Search

Hemp is an environmentally friendly porous fiber, and has good sound absorption properties, which can be used to reduce noise. In recent years, hemp-based composites have been widely studied, but most of them study the preparation methods of materials, Therefore, this paper studies the topic. Firstly, the material and specimens with different thickness and diameter were prepared, then, the standing wave tube method experiment was carried out, and the values of sound absorption coefficient of the specimens were measured and analyzed, while a novel model using genetic algorithm and artificial neural network is proposed. Secondly, the artificial neural network structure was designed, and the training data, verification data, test data are divided and the data is preprocessed. Thirdly, improved genetic algorithm is proposed to design to determine an optimal solution. Fourthly, the optimal solution was as the initial weight and threshold, and were input into the artificial neural network together with training data and verification data. Levenberg Marquardt algorithm were used to train the network. Finally, input the test data into the trained network to test the model. The results showed that there is only a minor deviation between the model output values and the measured values, the values of sound absorption coefficient of specimens with 10 mm thickness are between 0.9 and 1. It was also found that compared with artificial neural network model without genetic algorithm, the proposed model has the lower root mean squared error (RMSE) value, the larger coefficient of determination (R2) value.

Current acoustic modeling methods face problems such as complex processes or inaccurate sound absorption coefficients, etc. Therefore, this paper studies the topic. Firstly, the material samples were prepared, and standing wave tube method experiments were conducted. Material acoustic data were obtained, while a model using improved genetic algorithm and neural network was subsequently proposed. Secondly, the acoustic data obtained from the experiment were analyzed; a neural network structure was designed; and the training, verification, and test data were all divided. In order to facilitate data processing, a symmetrical method was used to inversely normalize all the data. Thirdly, by the design of real coding scheme, fitness function, crossover, and mutation operators, an improved genetic algorithm was proposed to obtain the optimal solution, as the initial weight and threshold, which were then input into the neural network along with the training and verification data. Finally, the test data were input into the trained neural network in order to test the model. The test results and statistical analysis showed that compared with other algorithms, the proposed model has the lower root mean squared error (RMSE) value, the maximum coefficient of determination (R2) value, and shorter convergence time.

For scanning electron microscopes with high resolution and a strong electric field, biomass materials under observation are prone to radiation damage from the electron beam. This results in blurred or non-viable images, which affect further observation of material microscopic morphology and characterization. Restoring blurred images to their original sharpness is still a challenging problem in image processing. Traditional methods can't effectively separate image context dependency and texture information, affect the effect of image enhancement and deblurring, and are prone to gradient disappearance during model training, resulting in great difficulty in model training. In this paper, we propose the use of an improved U-Net (U-shaped Convolutional Neural Network) to achieve image enhancement for biomass material characterization and restore blurred images to their original sharpness. The main work is as follows: use of depthwise separable convolution instead of standard convolution in U-Net to reduce model computation effort and parameters; embedding wavelet transform into the U-Net structure to separate image context and texture information, thereby improving image reconstruction quality; using dense multi-receptive field channel modules to extract image detail information, thereby better transmitting the image features and network gradients, and reduce the difficulty of training. The experiments show that the improved U-Net model proposed in this paper is suitable and effective for enhanced deblurring of biomass material characterization images. The PSNR (Peak Signal-to-noise Ratio) and SSIM (Structural Similarity) are enhanced as well. [ABSTRACT FROM AUTHOR]

The aeronautics and aerospace industries often require special-shaped parts made from lightweight materials with a constant resistance, such as filament winding composite elbows and tees. Filament winding patterns can be realized using numerically controlled filament winding machines. Herein, a 3-axis computer controlled filament winding machine is proposed to solve existing problems with winding of composite elbows such as inconsistent quality, low productivity, and high costs. In this study, a geodesic winding equation for the torus and non-geodesic winding equation for the cylindrical sections of the elbow are provided and the winding angle α' is optimized. Furthermore, the correspondence relationship between the cylindrical and torus section motion is derived. The winding pattern is optimized and tested using the proposed 3-axis filament-winding machine. The results show that the optimal winding pattern design can be easily calculated with a programmable multi-axis controller using a simple control program, and a consistent winding pattern can be achieved. This paper provides a low-cost manufacturing method for the filament winding of composite elbows with cylindrical ends of unequal lengths. [ABSTRACT FROM AUTHOR]

