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Efficiency and accuracy are major bottlenecks in conducting ecological surveys and acquiring statistical data concerning grassland desertification. Traditional manual ground-based surveys are inefficient, and aerospace-based remote sensing surveys are limited by low spatial resolution and accuracy. In this study, we propose a low-altitude unmanned aerial vehicle (UAV) hyperspectral visible near-infrared (vis-NIR) remote sensing hardware platform, which combines efficiency and accuracy for high-precision remote sensing-based ecological surveys and statistical data collection on grassland desertification. We use the classical deep learning network models VGG and ResNet and their corresponding improved 3D convolutional kernels: 3D-VGG and 3D-ResNet, respectively, to classify the collected data into features. The results show that the two classical models yield good results for vegetation and bare soil in desertified grasslands, and the 3D models yield superior classification results for small sample features. Our results can serve as benchmarks for hardware integration and data analysis for remote sensing-based grassland desertification research and lay the foundation for further finer classifications and more accurate statistics of features., Desertification is a major global environmental problem directly affecting approximately a quarter of the global population, with an estimated total of 10 million hectares of arable land being lost to [...]

High-precision statistics on desertification of grassland features are an important part of grassland ecosystem research. The traditional manual survey is inefficient, and satellite remote sensing has very limited statistical precision, so high-spectral remote sensing by lowaltitude drones is preferable. Here, we report a hyperspectral remote-sensing system for unmanned aerial vehicles (UAVs). We used the vegetation and soil of typical desertified grassland in Inner Mongolia as research objects to collect vis-NIR hyperspectral data on desertification using a deep belief network (DBN), 2D convolutional neural network (2D-CNN), and 3D convolutional neural network (3D-CNN). The results show that these typical deep learning models can effectively classify hyperspectral data on desertified grassland features. The highest classification accuracy was achieved by 3D-CNN, with an overall accuracy of 86.36%. This study enriches the spatial scale of remote sensing research on grassland desertification, and provides a basis for further high-precision statistics and inversion of remote sensing of grassland desertification., The term desertification was first proposed by the French scientist A. Aubreville in 1949. At the 1977 United Nations conference on desertification, it was defined as the decline or destruction [...]

Real-time and high-precision land cover classification is the foundation for efficient and quantitative research on grassland degradation using remote sensing techniques. In view of the shortcomings of manual surveying and satellite remote sensing, this study focuses on the identification and classification of grass species indicating grassland degradation. We constructed a UAV-based hyperspectral remote sensing system and collected field data in grassland areas. By applying artificial intelligence technology, we developed a 3D_RNet-O model based on convolutional neural networks, effectively addressing technical challenges in hyperspectral remote sensing identification and classification of grassland degradation indicators, such as low reflectance of vegetation, flat spectral curves, and sparse distribution. The results showed that the model achieved a classification accuracy of 99.05% by optimizing hyperparameter combinations based on improving residual block structures. The establishment of the UAV-based hyperspectral remote sensing system and the proposed 3D_RNet-O classification model provide possibilities for further research on low-altitude hyperspectral remote sensing in grassland ecology. [ABSTRACT FROM AUTHOR]

In recent years, grassland ecosystems have faced increasingly severe desertification, which has caused continuous changes in the vegetation composition in grassland ecosystems. Therefore, effective research on grassland plant taxa is crucial to exploring the process of grassland desertification. This study proposed a solution by constructing a UAV hyperspectral remote sensing system to collect the hyperspectral data of various species in desert grasslands. This approach overcomes the limitations of traditional grassland survey methods such as a low efficiency and insufficient spatial resolution. A streamlined 2D-CNN model with different feature enhancement modules was constructed, and an improved depth-separable convolution approach was used to classify the desert grassland plants. The model was compared with existing hyperspectral classification models, such as ResNet34 and DenseNet121, under the preprocessing condition of data downscaling by combining the variance and F-norm2. The results showed that the model outperformed the other models in terms of the overall classification accuracy, kappa coefficient, and memory occupied, achieving 99.216%, 98.735%, and 16.3 MB, respectively. This model could effectively classify desert grassland species. This method provides a new approach for monitoring grassland ecosystem degradation. [ABSTRACT FROM AUTHOR]

