection model is considered as a tuned system. However, in the actual working conditions, due to the manufacturing error, installation error and uneven materials of bolts, there are always random errors between different bolts. To investigate the influence of non-uniform parameters of bolt joint, including the stiffness and the distribution position, on frequency complexity characteristics of cylindrical shell through a statistical method is the main aim of this paper. The bolted joints considered here were simplified as a series of springs with random features. The vibration equation of the bolted joined cylindrical shell was derived based on Sanders’ thin shell theory. The Monte Carlo simulation and statistical theory were applied to the statistical analysis of mode characteristics of the system. First, the frequency and mode shape of the tuned system were investigated and compared with FEM. Then, the effect of the random distribution and the random constraint stiffness of the bolts on the frequency and mode shape were studied. And the statistical analysis on the natural frequencies was evaluated for different mistuned levels. And some special cases were presented to help understand the effect of random mistuning. This research introduces random theory into the modeling of bolted joints and proposes a reference result to interpret the complexity of the modal characteristics of cylindrical shells with non-uniform parameters of bolt joints.

A genome assembly for the Chinese poplar tree, Populus wilsonii, provides a unique resource to guide research into poplar development and breeding efforts.

IntroductionRealgar has a long history ofuse in traditional medicines. However, the mechanism through which Realgar or Realgar-Indigo naturalis formula (RIF) exert therapeutic effects is only partially understood.MethodsIn this study, 60 feces and 60 ileum samples from rats administered with realgar or RIF were collected to examine the gut microbiota.ResultsThe results showed that realgar and RIF influenced different microbiota in both feces and ileum. Compared with realgar, RIF at low dosage (0.1701 g/3 ml) significantly increased the microbiota diversity. LEfSe and random forest analyses showed that the bacterium Bacteroidales was significantly altered after RIF administration, and it was predicted that these microorganisms contribute to the inorganic arsenic metabolic process.DiscussionOur results suggest that realgar and RIF may exert their therapeutic effects through influencing microbiota. The low dose of RIF had greater effects on increasing the diversity of microbiota, and Bacteroidales in feces might participate in the inorganic arsenic metabolic process to exert therapeutic effects for realgar.

This paper proposes an Improved Multivariate Multiscale Dispersion Entropy(IMMDE) combined with Hierarchical Entropy(HE) for vibration signal feature extraction. The traditional coarse-grained calculation is missing the relationship between neighboring sample points in the shift operation, which may lead to missing fault information. Secondly, as the scale increases, the original sequence is gradually shortened, may lead to instability and inaccuracy in entropy estimation when dealing with short-term sequences. The improved coarse-grained calculation method overcomes its limitations to improve the stability, and using the HE method to extract deep fault frequency information from the high and low frequency components of the multivariate signal. Then, the extracted features are dimensioned using the Max-Relevance Min-Redundancy (mRMR) to create a new set of fault features to improve diagnosis efficiency. Finally, the Support Vector Machine(SVM) determines the degree and type of fault. Experiments were conducted with three examples, the results show that IMHMDE can effectively extract the feature information according to mechanical faults’ characteristics and improve the efficiency of fault diagnosis.

In this paper, based on the theory of elastic structure analysis, considering the rotational softening and centrifugal stiffening of the blade, the dynamic model of the fir-tree rotating blade and the macroslip hysteresis model of the dry friction on the contact surface of fir-tree tenon are established. Based on elastic mechanics, the pressure distribution model of fir-tree tenon is innovatively established and the relationship between fit clearance and contact pressure has been derived. After the blade is discretized by the finite element method, the dynamic equation of the blade is solved iteratively by the Newmark-β numerical integration method. According to the dynamic equation of the blade, the influence of the change of the tenon angle on the forced response and contact stress of the blade is derived. Finally, some novel conclusions are obtained by analyzing the influence of pressure distribution, tenon angle, friction coefficient, rotational speed, and aerodynamic excitation on blade vibration characteristics. It provides a scheme and relevant basis for the design and development of tenon blades with the most damping effect at different speeds in industrial practice.

The current evaluation of M&A performance lacks consideration of M&A motives. In this paper, we theoretically analyse and empirically test the effect of network synergy generated by M&A on the degree of realization of corporate M&A motives and the mechanism of its effect by constructing an equity network between a listed company and its subsidiaries within the company. The results show that the greater the variation of internal network node degree and strength, the more beneficial it is to promote the degree of realization of corporate M&A motivation; the results of further mechanism of action tests show that the variation of network node degree and strength has significant effects on economies of scale, economies of scope, and transaction costs; Furthermore, the heterogeneity test finds that the effect of variation of network node degree and strength to promote the degree of realization of corporate M&A motivation is more significant in the case of non-cash payment method and related M&A. This paper extends the study of complex networks to the field of M&A and uniquely explains the paradox of the "high failure rate" of M&A and the increasing activity of M&A activities from the perspective of network synergy, which helps to rationalize the M&A behavior of enterprises and further regulate the M&A behavior of listed companies by regulatory authorities.

