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In this study, a novel hybrid metaheuristic model was developed to forecast the undrained soil shear (USS) property from cone penetration test (CPT) data (data from bore log sample from 70 different sites in Louisiana). This algorithm produced with the integration of grey wolf optimization (GWO) and multilayer perceptron neural network (MLP), named GWO - MLP, where different numbers of hidden layers were tested (1 to 4). The duty of optimization algorithm was to determine the optimal number of neurons in each hidden layer. To this objective, the system comprised five inputs entitled sleeve friction, cone tip persistence, liquid limit, plastic limitation, too much weight, and USS as outcome. The developed models for forecasting the USS of soil show the proposed best models have R2 at 0.9134 and 0.9236 in the training and predicting stage. Although the total ranking score of GWO-MLP2 and GWO-MLP4 is equal, the OBJ value shows that GWO-MLP4 has better performance than GWO-MLP2. In this case, considering the time of model running and a greater number of hidden layers suggests that GWO-MLP2 could be most appropriate. Therefore, the GWO-MLP3 model outperforms other GWO-MLP networks in the training and testing phase.

The heterogeneity of command-and-control and market-based environmental regulations has been fully discussed. However, the classification of environmental regulations based on target-oriented approaches have not been investigated, especially the differentiated impacts on green total-factor productivity (GTFP). To bridge this gap in the literature, this study divides environmental regulations into energy-saving target (EST) regulations and emission-reduction target (ERT) regulations based on the regulation target, and compares their heterogeneous impacts on GTFP. The GTFP is measured and further decomposed into total-factor economic output efficiency (TFYE), total-factor energy efficiency (TFEE), and total-factor emission efficiency (TFCE) using the extended SBM-DDF model. The empirical research using the panel data of 23 OECD countries from 2004 to 2010 reveals that: (1) The EST regulations have a spillover effect, which can positively affect GTFP and its decomposition terms in the long term. (2) The ERT regulations increase TFYE and TFCE, but reduce GTFP and TFEE. (3) Stricter regulations are more effective in energy conservation and emissions reduction. These findings provide policy implications for governments to effectively achieve environmental governance targets by adjusting and optimizing environmental regulatory instruments.

Reconstruction on the surface of an SCFO perovskite oxide by acid treatment leads to improved OER performance.

The first sodium borate-squarate, Na2(C4O4)(H3BO3)(H2O)4·H3BO3, with strong SHG response obtained by the synergy effect between two planar NLO-active motifs.

Parkinson's disease (PD) is a tricky neurodegenerative disease characterized with motor deficits and gastrointestinal (GI) dysfunction.

A mussel bionic polydopamine-loaded ferrous sulfide nanocomposite was successfully constructed, which showed greatly improved antimicrobial performance via NIR-mediated Fenton reaction.

Dental X-ray image segmentation is helpful for assisting clinicians to examine tooth conditions and identify dental diseases. Fast and lightweight segmentation algorithms without using cloud computing may be required to be implemented in X-ray imaging systems. This paper aims to investigate lightweight deep learning methods for dental X-ray image segmentation for the purpose of deployment on edge devices, such as dental X-ray imaging systems. A novel lightweight neural network scheme using knowledge distillation is proposed in this paper. The proposed lightweight method and a number of existing lightweight deep learning methods were trained on a panoramic dental X-ray image data set. These lightweight methods were evaluated and compared by using several accuracy metrics. The proposed lightweight method only requires 0.33 million parameters ($$\sim 7.5$$ ∼ 7.5 megabytes) for the trained model, while it achieved the best performance in terms of IoU (0.804) and Dice (0.89) comparing to other lightweight methods. This work shows that the proposed method for dental X-ray image segmentation requires small memory storage, while it achieved comparative performance. The method could be deployed on edge devices and could potentially assist clinicians to alleviate their daily workflow and improve the quality of their analysis.

