Abstract:This study conducted the three-point bending tests to examine the flexural performance of the basalt textile reinforced alkali-activated slag-fly ash mortar after elevated temperature exposure. The influence of surface coating with the epoxy resin, number of textile layers and matrix type on the high-temperature resistance of basalt textile reinforced mortar specimens was also investigated. The experimental results indicated that the flexural strength of basalt textile reinforced alkali-activated slag-fly ash mortar specimens decreased almost linearly with the increase of temperature due to the deterioration of the matrix and basalt textile. And the failure morphology was also transformed from multiple-cracking mode to single-cracking mode. After heat exposure at 800 ℃ for 1h, the remained flexural strength of the specimens was only 1.67 MPa. Surface coating with epoxy resin enhanced the flexural strength under the exposure temperature below 600 ℃. Due to the decomposition of epoxy resin and the deterioration of the bond between fiber and matrix, significant strength loss can be observed when the exposure temperature was higher than 600 ℃. Compared with the basalt textile reinforced Portland cement mortar specimens, the alkali-activated mortar specimens owned better high-temperature resistance, and less strength loss under the exposure temperature above 400 ℃. An increase in the number of textile layers can enhance the mechanical properties of specimens after exposure to elevated temperatures to a certain extent, but the enhancement gradually weakened with the increase of temperature. And the improvement to the flexural bearing capacity became insignificant for the epoxy coated specimen after the exposure temperature reached 600 ℃.

Abstract:In view of the high cost of cement cementing material filling in Jinchuan mine, the low cost cementitious material was developed with ground granulated blast furnace slag (GGBFS) as the main raw material, and the ratio of the slurry was optimized to meet the requirements of the mine in order to reduce the filling cost. Firstly, physicochemical analysis and particle size gradation analysis of the experimental materials were carried out; Secondly, orthogonal test and range analysis were used to optimize the proportion of new cementitious materials. The optimal proportion was determined as follows: the mass fraction of clinker, desulfurization gypsum（DG） and GGBFS were 8%，14%， and 78%，respectively. XRD and SEM were used to explore the hydration products and their microstructures of the new cementitious materials，and to reveal their hydration mechanism. Finally，on this basis, the filling slurry proportioning test was carried out, and the slurry proportioning was optimized based on multi-attribute decision method with 7 d strength，28d strength，slump，bleeding rate（BR） and filling cost as the evaluation indexes. The results show that that when the composite cementitious material is used，the optimum mass proportion ratio of waste rock rod grinding sand (waste sand ratio) is 7 ∶ 3，the ratio of cement and aggregate is 1 ∶ 4，and the slurry mass fraction is 80%. Moreover，the verification test is carried out with above proportion. The corresponding 7 d strength, 28 d strength，slump and bleeding rate are 4.36 MPa，6.62 MPa，26.8 cm and 11.1%，respectively，which meet the requirements of the mine. And the filling cost is 139 yuan/m3，which is 29.8% lower than the original filling cost of 198 yuan/m3.

Abstract:Agglomerated grains of diamond bonded with Cu-P alloy powder are prepared at various sintered temperatures. Differential thermal analysis（DTA） and X-ray diffraction（XRD） are used to test the melting characteristics and phase composition of the Cu-P alloy. A scanning electron microscope（SEM） is used to analyze the microstructure of the agglomerated grains of diamond, the wettability of diamond and the bond interface. The physical properties such as single particle compressive strength, impact toughness（TI），porosity and average pore size of the agglomerated grains of diamond are tested. Meanwhile, the grinding performance of the agglomerated grains of diamond prepared at various sintering temperatures is compared, and their grinding mechanism is explained. The results indicate that for agglomerated grains of the diamond sintered at 760 ℃，the diamond is well wrapped by Cu-P bond with a good wettability and an appropriate protrusion height. The agglomerated grains of diamond have excellent mechanical properties. Its single particle compressive strength，impact toughness, porosity and average pore size are 23 N，78%，29.33% and 18.53 μm，respectively. The agglomerated grains of the diamond sintered at 760 ℃ show the best grinding performance. After grinding, the agglomerated grains of diamond in the grinding wheel are in a semi-wear state. Moreover，the grinding ratio to zirconia ceramics is 24.8，and the surface roughness is 1.01 μm.