Background . The immoderation of mitochondrial fission is one of the main contributors in ischemia reperfusion injury (IRI) and mesenchymal stromal cells (MSCs) derived extracellular vesicles have been regarded as a potential therapy method. Here, we hypothesized that extracellular vesicles (EVs) derived from human Wharton Jelly mesenchymal stromal cells (hWJMSCs) ameliorate acute renal IRI by inhibiting mitochondrial fission through miR-30b/c/d. Methods . EVs isolated from the condition medium of MCS were injected intravenously in rats immediately after monolateral nephrectomy and renal pedicle occlusion for 45 minutes. Animals were sacrificed at 24 h after reperfusion and samples were collected. MitoTracker Red staining was used to see the morphology of the mitochondria. The expression of DRP1 was measured by western blot. miR-30 in EVs and rat tubular epithelial cells was assessed by qRT-PCR. Apoptosis pathway was identified by immunostaining. Results . We found that the expression of miR-30 in injured kidney tissues was declined and mitochondrial dynamics turned to fission. But they were both restored in EVs group in parallel with reduced cell apoptosis. What is more, when the miR-30 antagomirs were used to reduce the miRNA levels, all the related effects of EVs reduced remarkably. Conclusion . A single administration of hWJMSC-EVs could protect the kidney from IRI by inhibition of mitochondrial fission via miR-30.

Bladder cancer (BC) is the most popular malignant urinary cancer in China. BC has the highest incidence and mortality among all genitourinary system tumors. Although the early-stage BC could be treated with advanced electron flexible systourethroscope, early metastasis of the BC occur frequently, and often results in poor prognosis. Recently, we reported that small ubiquitin related modifier (SUMO)-specific protease 2 (SENP2) was downregulated in BC specimen. SENP2 appeared to inhibit migration and invasion of bladder cancer cells in vitro, through suppressing MMP13 in BC cells. However, the exact underlying mechanisms remain unknown. Here, we reported that SENP2 inhibited nuclear translocation of β-catenin, which targeted the promotor of MMP13 to activate MMP13 to enhance BC cell metastasis. WNT ligands induced TBL1/TBLR1 SUMOylation to form complexes with β-catenin to facilitate β-catenin nuclear translocation, which could be efficiently inhibited through suppression of SUMOylation of TBL1/TBLR1. Together, our data suggest that SENP2 inhibits MMP13 expression in BC cells through de-SUMOylation of TBL1/TBLR1, which inhibits nuclear translocation of β-catenin. Thus, SENP2 may be a promising therapeutic target for BC.

Homeodomain-interacting protein kinase-2 (Hipk2) has been shown to have important regulatory roles in cancer biology, such as cancer cell proliferation, cell cycle, and cell invasion. However, the contributions of Hipk2 to bladder cancer metastasis remain largely unknown. In the current study, we assayed the expression level of Hipk2 in bladder cancer tissues by real-time PCR, and defined its biological functions. We found that Hipk2 levels were downregulated in most bladder cancer tissues compared with adjacent normal tissues, and Hipk2 levels were remarkably decreased in metastasized tumor tissues when compared with primary tumors. SiRNA-mediated Hipk2 silencing increased bladder cancer cell invasion. Hipk2 knockdown resulted in decrease of E-cadherin expression and increase of N-cadherin and fibronectin expression, indicated that epithelial-mesenchymal transition (EMT) was induced. We further demonstrated that Hipk2 knockdown induced Wnt signaling activation and β-catenin nuclear localization. Finally, we confirmed that Hipk2 inhibition promoted EMT and subsequent cell invasion, at least in part by activating Wnt signaling. These data suggest an important role of Hipk2 in regulating metastasis of bladder cancer and implicate the potential application of Hipk2 in bladder cancer therapy., (© 2014 Wiley Periodicals, Inc.)