Thyroid hormones (THs) regulate multiple physiological activities in the liver, including cellular metabolism, differentiation, and cell growth, and play important roles in the pathogenesis of hepatocellular carcinoma (HCC). Thyroid peroxidase (TPO) is a key molecule involved in the THs synthesis and signaling pathway. As an epigenetic modification, DNA methylation has a critical role in tumorigenesis with diagnostic potential. However, the connection between THs and DNA methylation has been rarely investigated.The methylation of key TH-related genes was analyzed by in-house epigenome-wide scanning, and we further analyzed the methylation levels of the TPO promotor in 164 sample pairs of HCC and adjacent non-cancerous tissues by Sequenom EpiTYPER assays, and evaluated their clinical implications.We identified that the methylation of the TPO promoter was downregulated in the HCC tissues (P0.0001) with a mean difference ranging from 18.5% to 22.3%. This methylation pattern correlated with several clinical factors, including a multi-satellite tumor, fibrous capsule, and the presence of tumor thrombus. The receiver operator characteristic (ROC) curve analysis further confirmed that the percent methylated reference (PMR) values for TPO were predictive of the tumor [the area under the curve (AUC) ranged from 0.755 to 0.818] and the thrombosis in the HCC patients (the AUC ranged from 0.706 to 0.777).These findings demonstrated that epigenetic alterations of TPO, as indicated by the PMR values, were a potential biomarker for HCC patients with tumor thrombosis.

This study examined empirical correlations among several horizontal and vertical ground-motion intensity measures (IMs), including spectral acceleration (SA), peak ground acceleration (PGA), peak ground velocity, acceleration spectrum intensity, velocity spectrum intensity, displacement spectrum intensity, spectrum intensity, effective peak acceleration (EPA), effective peak velocity (EPV), and effective peak displacement (EPD). The theoretical basis for the prediction equations of EPA, EPV, and EPD were developed based on the ground-motion model (GMM) of SA(T). Horizontal and vertical Next Generation Attenuation (NGA)-West2 GMMs and associated ground motions from active shallow crustal earthquakes in the NGA-West2 database were used to calculate empirical correlations. Fisher ? transformation and nonparametric bootstrapping methods were able to accurately describe the uncertainty caused by the limited sample size. The multivariate normality of the total residuals of the horizontal and vertical ground-motion IMs was verified. The results have shown a moderate correlation between the same IMs of horizontal and vertical ground motions. The difference in correlations between the IMs for two different combination cases (IMi,H–IMj,V and IMj,H–IMi,V) was not significant. The trends of ρlnIMV,lnSAH and ρlnIMH,lnSAV were almost the same, except that ρlnIMV,lnSAH was greater than ρlnIMH,lnSAV in the 0–0.3 s period, except for ρlnPGAV,lnSAH. Moreover, the median correlation coefficients were parametrically fitted to establish a correlation coefficient prediction model. Finally, an example of constructing the conditional distribution using the correlation coefficient models for horizontal and vertical ground motions IMs was given. The correlation coefficient models by this study provide the theoretical basis for the selection of horizontal and vertical ground motions using generalized conditional intensity measure.

Background. Transforming growth factor beta-induced protein (TGFBI, encoded by TGFBI gene), is an extracellular matrix protein, widely expressed in variety of tissues. It binds to collagens type I, II, and IV and plays important roles in the interactions of cell with cell, collagen, and matrix. It has been reported to be associated with myocardial fibrosis, and the latter is an important pathophysiologyical basis of atrial fibrillation (AF). However, the mechanism of TGFBI in AF remains unclear. We aimed to detect the potential mechanism of TGFBI in AF via bioinformatics analysis. Methods. The microarray dataset of GSE115574 was examined to detect the genes coexpressed with TGFBI from 14 left atrial tissue samples of AF patients. TGFBI coexpression genes were then screened using the R package. Using online analytical tools, we determined the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, Gene Ontology (GO) annotation, and protein-protein interaction (PPI) network of TGFBI and its coexpression genes. The modules and hub genes of the PPI-network were then identified. Another dataset, GSE79768 was examined to verify the hub genes. DrugBank was used to detect the potential target drugs. Results. In GSE115574 dataset, a total of 1818 coexpression genes (769 positive and 1049 negative) were identified, enriched in 120 biological processes (BP), 38 cellular components (CC), 36 molecular functions (MF), and 39 KEGG pathways. A PPI-network with average 12.2-degree nodes was constructed. The genes clustered in the top module constructed from this network mainly play a role in PI3K-Akt signaling pathway, viral myocarditis, inflammatory bowel disease, and platelet activation. CXCL12, C3, FN1, COL1A2, ACTB, VCAM1, and MMP2 were identified and finally verified as the hub genes, mainly enriched in pathways like leukocyte transendothelial migration, PI3K-Akt signaling pathway, viral myocarditis, rheumatoid arthritis, and platelet activation. Pegcetacoplan, ocriplasmin, and carvedilol were the potential target drugs. Conclusions. We used microdataset to identify the potential functions and mechanisms of the TGFBI and its coexpression genes in AF patients. Our findings suggest that CXCL12, C3, FN1, COL1A2, ACTB, VCAM1, and MMP2 may be the hub genes.