A calculation model of radial electromagnetic force wave for permanent magnet assisted reluctance motor (PMaSynRM) with rotor slots is proposed in this paper. By introducing complex air gap relative permeance, the improved magnetic potential permeability method is applied to the calculation of electromagnetic force wave of the PMaSynRM. Considering the influence of both stator and rotor slots, the characteristics of electromagnetic force wave are analyzed theoretically. A multi‐physical coupling model of PMaSynRM is established. The natural frequency of the stator core is obtained by modal finite element analysis and modal hammer experiment. The harmonic response is analyzed by loading electromagnetic force wave into the structure field and the vibration on the housing surface is calculated. The results show that although the amplitude of electromagnetic force is small at zero‐order slot frequency, the vibration caused by electromagnetic force at frequency of stator slots and rotor slots, especially at the rotor slot frequency, is the biggest vibration source. The effectiveness and regularity of the calculation model are verified by the prototype vibration experiments. © 2023 Institute of Electrical Engineer of Japan and Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

This paper established a mathematical method for the spectral feature extraction of ratholes, based on UAV hyperspectral imaging technology. The degradation of grasslands is a major challenge to terrestrial ecosystems. Rodents not only promote soil erosion and accelerate the process of grassland degradation, but also carry diseases that can easily cause epidemics. The calculation of the number of rodent holes and grassland vegetation cover is an important indicator for monitoring and evaluating grassland degradation. Manual surveys have drawbacks in efficiently monitoring large areas and are human- and material-costly, hardly meeting the current needs of grassland degradation monitoring. Therefore, there is an urgent need to conduct real-time dynamic monitoring of grassland rathole distributions and grassland degradation processes. In this study, a low-altitude remote sensing platform was constructed by integrating a hyperspectral imager with a UAV to collect spectral data of the desert steppes in central Inner Mongolia Autonomous Region, China. Then, the spectral features of ratholes were extracted via radiation correction, noise reduction, and principal component analysis (PCA). Meanwhile, the spectral features of vegetation and bare soil were extracted based on the normalized difference vegetation index (NDVI), which was inputted to calculate the vegetation cover. The results showed that the single-band map extracted based on PCA could effectively determine the location of ratholes, where the overall accuracy and kappa coefficient were 97% and 0.896, respectively. Therefore, the method proposed in this study can accurately identify the location of desert steppe rodent holes. It provides a high-precision technical means for scientific and effective control of grassland rodent infestation and also provides a higher technical means for grassland degradation. [ABSTRACT FROM AUTHOR]

Aiming to address the rotor eccentricity problem caused by various factors, such as manufacturing, operation and the mass imbalance of the induction motor, the variation law of electromagnetic force wave and vibration response under rotor eccentricity during no-load operation is investigated. To begin with, on the basis of the air-gap permeability, the air-gap magnetic density components under static and dynamic eccentricity are analyzed by using the analytical method. The order and amplitude expressions of the radial electromagnetic force generated by the interaction of harmonics are obtained. Subsequently, a finite element model of the electromagnetic field was developed, and the space-time spectrum of the electromagnetic force was obtained by combining the 2D Fourier analysis. Finally, the electromagnetic force wave is used as a load to investigate the electromagnetic vibration response under different rotor eccentric forms. The effect of rotor eccentricity on the vibration response of the motor is quantitatively analyzed by using the spectral analysis method. The method of analyzing electromagnetic force wave and vibration response can also provide a reference for the same type of motor. [ABSTRACT FROM AUTHOR]

Identifying grass species in grasslands based on unmanned aerial vehicle hyperspectral remote sensing is the basis and premise of hyperspectral remote sensing when applied to grassland degradation monitoring and research. The small targets and mixed pixels involved grass species identification in grasslands creates problems, making identification cumbersome and classification accuracy difficult. This study involved the construction of an unmanned aerial vehicle hyperspectral remote sensing system using hyperspectral data of grass species in desert habitats that had been collected under natural light. A multi‐resolution combined with a 1 × 1 feature map was formed by multiscale convolution, and grass species data were extracted from hyperspectral fine‐grained feature data from grasslands. A recognition and classification model for degradation indicator species CNN was constructed using max pooling to retain the maximum amount of feature detail and up‐sampling, reconstructing the feature space and feature fusion to smooth the edge texture of the data and enhance the weak data to alleviate the imbalance among samples. The results showed that the overall identification accuracy of the model for grassland species reached 98.78%, and the kappa coefficient reached 0.92, realizing the high‐precision identification of grassland species, which laid the foundation for grassland species detection and research based on unmanned aerial vehicle hyperspectral imagery. In addition, the proposed degradation indicator species CNN model provides a useful reference for the identification and classification of small targets with mixed pixels. [ABSTRACT FROM AUTHOR]