Gastric cancer (GC) is a cancer with a high mortality rate. lncRNAs play a role in regulating GC tumorigenesis. In this paper, we analyzed differentially expressed lncRNAs between GC and adjacent normal tissues using multiple bioinformatics tools to identify new potential targets in GC. Cell viability and migration ability were detected using the Cell Counting Kit-8 (CCK-8) and transwell assays, MIR4435-2HG was negatively correlated with the survival rate of GC patients, and by inhibiting the activity of MIR4435-2HG, the viability and migration ability of GC cells could be reduced. In addition, RT- qPCR and western blot to detect gene and protein level expression, transmission electron microscopy and nanoparticle tracking analysis (NTA) to study the efficiency of exosome isolation, and flow cytometry to observe cell differentiation were employed, delivery of MIR4435-2HG shRNA via MKN45 cell-derived exosomes significantly reversed the MKN45 exosome-induced M2 polarization in macrophages. Furthermore, the low expression of MIR4435-2HG in MKN45 cell-derived exosomes inhibited the Jagged1/Notch and JAK1/STAT3 pathways in macrophages; MIR4435-2HG downregulated exosomes were found to significantly inhibit GC tumor growth in vivo by establishing a mouse model. In short, MKN45 cell-derived exosomes deliver lncRNA MIR4435-2HG, which promotes gastric carcinogenesis by inducing macrophage M2 polarization.

Abstract Background The biomanufacturing of d-glucaric acid has attracted increasing interest because it is one of the top value-added chemicals produced from biomass. Saccharomyces cerevisiae is regarded as an excellent host for d-glucaric acid production. Results The opi1 gene was knocked out because of its negative regulation on myo-inositol synthesis, which is the limiting step of d-glucaric acid production by S. cerevisiae. We then constructed the biosynthesis pathway of d-glucaric acid in S. cerevisiae INVSc1 opi1Δ and obtained two engineered strains, LGA-1 and LGA-C, producing record-breaking titers of d-glucaric acid: 9.53 ± 0.46 g/L and 11.21 ± 0.63 g/L d-glucaric acid from 30 g/L glucose and 10.8 g/L myo-inositol in fed-batch fermentation mode, respectively. However, LGA-1 was preferable because of its genetic stability and its superior performance in practical applications. There have been no reports on d-glucaric acid production from lignocellulose. Therefore, the biorefinery processes, including separated hydrolysis and fermentation (SHF), simultaneous saccharification and fermentation (SSF) and consolidated bioprocessing (CBP) were investigated and compared. CBP using an artificial microbial consortium composed of Trichoderma reesei (T. reesei) Rut-C30 and S. cerevisiae LGA-1 was found to have relatively high d-glucaric acid titers and yields after 7 d of fermentation, 0.54 ± 0.12 g/L d-glucaric acid from 15 g/L Avicel and 0.45 ± 0.06 g/L d-glucaric acid from 15 g/L steam-exploded corn stover (SECS), respectively. In an attempt to design the microbial consortium for more efficient CBP, the team consisting of T. reesei Rut-C30 and S. cerevisiae LGA-1 was found to be the best, with excellent work distribution and collaboration. Conclusions Two engineered S. cerevisiae strains, LGA-1 and LGA-C, with high titers of d-glucaric acid were obtained. This indicated that S. cerevisiae INVSc1 is an excellent host for d-glucaric acid production. Lignocellulose is a preferable substrate over myo-inositol. SHF, SSF, and CBP were studied, and CBP using an artificial microbial consortium of T. reesei Rut-C30 and S. cerevisiae LGA-1 was found to be promising because of its relatively high titer and yield. T. reesei Rut-C30 and S. cerevisiae LGA-1were proven to be the best teammates for CBP. Further work should be done to improve the efficiency of this microbial consortium for d-glucaric acid production from lignocellulose.

Purpose: This study aims to evaluate the value of a serum metabolomics-based metabolic signature for locoregionally advanced nasopharyngeal carcinoma (LA-NPC) patients, thereby assisting clinical decisions. Methods: In this retrospective study, a total of 320 LA-NPC patients were randomly divided into a training set (ca. 70%; n = 224) and a validation set (ca. 30%; n = 96). Serum samples were analyzed using widely targeted metabolomics. Univariate and multivariate Cox regression analyses were used to identify candidate metabolites related to progression-free survival (PFS). Patients were categorized into high-risk and low-risk groups based on the median metabolic risk score (Met score), and the PFS difference between the two groups was compared using Kaplan–Meier curves. The predictive performance of the metabolic signature was evaluated using the concordance index (C-index) and the time-dependent receiver operating characteristic (ROC), and a comprehensive nomogram was constructed using the Met score and other clinical factors. Results: Nine metabolites were screened to build the metabolic signature and generate the Met score, which effectively separated patients into low- and high-risk groups. The C-index in the training and validation sets was 0.71 and 0.73, respectively. The 5-year PFS was 53.7% (95% CI, 45.12–63.86) in the high-risk group and 83.0% (95%CI, 76.31–90.26) in the low-risk group. During the construction of the nomogram, Met score, clinical stage, pre-treatment EBV DNA level, and gender were identified as independent prognostic factors for PFS. The predictive performance of the comprehensive model was better than that of the traditional model. Conclusion: The metabolic signature developed through serum metabolomics is a reliable prognostic indicator of PFS in LA-NPC patients and has important clinical significance.