Abstract:Mesophase pitch suffers severe expansion during carbonization due to the escape of light components, which significantly affect the interfacial compatibility of carbon fiber reinforced composites where mesophase pitch is used as binders or matrix. In this work, the effects of oxidation treatment on pitch fibers thermal stability，carbon yield, crystalline structure and dispersivity in alcohol aqueous solution were analyzed by TG, XRD and SEM. The fibers oxidized at 270 ℃ for 150 min were then selected for further study on the influence of carbonization conditions. It was found that the diameter of carbon fibers（CFs） carbonized at 700~900 ℃ changed significantly as observed by the optical microscope. The influence of carbonization temperature on interface compatibility between carbon fiber and mesophase pitch binders in carbon bonded carbon fiber composites was investigated using FTIR and SEM. The results show that the interface between CF carbonization at 500 ℃ and binder was smooth and crack-free, showing excellent interface compatibility. As CFs carbonized at 500 ℃ and mesophase pitch can experience a similar high-temperature carbonization process, during which a major transformation process of carbon structure occurs, the composite can be obtained with enhanced interfacial properties.

Abstract:In order to investigate the performance and modification mechanism of crumb rubber composite modified asphalt with chemical modifier，the conventional indexes such as softening point，5 ℃ ductility，elastic recovery rate，dynamic shear rheology test indexes are used to evaluated its performance. Compared with ordinary rubber-modified asphalt and SBS modified asphalt，the microscopic modification mechanism of crumb rubber composite modified asphalt was conducted by scanning electron microscope，Fourier infrared spectroscopy，and differential scanning calorimetry. The results show that crumb rubber composite modified asphalt has a higher failure temperature for performance grade（PG） of asphalt binder and shows better high-temperature performance. It can be known from the fluorescence microscope test，after 48 hours of storage，only some large rubber powder particles began to be adsorbed by the asphalt micelles and sank in the crumb rubber composite modified asphalt. After 72 hours of storage，the segregation has occurred obviously. Under the microscopic morphology, most of the rubber powders were evenly dispersed in the asphalt，arranged densely，and formed a sub-homogeneous structure in the crumb rubber composite modified asphalt. The infrared spectroscopy and the differential scanning calorimetry tests show that the physical blending modification and the chemical reaction existed simultaneously in the crumb rubber composite modified asphalt. Compared with a single physical modification, under the action of compound modification，the entire system appears a dense cross-linked network structure，which makes the intermolecular bonding firm，and performs better in terms of low-temperature properties.

Abstract:The modified reduced graphene oxide（MR-GO） and modified carbon nanotubes (M-CNT) were obtained through changing their lipophilicity, and then compounded into the base grease. The modification results of nano-particles were characterized by the infrared spectrometer and other equipments. The friction properties of the samples were evaluated by the ball-on-disk friction test and four-ball test. It was found that the lipophilic modification performance weakened the negative effect of carbon nano-particle agglomeration on lubrication, and the lubricating grease containing dual additives had a better anti-friction performance. Under the electron microscope, MR-GO and M-CNT could improve the roughness of the friction surface. Under the cooperation of the two additives, the self-repairing effect of the friction surface was more perfect, the friction coefficient of the friction surface was lower, and it could be more stable with the increase of the friction, thus forming a steady sustainable lubrication.

Abstract:The 304 stainless steel mesh was treated in a boiling solution containing 2 mol·L-1 nickel source for 120 s to obtain a self-supporting electrocatalyst（denoted SS/Ni-OH2M-120s） with excellent Oxygen Evolution Reaction（OER） performance. This self-supporting electrocatalyst facilitated industrialization and scale production. The overpotential of SS/Ni-OH2M-120s electrocatalyst obtained at the current density of 10 mA·cm-2 was 214 mV, which was about 127 mV lower than that of the blank 304 stainless steel mesh. After the constant potential polarization for 10 h at a current density of 20 mA·cm-2，the catalytic performance displayed no obvious change, indicating excellent stability. When SS/Ni-OH2M-120s anode was combined with the Pt mesh cathode（Pt-Mesh//SS/Ni-OH2M-120s） to make overall splitting water, a decomposition voltage of 1.61 V at the current density of 10 mA·cm-2 was achieved, which was 0.23 V lower than the commercial Pt-Mesh//IrO2 /SS.