Osteoarthritis (OA) is a severe inflammation-related disease which leads to cartilage destruction. The retinoic acid receptor gamma (RARγ) has been indicated to be involved in many inflammation processes. However, the role and mechanism of RARγ in cartilage destruction caused by inflammation in OA are still unknown. Here, we demonstrated that the RARγ was highly expressed in chondrocytes of OA patients compared with healthy people and was positively correlated with the damage degree of cartilage in OA. Cytokine TNF-α promoted the transcription and expression of RARγ through activating the NF-κB pathway in OA cartilage. In addition, the overexpression of RARγ resulted in the upregulation of matrix degradation and inflammation associated genes and downregulation of differentiation and collagen production genes in human normal chondrocyte C28/I2 cells. Mechanistically, overexpression of RARγ could increase the level of p-IκBα and p-P65 to regulate the expression of downstream genes. RARγ and IκBα also could interact with each other and had the same localization in C28/I2 cells. Moreover, the SD rats OA model induced by monosodium iodoacetate indicated that CD437 (RARγ agonist) and TNF-α accelerated the OA progression, including more severe cartilage layer destruction, larger knee joint diameter, and higher serum ALP levels, while LY2955303 (RARγ inhibitor) showed the opposite result. RARγ was also highly expressed in OA group and even higher in TNF-α group. In conclusion, RARγ/NF-κB positive feedback loop was activated by TNF-α in chondrocyte to promote cartilage destruction. Our data not only propose a novel and precise molecular mechanism for OA disease but also provide a prospective strategy for the treatment.

For the purpose of better matching the performance of the organic Rankine cycle (ORC) system concerning the vehicle engine waste heat recovery, this paper studies the output performance of free piston expander-linear generator (FPE-LG). A test bench of FPE-LG is established for small scale ORC system, and timing and displacement control strategy is proposed. Furthermore, the impact of the intake pressure and the torque on motion characteristics and output performance of FPE-LG are analyzed. According to evaluating different learning rates, number of hidden artificial neural networks and training functions, a prediction model of FPE-LG based on artificial neural network is established. Genetic algorithm is used to optimize the key operating parameters, to maximize the power output of FPE-LG. In consideration of the mean square error and determination coefficient, the artificial neural network model is verified and tested by experimental data. Finally, combining genetic algorithm with artificial neural network model, the maximum power output of FPE-LG is optimized and its performance is predicted. The results show that the maximum value of electric current, voltage and power output are 2.8 A, 14.75 V and 28.5 W, respectively. Based on artificial neural network, this method can provide useful guidance for performance prediction and coordinated optimization, with advantages of minimum deviation and high precision.

A novel protocol of rhodium-catalyzed tandem C-H annulation of aldehyde and aniline with diazonaphthalen-1(2