Background: Delineating the lesion area is an important task in image-based diagnosis. Pixel-wise classification is a popular approach to segmenting the region of interest. However, at fuzzy boundaries, such methods usually result in glitches, discontinuity or disconnection, inconsistent with the fact that lesions are solid and smooth. Methods: To overcome these problems and to provide an efficient, accurate, robust and concise solution that simplifies the whole segmentation pipeline in AI-assisted applications, we propose the BézierSeg model which outputs Bézier curves encompassing the region of interest. Results: Directly modeling the contour with analytic equations ensures that the segmentation is connected and continuous, and that the boundary is smooth. In addition, it offers sub-pixel accuracy. Without loss of precision, the Bézier contour can be resampled and overlaid with images of any resolution. Moreover, clinicians can conveniently adjust the curve’s control points to refine the result. Conclusions: Our experiments show that the proposed method runs in real time and achieves accuracy competitive with pixel-wise segmentation models.

This paper presents a method for the protected geographical indication discrimination of Ophiopogon japonicus from Zhejiang and elsewhere using near-infrared (NIR) spectroscopy combined with chemometrics. A total of 3657 Ophiopogon japonicus samples from five major production areas in China were analyzed by NIR spectroscopy, and divided into 2127 from Zhejiang and 1530 from other areas (‘non-Zhejiang’). Principal component analysis (PCA) was selected to screen outliers and eliminate them. Monte Carlo cross validation (MCCV) was introduced to divide the training set and test set according to a ratio of 3:7. The raw spectra were preprocessed by nine single and partial combination methods such as the standard normal variable (SNV) and derivative, and then modeled by partial least squares regression (PLSR), a support vector machine (SVM), and soft independent modeling of class analogies (SIMCA). The effects of different pretreatment and chemometrics methods on the model are discussed. The results showed that the three pattern recognition methods were effective in geographical origin tracing, and selecting the appropriate preprocessing method could improve the traceability accuracy. The accuracy of PLSR after the standard normal variable was better, with R2 reaching 0.9979, while that of the second derivative was the lowest with an R2 of 0.9656. After the SNV pretreatment, the accuracy of the training set and test set of SVM reached the highest values, which were 99.73% and 98.40%, respectively. The accuracy of SIMCA pretreated with SNV and MSC was the highest for the origin traceability of Ophiopogon japonicus, which could reach 100%. The distance between the two classification models of SIMCA-SNV and SIMCA-MSC is greater than 3, indicating that the SIMCA model has good performance.

Abstract An aim of completely blind image quality assessment (BIQA) is to develop algorithms which can grade image quality without any prior knowledge of the images. Here, a new contourlet energy statistics based completely on blind opinion‐unaware BIQA (OU‐BIQA) method is proposed, which can predict the perceptual severity of a range of image distortion types without requiring any prior knowledge. According to the energy distribution of the contourlet sub‐bands of natural images in log‐domain, the lower‐scale sub‐band energy can be predicted by the corresponding higher‐scale sub‐band energies of distorted images. A quality model is then constructed by quantifying the difference between predicted energy and realistic energy. Meanwhile, an effective method for adjusting and compensating an undesired distortion is integrated into the quality model. Experimental results show that the proposed new method outperforms state‐of‐the‐art OU‐BIQA models on relevant portions of TID2013 database, and is competitive on the LIVE IQA database. Moreover, the proposed model is very fast, suggesting a real‐time solution to high‐performance BIQA.

Abstract Background The recalcitrance of lignocellulosic biomass provided technical and economic challenges in the current biomass conversion processes. Lignin is considered as a crucial recalcitrance component in biomass utilization. An in-depth understanding of lignin biosynthesis can provide clues to overcoming the recalcitrance. Laccases are believed to play a role in the oxidation of lignin monomers, leading to the formation of higher-order lignin. In plants, functions of only a few laccases have been evaluated, so little is known about the effect of laccases on cell wall structure and biomass saccharification. Results In this study, we screened a gain-of-function mutant with a significant increase in lignin content from Arabidopsis mutant lines overexpressing a full-length poplar cDNA library. Further analysis confirmed that a Chinese white poplar (Populus tomentosa) laccase gene PtoLAC14 was inserted into the mutant, and PtoLAC14 could functionally complement the Arabidopsis lac4 mutant. Overexpression of PtoLAC14 promoted the lignification of poplar and reduced the proportion of syringyl/guaiacyl. In contrast, the CRISPR/Cas9-generated mutation of PtLAC14 results in increased the syringyl/guaiacyl ratios, which led to integrated enhancement on biomass enzymatic saccharification. Notably, the recombinant PtoLAC14 protein showed higher oxidized efficiency to coniferyl alcohol (precursor of guaiacyl unit) in vitro. Conclusions This study shows that PtoLAC14 plays an important role in the oxidation of guaiacyl deposition on cell wall. The reduced recalcitrance of the PtoLAC14-KO lines suggests that PtoLAC14 is an elite target for cell wall engineering, and genetic manipulation of this gene will facilitate the utilization of lignocellulose.

Reducing the impact of hazy images on subsequent visual information processing is a challenging problem. In this paper, combining with atmospheric scattering model, we propose an end-to-end multi-scale feature multiple parallel fusion network called MMP-Net for single image haze removal. The MMP-Net includes three components: multi-scale CNN module, residual learning module and deep parallel fusion module. 1) In multi-scale CNN module, a multi-scale convolutional neural network (CNNs) is adopted to extract different scales features from whole to local, and these features are fused multiple times in parallel. 2) In residual learning module, residual blocks are introduced to deeply learn detailed features, which can recover more image details. 3) In deep parallel fusion module, those features from residual learning module are deeply merged with the fused features from CNNs, and finally used to recover a clean haze-free image via the atmospheric scattering model. The experimental results show that on the average of three datasets (SOTS, HSTS, and D-Hazy), proposed MMP-Net improves PSNR from 20.91db to 22.21db and SSIM from 0.8720 to 0.9023 over the best state-of-the-art DehazeNet method. What's more, MMP-Net gains the best subjective visual quality on real-world hazy images.