Abstract:ZL114A alloy is a casting hypoeutectic Al-Si alloy independently developed by Beijing Institute of Aeronautical Materials. The porosity, distribution and morphology of micro-pores have a great influence on the mechanical properties of the alloy. Using density measuring instrument, SEM with EDX, the effects of Y element on the porosity, distribution and morphology of micro-pores of ZL114A ingot were studied in sand casting conditions. The results showed that with the addition of Y，because the Y atomic number is larger，the theoretical density and actual density of ZL114A alloy increased slightly. At the same time，the porosity of the alloy decreased, and the distribution of micro-pores changed from being distributed throughout the alloy matrix to being more distributed in the eutectic region, and the morphology changed from coexistence of particles and networks to network-based ones. Although the Y element had an effect on the porosity, distribution and morphology of micro-pores, the Y element did not play a role by directly interacting with gases in the alloy melt.

Abstract:The existing deep supervised hashing methods cannot effectively utilize the extracted convolution features, but also ignore the role of the similarity information distribution between data pairs on the hash network, resulting in insufficient discrimination between the learned hash codes. In order to solve this problem, a novel deep supervised hashing method called deep priority locally aggregated hashing (DPLAH) is proposed in this paper, which embeds the vector of locally aggregated descriptors (VLAD) into the hash network, so as to improve the ability of the hash network to express the similar data, and reduce the impact of similarity distribution skew on the hash network by imposing different weights on the data pairs. DPLAH experiment is carried out by using the Pytorch deep framework. The convolution features of the Resnet18 network model output are aggregated by using the NetVLAD layer, and the hash coding is learned by using the aggregated features. The image retrieval experiments on the CIFAR-10 and NUS-WIDE datasets show that the mean average precision (MAP) of DPLAH is 11 percentage points higher than that of non-deep hash learning algorithms using manual features and convolution neural network features, and the MAP of DPLAH is 2 percentage points higher than that of asymmetric deep supervised hashing method.

Abstract:In order to reduce the outage probability (OP) of wireless communication and improve the communication performance of the wireless network, this paper investigated a full duplex wireless network with multiple users and relays under the premise of considering aggregation interference and self-interference (SI), and designed a corresponding relay selection scheme. Firstly, based on Nakagami-m fading channels and amplify-and-forward protocol, this paper analyzed the outage performance of the full duplex multi-relay network and provided a new closed-form expression of the OP. Then, based on the idea of maximum weighted matching（MWM），according to the user node's desire for a relay, an algorithm named maximum-carving-matching（MCM） was proposed to realize relay selection. Finally, Monte Carlo method was used to display the change of the system OP under the conditions of different system key parameters, and the effectiveness of the relay selection strategy was verified. The simulation results show that increasing the transmitting power can reduce the system OP，but its improvement effect tends to be saturated after reaching a certain value. After that, increasing the transmitting power can no longer improve the OP. In the saturation state, compared with the existing other relay selection algorithms, the system OP using the MCM algorithm can be reduced by about 4%~7%.

Abstract:The acoustic signal radiated by the helicopter has a slow attenuation speed and a long propagation distance in the air, which is the main basis for recognition of helicopter target. Inspired by the excellent sound signal recognition ability of the human auditory system, an auditory perceptual feature extraction method based on Gammatone cepstral coefficients（GTCC） is proposed to classify helicopter acoustic signal. Through the simulation experiments，the influence of parameter settings on the recognition performance, the robustness of the proposed method in noisy environments, the universal applicability to various classifiers, and the superiority to other helicopter acoustic signal feature extraction methods were studied in detail. Reasonable explanations of the observed experimental results were also given in this paper. The results show that the proposed method can effectively identify the type of helicopter according to the acoustic signal, and has good anti-interference ability to noise, which has certain application prospects. It is also shown that different parameter settings have different effects on the recognition performance, where the length of window function, the number of Gammatone cepstral coefficient features and the low-frequency acoustic signal have a great influence on the recognition accuracy, while high-frequency acoustic signal has little influence on the recognition.

Abstract:To solve the resource scheduling problem in the large-scale cloud computing environment, this paper proposes an improved competitive particle swarm optimization algorithm (ICSO) to improve the efficiency of resource scheduling in cloud computing. Based on the multi-objective comprehensive evaluation model, firstly, the fitness function including task completion time, power consumption and load balance are established. Then, the more evenly distributed initialization particles are generated by the chaos optimization method, and the Gaussian mutation of adaptive probability is introduced to update the position of the victory particles, so as to improve the population diversity and enhance the global search ability. Simulation results show that under the same conditions, the algorithm can find the best scheduling scheme, which is suitable for large-scale resource scheduling, and the results are better than the comparison model.