Hyperspectral imaging remote sensing can obtain abundant spectral, radiation and spatial information of ground objects, which has been widely used in various fields of national economy. But its narrow band spacing brings not only rich spectral information, but also information redundancy and the difficulty of data processing. Therefore, before the practical application of hyperspectral remote sensing data, band selection is needed to extract spectral features and reduce the data dimension. This review summarizes the research progress of band selection for hyperspectral remote sensing images. Based on the analysis and summary of band selection strategies, the related technology and the latest research status are expounded from six aspects: the evaluation criteria of band selection, the band selection based on the combination of spatial and spectral features, the band selection based on semi-supervised learning, the band selection based on sparse representation, the band selection based on intelligent search and the band selection based on deep learning. Then, the current problems and challenges faced by hyperspectral image band selection are discussed. Finally, the future development direction of hyperspectral image band selection is predicted. [ABSTRACT FROM AUTHOR]

This paper deduces an exact model of analytical calculation for the multilayer rotor eddy current losses of high‐speed permanent magnet machines based on the subdomain method. The analytical calculation model solution domain is divided into six parts of subdomains, including permanent magnet, shielding layer, metal retaining sleeve, air gap, slot openings, and windings. The Laplace equation of the air subdomain and the diffusion equation of the eddy current subdomain and the windings subdomain are established with the vector magnetic potential as the independent variable. The eddy current losses of the permanent magnet, shielding layer, and retaining sleeve of the multilayer rotor are calculated considering the slots effect and eddy current reaction. This analytical model is used to study the interfering factors of the multilayer rotor eddy current losses including the shielding layer thickness, carrier ratio, and modulation ratio. Finally, the correctness and regularity of the analytical calculation model are proved by finite element analysis and machine experiment analysis. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

To effectively optimise pole shape for surface‐mounted permanent magnet synchronous machine (SPMSM), an analytical model of SPMSM with the chamfered pole is proposed for no‐load and on‐load magnetic field calculation. In this model, the pole of SPMSM is approximately segmented into pieces with regular shape and uniform magnet property, and magnetic field parameters can be obtained by subdomain superposition. Meanwhile, iron core saturation is considered to get a correction coefficient to revise air‐gap flux density, inducing flux linkage, line no‐load back electromotive force (EMF) and electromagnetic torque. Based on this analytical model, the geometry optimisation of PM can be optimised by end thickness of pole, pole‐arc coefficient of cutting and remanence, and the waveform total harmonic distortion of air‐gap flux density and no‐load back EMF are greatly reduced. To verify the analytical model, an outer rotor type SPMSM with 20‐poles and 72‐slots for tractor application is designed and manufactured. Finally, the effectiveness of the improved method is validated by the finite‐element method and experimental test. [ABSTRACT FROM AUTHOR]

An inertial particle separator (IPS) mounted before a helicopter engine faces the danger of ice accretion caused by the impingement of super-cooled water droplets. This paper shows the results of a numerical study on the flow and impingement of water droplets in the IPS using the Eulerian–Eulerian method. Cases for different medium volume diameters (MVDs = 5 μm, 10 μm, and 20 µm), liquid water contents (LWCs = 0.5 g/m3, 2 g/m3, and 4 g/m3), and incoming velocities (U0s = 40 m/s, 65 m/s, and 90 m/s) are examined to study their effects on the flow and impingement of water droplets in the IPS. The results indicate that the IPS can reduce the water that enters the core flow path by trapping the water on the inner walls and separating it into the scavenge flow path. The ratio between the flow rate of water at the outlet of the core flow path and that at the inlet ( m ̇ c / m ̇ i n l e t ) decreases with an increased MVD or incoming velocity, which, however, does not change with the LWC. The results also show that the water collection coefficient (β) on the hub and shroud walls increases with a greater MVD, while the β on the splitter wall reaches its maximum at an MVD of 10 µm in the studied cases. The LWC does not have any effect on β for any of the IPS walls, while β increases on all IPS surfaces with the incoming velocity. [ABSTRACT FROM AUTHOR]