Rhizoma Paridis is a traditional Chinese medicine commonly used in the clinical treatment of gynecological diseases. Previous studies have shown that aqueous extracts of Rhizoma Paridis exhibit some hepatotoxicity to hepatocytes. Here, using lipidomics analysis, we investigated the potential hepatotoxicity of Rhizoma Paridis and its possible mechanism. The hepatic damaging of different solvent extracts of Rhizoma Paridis on zebrafish larvae were determined by a combination of mortality dose, biochemical, morphological, and functional tests. We found that ethyl acetate extracts (AcOEtE) were the most toxic fraction. Notably, lipidomic responsible for the pharmacological effects of AcOEtE were investigated by Q-Exactive HF-X mass spectrometer (Thermo Scientific high-resolution) coupled in tandem with a UHPLC system. Approximately 1958 unique spectral features were detected, of which 325 were identified as unique lipid species. Among these lipid species, phosphatidylethanolamine cardiolipin Ceramide (Cer), lysophosphatidylinositol sphingosine (Sph), etc., were significantly upregulated in the treated group. Pathway analysis indicates that Rhizoma Paridis may cause liver damage via interfering with the glycerophospholipid metabolism. Collectively, this study has revealed previously uncharacterized lipid metabolic disorder involving lipid synthesis, metabolism, and transport that functionally determines hepatic fibrosis procession.

Analysis of the vibration reduction characteristics of shock absorbers is crucial for engines. In this study, the fractal theory was applied to the contact surface of an under-platform damper (UPD), and the influence of the excitation force in the same and opposite directions on the roughness of the contact surface was studied. First, based on fractal geometry theory (FGT), the roughness characterization method of a UPD contact surface was proposed. Then, the friction mechanical model of the rough contact surface was established by combining it with a 3D contact mechanical model. Furthermore, a finite element dynamic model of a blade with a UPD structure was set up. Next, the harmonic balance method was used to calculate the nonlinear response characteristics of a blade under different levels of contact surface roughness. Finally, the influence of the contact surface roughness on the vibration reduction ability of a UPD under different excitation modes was analyzed. According to the simulation results, as the contact surface became rougher, the vibration suppression ability of the UPD on the blade became stronger and stronger. With the change in the centrifugal force of the UPD and the amplitude of the same/reverse excitation force, the influencing law of the contact surface roughness on the vibration suppression ability of the UPD remained unchanged, indicating that the rougher the contact surface roughness, the better the vibration suppression effect.

The vibration dissipation mechanism of the rotating blade with a dovetail joint is studied in this paper. Dry friction damping plays an indispensable role in the direction of vibration reduction. The vibration level is reduced by consuming the total energy of the turbine blade with the dry friction device on the blade-root in the paper. The mechanism of the vibration reduction is revealed by the variation of the friction force and the energy dissipation ratio of dry friction. In this paper, the flexible blade with a dovetail interface feature is discretized by using the spatial beam element based on the finite element theory. Then the classical Coulomb-spring friction model is introduced to obtain the dry friction model on the contact interfaces of the tenon-mortise structure. What is more, the effects of the system parameters (such as the rotating speed, the friction coefficient, the installation angle of the tenon) and the excitation level on blade damping characteristics are discussed, respectively. The results show that the variation of the system parameters leads to a significant change of damping characteristics of the blade. The variation of the tangential stiffness and the position of the external excitation will affect the nonlinear characteristics and vibration damping characteristics.

Light-driven synthetic biology refers to an autotrophic microorganisms-based research platform that remodels microbial metabolism through synthetic biology and directly converts light energy into bio-based chemicals. This technology can help achieve the goal of carbon neutrality while promoting green production. Cyanobacteria are photosynthetic microorganisms that use light and CO2 for growth and production. They thus possess unique advantages as “autotrophic cell factories”. Various fuels and chemicals have been synthesized by cyanobacteria, indicating their important roles in research and industrial application. This review summarized the progresses and remaining challenges in light-driven cyanobacterial cell factory. The choice of chassis cells, strategies used in metabolic engineering, and the methods for high-value CO2 utilization will be discussed.

Abstract Background Congenital tuberculosis is rare and carries a high mortality rate. Our objective was to summarize the current experience of the diagnosis and treatment of patients with congenital tuberculosis. Methods In total, 73 reported cases of congenital tuberculosis published in Chinese and 19 patients with congenital tuberculosis admitted to West China Second University Hospital, Sichuan University, were retrospectively reviewed. Results Sixty-four male and 28 female patients were identified. The majority of the patients were less than 3 weeks old at the time of presentation (range, 0–67 days). With regard to the tuberculosis type, 89 patients had pulmonary tuberculosis, and 20 patients had hepatic tuberculosis. There was active tuberculosis in 71 mothers, no tuberculosis in 12 mothers, and an unknown history of tuberculosis in 9 mothers. Fever, cyanosis, jaundice, shortness of breath, cough, pulmonary moist rales, hepatomegaly, splenomegaly and abdominal distention were the main clinical symptoms at the time of presentation. The abnormal ratios of chest, abdomen and head radiographic images were 97.53, 75 and 81.25%, respectively. The positive rates of acid-fast staining of sputum smears and tuberculosis bacillus DNA were 62.50 and 66.67%, respectively. The misdiagnosis rate was 59.78%. The overall mortality due to congenital tuberculosis was 43.48%. Respiratory failure was the most common cause of death. Sixty-five patients received anti-tuberculosis therapy, and of those, only 16 (15.38%) died. Conclusions The clinical manifestations and radiographic findings of congenital tuberculosis are nonspecific. It is important to thoroughly evaluate the mothers of infants with suspected congenital tuberculosis. Good outcomes can be achieved in infants with the early identification of congenital tuberculosis and early administration of anti-tuberculosis treatment.