Unlabelled: Long non-coding RNAs (lncRNAs) play important roles in diverse biological processes, such as transcriptional regulation, cell growth and tumorigenesis. However, little is known about whether lncRNA-GAS5 (growth arrest-specific 5) regulates bladder cancer progression. In the present study, we found that the GAS5 expression is commonly downregulated in bladder cancer cell lines and human specimens. Knockdown of GAS5 promotes bladder cancer cell proliferation, whereas forced expression of GAS5 suppresses cell proliferation. We further demonstrated that knockdown of GAS5 increases CDK6 mRNA and protein levels in bladder cancer cells. Expectedly, GAS5 inhibition induces a significant decrease in G0/G1 phase and an obvious increase in S phase. Gain-of-function and loss-of-function studies showed that GAS5 inhibits bladder cancer cell proliferation, at least in part, by regulating CDK6 expression., Conclusions: Downregulated GAS5 promotes bladder cancer cell proliferation, partly by regulating CDK6, and thus may be helpful in the development of effective treatment strategies against bladder cancer.

Nephrolithiasis is a common disorder worldwide. E-cadherin (CDH1) is involved in epithelial cell-cell interactions and plays important roles in the etiology of nephrolithiasis. We hypothesized that variants in the CDH1 gene are associated with risk of nephrolithiasis. In a hospital-based case-control study of 127 nephrolithiasis patients and 152 controls frequency matched by age and sex, we genotyped the functional -160C>A (rs16260) polymorphism and assessed its associations with risk of nephrolithiasis in a Chinese population. We found that the CA/AA genotypes were associated with a significantly decreased risk of nephrolithiasis (OR = 0.53, 95%CI = 0.32-0.87), compared with the CC genotype, particularly among subgroups of BMI > 24 kg/m(2) (OR = 0.38, 95%CI = 0.17-0.85), age ≤ 57 years (OR = 0.47, 95%CI = 0.24-0.93), and men (OR = 0.56, 95%CI = 0.29-0.99). Our results suggest that the CDH1 polymorphism is involved in the etiology of nephrolithiasis and thus may be a marker for genetic susceptibility to nephrolithiasis.

CXCL12 has been implicated in human carcinogenesis, but the association between the most-studied G801A polymorphism (rs1801157) and the risk of various cancers was reported with inconclusive results. The aim of this study was to assess the association between the CXCL12 G801A polymorphism and cancer risk. A meta-analysis of 17 studies with 3048 cancer patients and 4522 controls was conducted to evaluate the strength of the association using odds ratio (OR) with its 95% confidence interval (CI). The overall results showed that the variant genotypes were associated with a significantly increased risk of all cancer types (OR=1.38, 95%CI=1.18-1.61 for GA versus GG, and OR=1.36, 95%CI=1.17-1.59 for GA/AA versus GG). In the stratified analyses, there was a significantly increased risk for the studies of breast cancer (OR=1.64, 95% CI=1.16-2.33 for AA versus GG, OR=1.42, 95%CI=1.18-1.71 for GA versus GG, and OR=1.44, 95%CI=1.21-1.72 for GA/AA versus GG) and lung cancer (OR=2.86, 95% CI=1.75-4.69 for AA versus GG, OR=1.62, 95% CI=1.20-2.18 for GA vs. GG, OR=1.80, 95% CI=1.36-2.39 for GA/AA versus GG, and OR=2.24, 95%CI=1.41-3.57 for AA versus GA/GG), which remained for the studies of Asian populations and hospital-based control sources. Although some modest bias could not be eliminated, this meta-analysis indicates that the CXCL12 G801A polymorphism is a low-penetrance risk factor for cancer development., (Crown Copyright © 2012. Published by Elsevier B.V. All rights reserved.)