A type of sealed steel box was designed to simulate sulfate attack and hydraulic pressure on concrete. Cup-shaped concrete specimens with water/cement (w/c) ratios of 0.4, 0.5, and 0.6 were fabricated. During the 270 days corrosion time, corrosion behavior on concrete surfaces was observed every 30 days. The extent of damage on concrete was calculated on the basis of the results of periodic ultrasonic testing. After the completion of experiments, X-ray fluorescence analysis was conducted on the element contents at different depth locations of partial specimens. Experimental results showed that hydraulic pressure accelerated the sulfate attack on concrete, and high pressure yielded serious damage. In comparison with zero pressure, the accelerating coefficients of 0.1, 0.2, and 0.3 MPa hydraulic pressures were 1.48, 1.75, and 2.35, respectively. Hydraulic sulfate corrosion can bring additional sulfate ions into concrete and cause chemical and physical sulfate corrosions on concrete simultaneously, thereby resulting in serious damage on concrete. The reduction of w/c ratio and incorporation of fly ash are beneficial for concrete to resist hydraulic sulfate attack. [ABSTRACT FROM AUTHOR]

The vibration and noise are a serious problem for large power transformers. The core vibration, as the noise source, is very important to calculate accurately. For the transformers with tanks, vibration calculation is very complicated, considering the complicated propagation path of vibration in the tank and the transformer oil. This paper provides a novel approach to investigate the core vibration of the DFP-270000/500 type super high-voltage generator transformer. Based on the vibration acoustic coupling calculation, the damping coefficient of the core vibration of the transformer is obtained, and the magnetic structural coupling analysis is used for the vibration of the transformer core. To validate the feasibility and applicability of the proposed method, the numerical results obtained from the proposed method are compared with those of experimental ones. [ABSTRACT FROM AUTHOR]

To study the inhibitory effects of chloride ions on concrete sulfate attack in the marine adsorption environment, a series of cubic concrete specimens was fabricated. These specimens were totally submerged or partially submerged in 10% Na2SO4solutions with 0, 0.5, 2, and 5% NaCl concentration. Three specific aspects, namely, superficial phenomenon, compressive strength degradation, and X-ray fluorescence spectrometry analysis, were studied during 450 days of long-term exposure. Results showed that Na2SO4solution had a strong corrosive effect on concrete in both the adsorption and submersion zones, especially in the adsorption zone. Chloride ions exerted inhibitory effects on concrete sulfate attack in both the submersion and adsorption zones, and higher concentration of chloride ions will produce stronger inhibitory effects. However, given the different inhibitory effects of chloride ions on concrete sulfate attack with different corrosion mechanisms, the inhibitory effect of the same chloride concentration on concrete sulfate attack was a little lower in the adsorption zone than in the submersion zone. [ABSTRACT FROM PUBLISHER]

Grassland ecosystems are an important part of terrestrial ecosystems and are important for building ecological barriers, promoting the pastoral economy, and maintaining social stability. In recent decades, grasslands in northern China have undergone extensive degradation due to the combined effects of global climate change and the anthropogenic overuse of grasslands. An understanding of the spatial distribution of grassland degradation species is helpful for evaluating the process of grassland degradation and formulating appropriate protective measures. This is important for grassland degradation monitoring. To address the limitations of traditional ground surveys and realize intelligent remote sensing grassland degradation monitoring tasks, we use unmanned aerial vehicle (UAV) hyperspectral remote sensing technology to collect data on vegetation species in desert grasslands. In this paper, we propose a local-global feature enhancement network (LGFEN) for the classification of desert grassland species. The method uses the local feature enhancement (LFE) module and global feature enhancement (GFE) module to extract local and spatial information from hyperspectral images (HSIs), respectively. In addition, the introduction of the convolutional block attention module (CBAM) refines the features of HSIs, improving the stability of the classification performance. The results show that the proposed method has superior classification performance compared with existing HSI classification methods. With only 10 training samples per class, the overall accuracy, average accuracy, and kappa coefficient of the proposed method were 98.61%, 97.61%, and 0.9815, respectively. The proposed method provides a new approach for high-precision and high-efficiency dynamic monitoring of grassland ecosystems. • A local-global feature enhancement network (LGFEN) is proposed. • Improved efficiency of grassland degradation monitoring. • The LFE module is proposed to implement global feature extraction. • Compared with existing methods, LGFEN has better performance. [ABSTRACT FROM AUTHOR]