Abstract Background Cellulase is the one of the largest contributors to the high production costs of the lignocellulose-based biorefineries. As the most widely used cellulase producer, Trichoderma reesei has two weaknesses, deficiencies in β-glucosidase and cellobiohydrolase II. This work aimed at solving this problem by simultaneous enhancement of the beta–exo synergism and exo–exo synergism in T. reesei cellulase to increase the cellulose degrading capability, i.e. enhanced co-expression of the β-glucosidase gene the cellobiohydrolase II gene of T. reesei. Results Enhanced co-expression of the β-glucosidase gene and the cellobiohydrolase II gene in T. reesei using the strong promoter Pcbh1 was found successful in overcoming the two weaknesses. Filter paper activities of T. reesei cellulase were greatly elevated, which were 7.21 ± 0.45 (E7, Aabgl1 and Trcbh2) and 7.69 ± 0.42 (F6, Anbgl1 and Trcbh2) FPIU/mL. They were much higher than that of the parental strain Rut-C30, 2.45 ± 0.36 FPIU/mL. Enzymatic hydrolysis yields were also improved, from 67.22 ± 1.61% by Rut-C30 cellulase to 87.98 ± 0.65% by E7 cellulase and 86.50 ± 1.01% by F6 cellulase. The substrate loading for 1 g glucose release from SECS were decreased, from 2.9637 g SECS using Rut-C30 cellulase to 2.0291 g SECS using E7 cellulase and 2.0573 g SECS using F6 cellulase. As a result, the efficiency of the process from SECS to glucose was substantially improved. Conclusions Enhanced co-expression of the β-glucosidase gene and the cellobiohydrolase II gene in T. reesei using the strong promoter Pcbh1 in T. reesei was proven triumphal in the simultaneous enhancement of the beta–exo synergism and exo–exo synergism in T. reesei cellulase. This strategy also improved the cellulase production, enzymatic hydrolysis yield and the efficiency of the process from SECS to glucose in the context of on-site cellulase production. This work is a commendable attempt in the cellulase composition optimization at the transcriptional level.

Cadmium (Cd) displays strong toxicity, high mobility, and cannot be degraded, which poses a serious threat to the environment. Cenococcum geophilum (C. geophilum) is one of the most common ectomycorrhizal fungi (ECMF) in the natural environment. In this study, three Cd sensitive and three Cd tolerant strains of C. geophilum were used to analyze the physiological and molecular responses to Cd exposure. The results showed that Cd inhibited the growth of all strains of C. geophilum but had a less toxic effect on the tolerant strains, which may be correlated to a lower content of Cd and higher activity of antioxidant enzymes in the mycelia of tolerant strains. Comparative transcriptomic analysis was used to identify differentially expressed genes (DEGs) of four selected C. geophilum strains after 2 mg/L Cd treatment. The results showed that the defense response of C. geophilum strain to Cd may be closely related to the differential expression of functional genes involved in cell membrane ion transport, macromolecular compound metabolism, and redox pathways. The results were further confirmed by RT-qPCR analysis. Collectively, this study provides useful information for elucidation of the Cd tolerance mechanism of ECMF.

Rice cultivation is one of the most significant human-created sources of methane gas. How to accurately measure the methane concentration produced by rice cultivation has become a major problem. The price of the automatic gas sampler used as a national standard for methane detection (HJ 38-2017) is higher than that of gas chromatography, which greatly increases the difficulty of methane detection in the laboratory. This study established a novel methane detection method based on manual injection and split pattern by changing the parameters of the national standard method without adding any additional automatic gas samplers. The standard curve and correlation coefficient obtained from the parallel determination of methane standard gas were y = 2.4192x + 0.1294 and 0.9998, respectively. Relative standard deviation (RSD,

Visual ship tracking provides crucial kinematic traffic information to maritime traffic participants, which helps to accurately predict ship traveling behaviors in the near future. Traditional ship tracking models obtain a satisfactory performance by exploiting distinct features from maritime images, which may fail when the ship scale varies in image sequences. Moreover, previous frameworks have not paid much attention to weather condition interferences (e.g., visibility). To address this challenge, we propose a scale-adaptive ship tracking framework with the help of a kernelized correlation filter (KCF) and a log-polar transformation operation. First, the proposed ship tracker employs a conventional KCF model to obtain the raw ship position in the current maritime image. Second, both the previous step output and ship training sample are transformed into a log-polar coordinate system, which are further processed with the correlation filter to determine ship scale factor and to suppress the negative influence of the weather conditions. We verify the proposed ship tracker performance on three typical maritime scenarios under typical navigational weather conditions (i.e., sunny, fog). The findings of the study can help traffic participants efficiently obtain maritime situation awareness information from maritime videos, in real time, under different visibility weather conditions.