BackgroundGalectin-3 is a multi-functional lectin protein and a ligand of mucin-1 (CA15-3), and has been linked to renal fibrosis in animal models and renal function in humans. However, no population study has ever explored the associations with both ligand and receptor. We therefore investigate the independent association of renal function with serum galectin-3 and mucin-1 (CA15-3) in untreated Chinese patients.METHODSThe study participants were outpatients who were suspected of hypertension, but had not been treated with antihypertensive medication. Serum galectin-3 and mucin-1 (CA15-3) concentrations were both measured by the enzyme-linked immunosorbent assay (ELISA) method. Estimated glomerular filtration rate (eGFR) was calculated from serum creatinine by the use of the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation.ResultsThe 1,789 participants included 848 (47.4%) men. Mean (±SD) age was 51.3 ± 10.7 years. Multiple regression analyses showed that eGFR was significantly associated with serum galectin-3 and mucin-1 (CA15-3) concentration (0.68 and 1.32 ml/min/1.73 m2 decrease per 1-SD increase in log transformed serum galectin-3 and mucin-1 (CA15-3) concentration, respectively; P ≤ 0.006). The association of eGFR with serum mucin-1 (CA15-3) concentration was significantly stronger in the overweight (BMI 24.0–27.9 kg/m2) and obese (BMI ≥ 28.0 kg/m2) than in normal weight subjects (BMI < 24.0 kg/m2, P for interaction 0.018). Path analysis showed that serum galectin-3 concentration had both a direct (P = 0.016) and a mucin-1 mediated indirect effect (P = 0.014) on eGFR.ConclusionsBoth circulating galectin-3 and mucin-1 (CA15-3) were significantly associated with renal function. The role of galectin-3 on renal function might be partially via mucin-1.

To investigate the relationship between systemic inflammatory response and short-term mortality in patients with non-cirrhotic chronic severe hepatitis (CSH) by using several indicators of inflammation including neutrophil-to-lymphocyte ratio (NLR), neutrophil (NEU), white blood cell (WBC), platelet-to lymphocyte ratio (PLR), and monocyte-to-lymphocyte ratio (MLR).Data were collected from two prospectively enrolled CATCH-LIFE noncirrhotic cohorts. Cox regression analysis was used to investigate the association between systemic inflammatory biomarkers and 90-day liver transplant (LT)-free mortality. A generalized additive model (GAM) was used to illustrate the quantitative curve relationship between NLR and 90-day LT-free mortality. Kaplan-Meier method was used to estimate the 90-year LT-free survival.The prevalence of CSH was 20.5% (226/1103). The 28-day and 90-day LT-free mortality rates were 17.7% and 26.1%, respectively, for patients with non-cirrhotic CSH. Patients with no infection accounted for 75.0% of all CSH patients, and NLR was independently associated with 90-day LT-free mortality. NLR of 2.9 might be related to disease deterioration in CSH patients without infection.NLR may be an independent risk factor for 90-day LT-free mortality in patients with non-cirrhotic chronic liver disease. A NLR of 2.9 as the cut-off value can be used to predict disease aggravation in CSH patients without infection.

Masked hypertension is difficult to identify and is associated with adverse outcomes. How and to what extent masked hypertension is related to overweight and obesity remain unclear. In participants with a clinic blood pressure (BP) 140/90 mmHg enrolled in a nationwide prospective registry in China, we performed ambulatory and home BP measurements and defined masked hypertension and masked uncontrolled hypertension as an elevated 24-h (≥130/80 mmHg), daytime (≥135/85 mmHg) or nighttime ambulatory BP (≥120/70 mmHg) or an elevated home BP (≥135/85 mmHg). Overweight and obesity were defined as a body mass index of 25.0-29.9 and ≥30.0 kg/m

Purpose. To explore the clinical application of Baihe Dihuang Decoction. To provide certain data support and theoretical basis for the clinical application of Baihe Dihuang Decoction in the future. Methods. With “Baihe Rehmannia Tang” as the search term, the search was carried out on CNKI, VIP, Wanfang, PubMed and other databases. The statistical analysis of Baihe Dihuang decoction for treating diseases was obtained. Meta-analysis of the data was performed using RevMan 5.3 software to analyze the main therapeutic indicators of the disease. Results. According to the 83 valid literature that can be found, it is shown that 17 are used for the treatment of depression, 14 are used for the treatment of menopausal syndrome, 24 are used for the treatment of insomnia, and 28 are used for the treatment of other diseases. Conclusion. In the treatment of depression, menopausal syndrome, and insomnia combined with Baihe Dihuang Decoction can have a better therapeutic effect and diminish the incidence of adverse reactions. It provides a theoretical basis for the study and experimental study of its active components.