Water retting used to degrade pectin in the bast of plant, release and separate fibers normally takes one to two weeks. In this study, radio frequency (RF) was introduced to enhance the retting efficiency in different stages of water retting, and different RF treatment temperatures and durations were used. The pectin loss in phloem part of the RF-treated flax straws, defined as degumming rate, was measured to evaluate retting efficiency besides Fried test. The color, linear density and tensile properties of the resulting fibers were measured. The relationships between retting results and process parameters were established using the response surface methodology, and the way RF functioned in retting process was studied. It was found that RF best improved retting quality of the 2-day, and 6- and 10-day water retting at 40 °C and 90 °C for 60 min, respectively. [ABSTRACT FROM AUTHOR]

Grassland species composition is a key indicator for assessing grassland ecological health. In order to obtain the distribution of species in the desert steppe of Gegen tara, Inner Mongolia, China, we used a new hyperspectral imaging system based on an unmanned aerial vehicle to acquire images. Through spectral transformation, the spectral difference of species was increased. The classification features of desert steppe species were constructed by spectral transformation vegetation indices. The maximum interclass variance was used to compare the reflectance vegetation index, the first order transformation differential vegetation index, the logarithm transformation vegetation index and the continuum removal transformation vegetation index, to select the classification features and to calculate the classification threshold. The classification decision tree model constructed by continuum removal transformation normalized differential vegetation index and continuum removal transformation difference vegetation index has the best effect on desert steppe species classification, and the overall classification accuracy and Kappa coefficient are 87% and 0.8. The classification and identification of keystone species Stipa breviflora Griseb., Artemisia frigida Willd., and Salsola collina Pall. in the desert steppe were realized by this new method. Our study will have a positive effect on the understanding of the evolutionary law of grassland ecosystems, and provide quantitative indicators for grassland ecological management. [ABSTRACT FROM AUTHOR]

The identification and counting of grassland degradation indicator ground objects is an important component of grassland ecological monitoring. These steps are also an important basis for developing ecological restoration and management programs for degraded grasslands. Compared with a traditional human survey, the use of remote sensing images can not only achieve dynamic monitoring of a large area, but also improve the efficiency. Recently, most studies regarding ground object classification based on remote sensing images address the development and optimization of classification models for features in several widely used datasets. For the remote sensing of desertified grasslands, remote sensing images with high spatial resolutions are used for studies on small and sparse features in degraded grasslands. The spatial resolution of the above mentioned datasets yields difficulties when attempting to classify small and sparse indicator features for desertified grasslands because generalization becomes limited. Therefore, establishing a lightweight classification model suitable for degraded grassland features with high spatial resolution is important. In this study, a low altitude unmanned aerial vehicle (UAV) hyperspectral remote sensing platform was constructed to collect high spatial resolution remote sensing images of degraded grasslands. The GDIF-3D-CNN classification model was used to classify the pure pixels and all pixels datasets, whose accuracy and efficiency were further improved by optimizing the eight parameters of the model. This study explores the remote sensing ground object classification of thin small plants and a large number of mixed pixels, realizing high precision classification among desertification degradation indicating plant populations of a species, and provides key quantitative data for grassland degradation research. [ABSTRACT FROM AUTHOR]