We aimed to develop a nomogram integrating MRI-based tumor burden features (MTBF), nodal necrosis, and some clinical factors to forecast the distant metastasis-free survival (DMFS) of patients suffering from non-metastatic nasopharyngeal carcinoma (NPC). A total of 1640 patients treated at Sun Yat-sen University Cancer Center (Guangzhou, China) from 2011 to 2016 were enrolled, among which 1148 and 492 patients were randomized to a training cohort and an internal validation cohort, respectively. Additionally, 200 and 257 patients were enrolled in the Foshan and Dongguan validation cohorts, respectively, which served as independent external validation cohorts. The MTBF were developed from the stepwise regression of six multidimensional tumor burden variables, based on which we developed a nomogram also integrating nodal necrosis and clinical features. This model divided the patients into high- and low-risk groups by an optimal cutoff. Compared with those of patients in the low-risk group, the DMFS [hazard ratio (HR): 4.76, 95% confidence interval (CI): 3.39–6.69; p < 0.0001], and progression-free survival (PFS; HR: 4.11, 95% CI: 3.13–5.39; p < 0.0001) of patients in the high-risk group were relatively poor. Furthermore, in the training cohort, the 3-year DMFS of high-risk patients who received induction chemotherapy (ICT) combined with concurrent chemoradiotherapy (CCRT) was better than that of those who were treated with CCRT alone (p = 0.0340), whereas low-risk patients who received ICT + CCRT had a similar DMFS to those who only received CCRT. The outcomes we obtained were all verified in the three validation cohorts. The survival model can be used as a reliable prognostic tool for NPC patients and is helpful to determine patients who will benefit from ICT.

In this work, a continuum model is proposed to simulate and interpret the coupling vibration characteristics of a rotating disk-beam system with the dovetail interfaces. The dovetail interface feature is represented by a macroslip dry friction model. The present study also derives a new mode function to simulate the vibration of a rotating beam with loosely assembled dovetail attachment. The new proposed mode function is validated by comparing the natural characteristics and vibration response with those obtained from a finite element (FE) model. At last, based on the nonlinear response results obtained by the Newmark-β method, the effects of different parameters on the nonlinear dynamics of the coupling system are discussed. The following interesting phenomena have been revealed: the flexible disk can impose different influences on the response characteristics of the rotating beam. The effects of dry friction on the beam’s energy dissipation are significant, especially at a low rotational speed. Further analysis yields that the excitation level and friction coefficient also exhibit a significant impact on the damping effect of dry friction. Consequently, it should be noted that the optimal values of the contact surface’s parameters allow achieving a better damping effect in the engineering practice.

Objective. To investigate the efficacy and safety of the combination use of tegafur and apatinib as a first-line therapy strategy in advanced gastric cancer (GC). Methods. The present study included a total of 62 advanced GC patients. The patients were randomized into the combined group (treated with both tegafur and apatinib) and the control group (treated with only tegafur). Treatment efficacy, KPS score, nutrition condition, and progression-free survival time (PFS) were recorded. Results. Both the response and disease control rates were significantly higher in the combined group. The PFS time was remarkably higher and the KPS score was significantly reduced in the combined group after treatment. After treatment, both groups showed significantly increased nutrition risk, but the rates of patients with nutrition risk or innutrition were remarkably higher in the combined group. The ADR rates were also significantly higher in the combined group. Conclusion. The combination use could achieve good efficacy and prolong patients’ PFS time; however, apatinib also reduced the patients’ quality of life and enhanced the nutrition risk and adverse drug reactions.

Abstract Background Due to the occult anatomic location of the nasopharynx and frequent presence of adenoid hyperplasia, the positive rate for malignancy identification during biopsy is low, thus leading to delayed or missed diagnosis for nasopharyngeal malignancies upon initial attempt. Here, we aimed to develop an artificial intelligence tool to detect nasopharyngeal malignancies under endoscopic examination based on deep learning. Methods An endoscopic images-based nasopharyngeal malignancy detection model (eNPM-DM) consisting of a fully convolutional network based on the inception architecture was developed and fine-tuned using separate training and validation sets for both classification and segmentation. Briefly, a total of 28,966 qualified images were collected. Among these images, 27,536 biopsy-proven images from 7951 individuals obtained from January 1st, 2008, to December 31st, 2016, were split into the training, validation and test sets at a ratio of 7:1:2 using simple randomization. Additionally, 1430 images obtained from January 1st, 2017, to March 31st, 2017, were used as a prospective test set to compare the performance of the established model against oncologist evaluation. The dice similarity coefficient (DSC) was used to evaluate the efficiency of eNPM-DM in automatic segmentation of malignant area from the background of nasopharyngeal endoscopic images, by comparing automatic segmentation with manual segmentation performed by the experts. Results All images were histopathologically confirmed, and included 5713 (19.7%) normal control, 19,107 (66.0%) nasopharyngeal carcinoma (NPC), 335 (1.2%) NPC and 3811 (13.2%) benign diseases. The eNPM-DM attained an overall accuracy of 88.7% (95% confidence interval (CI) 87.8%–89.5%) in detecting malignancies in the test set. In the prospective comparison phase, eNPM-DM outperformed the experts: the overall accuracy was 88.0% (95% CI 86.1%–89.6%) vs. 80.5% (95% CI 77.0%–84.0%). The eNPM-DM required less time (40 s vs. 110.0 ± 5.8 min) and exhibited encouraging performance in automatic segmentation of nasopharyngeal malignant area from the background, with an average DSC of 0.78 ± 0.24 and 0.75 ± 0.26 in the test and prospective test sets, respectively. Conclusions The eNPM-DM outperformed oncologist evaluation in diagnostic classification of nasopharyngeal mass into benign versus malignant, and realized automatic segmentation of malignant area from the background of nasopharyngeal endoscopic images.

Patients with hepatocellular carcinoma require regular follow-up. Here, using Cox-based feature selection to identify key prognostic features, the authors convert time-series follow-up data into a cascading survival map, and show that the approach improves dynamic prognosis prediction for patients.

Aiming at the problem that traditional lung nodules detection method can only get low sensitivities with a lot of false positives, we propose a new framework of ensemble of convolutional neural networks (E-CNNs) and use it to significantly reduce the number of false positive on lung nodules detection in chest radiographs (CXRs). First, unsharp mask technique is used to enhance the nodules in the CXRs. Then, we cut patches in the $229\times229$ image containing or not containing nodule from the enhanced CXRs, which correspond to the positive and negative samples. Third, three optimized CNNs of different input sizes and different depths, namely, CNN1, CNN2 and CNN3, are constructed to detect lung nodule separately, and their input sizes are $12\times12$ , $32\times32$ , and $60\times60$ , and the number of layers are 5, 7, and 9, separately. Finally, a logical AND operator is used to fuse the results of CNN1, CNN2, and CNN3, and E-CNNs are constructed for detecting lung nodules. Our experimental results on the Japanese Society of Radiological Technology database show our proposed E-CNNs attain a sensitivity of 94% and 84% with an average of 5.0 false-positives (FPs) per image and 2.0 FPs per image, respectively, in a five-fold cross-validation test, which far outperforms the state of the art.

In the real application, digital images may undergo the process of acquisition, compression, and transmission, which causes the excess blurring, quantization, and noise. However, the metrics of image quality assessment for multiply distorted images are very limited. In this paper, we propose a new multiscale learning quality-aware features blind image quality assessment algorithm for multiply distorted images by using both local phase and local amplitude. In the new model, a distorted image is decomposed into three scales by Gabor transform, and its phase congruency image (PCI), phase congruency covariance maximum image (PCCmax), and phase congruency covariance minimum image (PCCmin) are produced. Then, we calculate contrast sensitivity function and gray level-gradient co-occurrence matrix features from distorted image and its PCI, PCCmax, and PCCmin, and mean value of intensity of PCI, PCCmax, PCCmin, and overlapping blocked local amplitude of distorted image. At last, SVR is used to build the approximating function between these features and subjective mean opinion scores. Both local phase and local amplitude features are extracted at multi-scale images, which supply more flexibility than the previous single-scale methods in incorporating the variations of viewing scene. Comparative experiments between our proposed metric and the state-of-the-art full-reference and no-reference metrics are conducted on two newly released multiply distorted image databases (LIVEMD and MDID2013) that demonstrate the effectiveness of our proposed method.

Of the salmon sold in China’s consumer market, 92% was labelled as Norwegian salmon, but was in fact was mainly imported from Chile. The aim of this study was to establish an effective method for discriminating the geographic origin of imported salmon using two fingerprint approaches, Near-infrared (NIR) spectroscopy and mineral element fingerprint (MEF). In total, 80 salmon (40 from Norway and 40 from Chile) were tested, and data generated by NIR and MEF were analysed via various chemometrics. Four spectral preprocessing methods, including vector normalization (VN), Savitzky Golay (SG) smoothing, first derivative (FD) and second derivative (SD), were employed on the raw NIR data, and a partial least squares (PLS) model based on the FD + SG9 pretreatment could successfully differentiate Norwegian salmons from Chilean salmons, with a R2 value of 98.5%. Analysis of variance (ANOVA) and multiple comparative analysis were employed on the contents of 16 mineral elements including Pb, Fe, Cu, Zn, Al, Sr, Ni, As, Cr, V, Se, Mn, K, Ca, Na and Mg. The results showed that Fe, Zn, Al, Ni, As, Cr, V, Se, Ca and Na could be used as characteristic elements to discriminate the geographical origin of the imported salmon, and the discrimination rate of the linear discriminant analysis (LDA) model, trained on the above 10 elements, could reach up to 98.8%. The results demonstrate that both NIR and MEF could be effective tools for the rapid discrimination of geographic origin of imported salmon in China’s consumer market.

Objective This study aimed to investigate the clinical features and risk factors of acute kidney injury (AKI) in children with acute paraquat intoxication. Methods A retrospective study of 110 hospitalized children with acute paraquat intoxication in West China Second University Hospital, Sichuan University was conducted from January 2010 to May 2017. The Kaplan–Meier method was used to compare the survival rates of children with different AKI stages. Multivariate logistic regression was applied to analyse the risk factors for paraquat-induced AKI. Results AKI occurred in 42 of 110 (38.2%) children. We observed AKI stage 1 in two (4.8%) children, AKI stage 2 in 11 (26.2%), and AKI stage 3 in 29 (69.0%). The survival rate of children in AKI stage 3 (34.5%) was significantly lower than that in children in AKI stage 2 (63.6%) and AKI stage 1 (100%). Multivariate analysis showed that oral ulcers and elevated blood glucose levels were significant independent risk factors for paraquat-induced AKI in children (odds ratio = 4.223 and 5.545, respectively). Conclusions The incidence and mortality rates of paraquat-induced AKI in children are high. Oral ulcers and elevated blood glucose levels are independent risk factors affecting the occurrence of paraquat-induced AKI in children.