• Microwave (MW) pretreatment led to better retting efficiency than radio frequency. • MW enabled flax stems to absorb more water and faster than radio frequency (RF). • MW helped non-presoaked flax to remove more pectin than pure enzymatic retting. • MW pretreatment tended to weaken fibers tensile performance more than RF. • The superiority of MW treatment over radio frequency lay in its higher frequency. Microwave (MW) together with prior water presoaking was used as a pretreatment for enzymatic retting of flax stems in this work. Weight loss, pectin removal, the resulting fibers' properties and the degree of water absorption of the stems after MW pretreatment were measured and analyzed. The effect of MW pretreatment on enzymatic retting was determined and compared with the radio frequency (RF) pretreatment which adopted the same processing parameters. It was found that the 8 h-30 min MW pretreatment improved the enzymatic retting efficiency most, increasing weight loss by 39 %, decreasing pectin content by 10.96 % compared to the control enzymatic retting and obtaining water sorption of 2.23, and produced fibers with reasonable tensile performance. Compared with RF pretreatment, MW pretreatment enabled flax to absorb more water and more energy then got more improvement in the retting efficiency. And the 30 min-MW treatment could improve pectin removal for the non-presoaked flax as compared to the control enzymatic retting, which was different from RF treatment. The enzyme-retted fibers with the same MW and RF pretreatments had close tensile properties, however, their values of the MW-pretreated fibers tended to be slightly lower. It was also found that the tensile performance of the pretreated, enzyme-retted fibers was linked to the amount of energy absorbed, the temperature-maintaining time proportion during MW or RF treatment, and whether the flax had been presoaked or not. [ABSTRACT FROM AUTHOR]

The article undertakes the very important topic of the long-term durability of concrete in a natural draft concrete cooling tower with flue gas injection. The corrosive conditions, including temperature, relative humidity, and CO2 and SO2 gas concentrations, near the inner wall of a cooling tower with flue gas injection were monitored in real time to obtain the long-term durability performance of concrete. The pH and chemical compositions of the condensed liquid that adhered to the tower's inner face and the macromorphology, compressive strength, and neutralization depth of in situ specimens were tested periodically. In addition, a finite element numerical simulation was conducted to simulate and verify the concentration distributions of CO2 and SO2 in the flue gas in the cooling tower. The results showed that the cleaned flue gas was enveloped, diluted, and uplifted by hot vapor in the cooling tower, and its concentration decreased. Meanwhile, the effective diffusion radius increased gradually as the flue gas rose. With the same elevation in the cooling tower, the concentration of flue gas decreased rapidly from the central point to the surrounding area. The air near the inner surface of the cooling tower was merely dampened air with a low concentration of acidic gas due to the gigantic diameter of the cooling tower. As a result, the injection of cleaned flue gas will not evidently increase the corrosion risk in a natural draft concrete cooling tower. [ABSTRACT FROM AUTHOR]

• The 8h-30 min RF pretreatment improved enzymatic retting of flax stems most. • RF pretreatment could encourage flax stems to soak water and swell fast. • The results RF treated the presoaked and non-presoaked flax were different. • RF pretreatment tended to weaken fibers tensile performance, but recoverably. • Fibers tensile parameters were closely linked to the RF pretreatment processing. Radio frequency (RF) pretreatment of different water-presoaking time and RF treatment durations was introduced into enzymatic retting. RF pretreatment was used to degrade non-cellulosic materials and encourage the fast water-absorbing and swelling of the polar components in flax phloem, thus loosen the interfaces between fibers and fiber bundles and facilitate enzymes penetration. Retting efficiency, the resulting fibers properties and the water sorption after RF pretreatment were measured. It was found that the 8h-30min RF pretreatment improved retting efficiency most, increasing weight loss by 47 % and decreasing pectin content by 7.87 % compared to the control enzymatic retting and obtaining water sorption of 2.19. The results RF treated presoaked and non-presoaked flax were found to be different. The RF treatment of 30 min for the non-presoaked stems did not cause any improvement in pectin removal with a percentage decrease in pectin content of -8.41 %. The reason probably was that partial pectic substances in the non-presoaked flax phloem were dried, hardened and compacted during RF treatment. It was also found that RF pretreatment improved fibers whiteness and tended to weaken fibers tensile performance, and how it affected the fibers tensile properties was closely linked to the RF pretreatment processing. [ABSTRACT FROM AUTHOR]