An improved principle is proposed in this paper to achieve a more efficient amplitude suppression of an oscillating pendulum by a controllable moving mass. By establishing the governing equation of the pendulum with a moving mass, several suppression rules are presented to stipulate the motion parameters of the moving mass. The damping ratio is introduced to quantify the suppression effects generated by the mass intermittent motion. With the verification of the accuracy of the present model, some simulation has been taken to get the maximum damping ratio and solve the problem of the nonsynchronous motion. The simulation results show that the new principle is a more powerful control method for the oscillation problem of a pendulum. It is suggested that the new method should carry out the relevant active control experiment in the future research.

A dynamic model of the rotating shrouded blade is established, considering the shroud mass, the Coriolis force, and the centrifugal stiffening effect. And a macroslip model of dry friction with variable normal load is established to simulate the separation-contact-stick-slip state of the shroud. The Lagrangian equation is utilized to solve the differential motion equation, and the Galerkin method is used for discretization. The influence of shroud structure’s parameters such as rotational speed, contact angle, friction coefficient, clearance, and shroud position on the damping effect of the shroud is reviewed by means of amplitude-frequency response and energy through the Newmark-β numerical method. The results demonstrate that the damping effect of the shroud by contact is more obvious than by friction and the amplitude-frequency curve of the shrouded blade shows a strong hard nonlinear phenomenon.

Heavy metals in food packaging materials have been indicated to release into the environment at slow rates. Heavy metal contamination, especially that of cadmium (Cd), is widely acknowledged as a global environment threat that leads to continuous growing pollution levels in the environment. Traditionally, the detection of the concentration of Cd relies on expensive precision instruments, such as inductively coupled plasma mass spectrometry (ICP-MS) and inductively coupled plasma-atomic emission spectrometry (ICP-AES). In this study, an indirect competitive enzyme-linked immunosorbent assay (ic-ELISA) based on a specific monoclonal antibody was proposed to rapidly detect Cd. The half-inhibitory concentration and detection sensitivity of the anti-cadmium monoclonal antibody of the ic-ELISA were 5.53 ng mL−1 and 0.35 ng mL−1, respectively. The anti-Cd monoclonal antibody possessed high specificity while diagnosising other heavy metal ions, including Al (III), Ca (II), Cu (II), Fe (III), Hg (II), Mg (II), Mn (II), Pb (II), Zn (II), Cr (III) and Ni (II). The average recovery rates of Cd ranged from 89.03–95.81% in the spiked samples of packing materials, with intra- and inter-board variation coefficients of 7.20% and 6.74%, respectively. The ic-ELISA for Cd detection was applied on 72 food packaging samples that consisted of three material categories—ceramic, glass and paper. Comparison of the detection results with ICP-AES verified the accuracy of the ic-ELISA. The correlation coefficient between the ic-ELISA and the ICP-AES methods was 0.9634, demonstrating that the proposed ic-ELISA approach could be a useful and effective tool for the rapid detection of Cd in food packaging materials.

Poly-ether-ether ketone (PEEK) is a great potential thermoplastic in industry and medical treatment and health. In this work, PEEK/graphene oxide (GO) and PEEK/MoS2 composites were prepared by a novel hot isostatic pressing method. The addition of GO alters the tribological behaviors mechanism; fatigue wear mechanism is predominant to PEEK/GO composites. However, the combination of abrasive and adhesive wear mechanisms is observed for PEEK/MoS2 composites and PEEK. The reason for this is that the hardness and tensile strength of composites are increased with the appropriate addition of GO. The response time to stable friction state of PEEK/GO and PEEK/MoS2 composites is reduced in comparison with PEEK, which is conducive to shorten running-in time, reduce the energy consumption, and improve the tribological performances of composites. The addition of GO and MoS2 can effectively decrease the friction coefficient and wear rate, and the optimal content of GO and MoS2 was 0.7 wt.% and 15 wt.%, respectively. The results indicate that PEEK/GO and PEEK/MoS2 are impressive composites that possess super tribological properties.

In vascular plants, R2R3-MYB transcription factors are important regulators of secondary cell wall formation. Although 192 annotated R2R3 MYB genes were identified in the poplar genome, only a few members were characterized to participate in the regulation of the secondary cell wall biosynthesis. In this paper, we identify an R2R3-MYB transcription factor, PtoMYB74, which is predicted to be an ortholog of Arabidopsis AtMYB61, a transcription activator that regulates the secondary cell wall formation, lignin biosynthesis, stomatal aperture, and the mucilage of seed coat. PtoMYB74 is mainly expressed in the stems, especially in the xylem tissues and organs. PtoMYB74 as a transcriptional activator is localized to the nucleus. The overexpression of PtoMYB74 increased the secondary cell wall thickness of vessels in transgenic poplar and changed the secondary cell wall compositions. The expression levels of lignin and cellulose biosynthetic genes were elevated in the transgenic poplar overexpressing PtoMYB74 compared to the wild type, while there was no change in the xylan biosynthetic genes. Transcriptional activation assays demonstrated that PtoMYB74 could activate the promoters of structural genes in the lignin and cellulose biosynthetic pathways. Taken together, our data show that PtoMYB74 positively regulates the secondary cell wall biosynthesis in poplar.