A new time-dependent model for concrete carbonation depth prediction combining with the ageing effects of a coating was established to predict the carbonation depth of concrete with organic film coatings under practical service environmental conditions. This model could be solved by introducing a function about the equivalent concrete thickness of a coating with ageing time. Three coated concrete specimens with epoxy, polyurethane, and chlorinated rubber coatings were fabricated and subjected to natural outdoor experiments of exposure degradation for one year. The coated specimens were collected and subjected to accelerated carbonation experiments with different corresponding ageing periods. Based on these experiments, development models of the coatings’ equivalent concrete thickness with exposure time were obtained through regression analysis, and the carbonation depths of concrete with organic film coatings combined with the ageing of the coatings and repainting effects were obtained through numerical calculation. Results indicated that organic film coatings could improve concrete carbonation resistance effectively, and a coating with denser equivalent concrete thickness could better improve the carbonation resistance of concrete compared with a thinner application. However, this protection would gradually decrease and reach zero because of coating degradation. Coatings would not affect the development of concrete carbonation after reaching the desired service life. The carbonation resistance of concrete could be improved again through effective coating repainting, which could prolong its service life against carbonation. [ABSTRACT FROM AUTHOR]

This study aims to determine the effects of coating category and degradation on chloride resistance and service life of concrete coatings. Four typical coatings were applied on concrete specimens, and aged under outdoor natural climate conditions and indoor artificial accelerated experiments using ultraviolet light radiation and wetting/drying cycle. Coulomb electric fluxes of the specimens were periodically tested to determine their chloride resistance before and during aging. The chloride resistance of concrete is remarkably improved with the use of coatings, and organic film coatings provide superior improvement to infiltrating coatings. The chloride resistance of coatings is time-dependent, and organic film coatings exhibit faster aging than infiltrating coatings. The experimental time needed for coating degradation can be shortened through artificial accelerated aging experiments. The service lives of concrete coatings against chloride resistance are closely related and can be predicted through sunlight irradiance of the service environment. [ABSTRACT FROM AUTHOR]

Increasing evidence has indicated that aberrant expression of miRNAs has been shown to be strongly implicated in the initiation and progression of glioblastoma. Here, we identified a novel tumor suppressive miRNA, miR-564, and investigated its role and therapeutic effect for glioblastoma. We showed that miR-564 was down-regulated in human glioblastoma tissues and cell lines. Introduction of miR-564 dramatically inhibited cell growth and invasion in glioblastoma cells. Subsequent experiments revealed that Transforming growth factor-β1 (TGF-β1) was a direct and functional target of miR-564 in glioblastoma cells. Furthermore, overexpression of miR-564 decreased p-SMAD and SMAD4 expression, which are the downstream signaling molecules of TGF-β. Meanwhile, ectopic of miR-564 reduced the messenger RNA (mRNA) and protein expression of epidermal growth factor receptor (EGFR) and MMP9. Furthermore, the upregulation of miR-564 suppressed TGF-β-mediated U87 proliferation and migration. The expression of EGFR and MMP9 was upregulated in glioblastoma tissues compared to their normal tissues. The EGFR and MMP9 expression levels were inverse correlated with the expression of miR-564. miR-564 suppressed the growth of U87-engrafted tumors. These findings reveal that miR-564/TGF-β1 signaling that may be required for glioblastoma development and may consequently serve as a new therapeutic target for the treatment of glioblastoma., Competing Interests: The authors state that there are no conflicts of interest to disclose.

Background: Excision repair cross complementation group 1 (ERCC1) has been shown to be involved in the progression of glioma susceptibility. However, the results remain conflict. The aim of this study was to systematically review and evaluate the role of ERCC1 C118T and C8092A polymorphisms in glioma risk among Chinese population., Methods: Related case-control studies were searched in online electronic databases. Odds ratio (OR) with its 95% confidence interval (CI) were employed to calculate the extracted data., Results: Total seven articles were retrieved, including 4426 subjects (1926 were glioma patients and 2500 were matched controls). No significant heterogeneity was found between studies (I(2)=0%, P>0.01). Our results demonstrated that A allele and AA genotype of ERCC1 C8092A polymorphism have a positive association with increasing the risk of glioma in the fixed-effect model (A vs. C: OR=1.13, 95% CI=1.02-1.25, P=0.02; AA vs. CC: OR=1.29, 95% CI=1.04-1.61, P=0.02; AA vs. CA+CC: OR=1.25, 95% CI=1.01-1.55, P=0.04). However, no significant relationship was found between C118T variant and glioma susceptibility., Conclusions: Our results indicated that ERCC1 C8092A, not C118T polymorphism might be a biomarker for patients with glioma among Chinese population. Future studies with more ethnicities are needed to explore the precise association.