Abstract:Considering that the existing prediction models of satellite observation task schedulability are difficult to model the potential dependencies between observation tasks with long time interval, a novel predictive model for satellite earth observation task schedulability based on Bidirectional Gated Recursive Unit (Bi-GRU) network is proposed. The model can learn from the historical satellite observation task scheduling results and forecast the observation task scheduling result accurately without a time-consuming scheduling computation. Firstly，the model adopts a multi-layer fully connected forward neural network to extract the relationship between the features of observation tasks. Then，a multi-group and multi-layer Bi-GRU network is designed to formulate the temporal features between the current task and its precursors and successors in task sequence bi-directionally. Lastly，the outputs of Bi-GRU groups are fused in order to enhance the accuracy of the prediction result. The experimental results show that，compared with the state-of-the-art approaches，the accuracy, precision, recall and F1 score of the proposed method are improved by 2.27%, 2.36%, 3.45% and 2.37%, respectively.

Abstract:Limited by the irregularity of graph topology, permutation independence of graph nodes and variability of graph node scale, the majority of neural networks designed for graph classification adopts simple aggregation or sort operation to generate graph-level representation, leading to over-compression and translation of features. In order to address such problems, this paper proposes a novel graph convolutional network, called Globally Aligned Graph Convolutional Network（GAGCN），where graph-level representations are globally aligned by constructing a sub-structural approximate distribution. GAGCN can not only avoid over-compression and feature translation, but also utilize sub-structural distribution to further learn the internal structural similarity among graph data, thereby effectively improving the efficiency of information mining for the downstream classification network and the inference ability for graph classification, respectively. Experimental results show that GAGCN achieves superior results and improves 2%~6% average accuracy on a range of graph datasets，compared with several state-of-the-art graph classification algorithms. The ablation study and the hyper-parameter analysis further reflect the effectiveness and robustness of our approach.

Abstract:The energy of the traditional mixed graph is obtained by calculating the eigenvalues of the matrix in the form of a square matrix，and it is difficult to be extended to large-scale mixed graphs. In response to this problem, this paper applies the network dimension to the mixed graph, and proposes the network energy of the mixed graph, thus the network energy is extended from the undirected graph and the directed graph to the mixed graph. The network energy of a mixed graph can be obtained by the number of nodes and the number of directed and undirected edges of the mixed graph. At the same time，several upper and lower limits of the network energy of the mixed graph are given. Comparied with the Hermitian energy of mixed graph and the network energy of directed and undirected graphs, some important properties of the proposed network energy of the mixed graph are analyzed. The internal relationships among undirected graph, directed graph and mixed graph are also demonstrated.

Abstract:Although the single image dehazing algorithms based on the deep convolutional neural network have made significant progress，there are still some problems, such as poor visibility and artifacts. To overcome these shortcomings，we present a single image dehazing network, taking the encoder-decoder structure as the basic frame and combining the attention mechanism and residual dense block. First，the scheme integrates an encoder, a feature recovery module and the decoder to directly predict the clear images. Then, the residual dense block with attention mechanism is introduced into the dehazing network so as to improve the network's feature extraction ability. Finally, based on the attention mechanism, an adaptive skip connection module is proposed to enhance the network recovering ability for the clear images’ details. Experimental results show that the proposed dehazing network provides better dehazing results on synthetic datasets and real-world images.

Abstract:Aiming at the problem that the parameters of fault diagnosis model are difficult to be optimized of wind turbine pitch system, a fault diagnosis method of wind turbine pitch system based on multi-class optimal margin distribution machine optimized by the state transition algorithm (mcODM-STA) is proposed. In this method, the wind turbine power output is selected as the main state parameter, and Pearson correlation coefficient is used to analyze the historical operation data of wind turbine in wind power data acquisition and monitoring control system, and the features with low correlation of power output state parameters are eliminated. The remaining features are analyzed twice to reduce the sample features. The data set is divided into training set and test set. The training set is used to train the proposed fault diagnosis model, and the test set is used for testing. The operation data of a domestic wind farm is used for experimental verification. Experimental results show that the proposed method has higher fault diagnosis accuracy and Kappa coefficient than other parameter optimization methods.

Abstract:Multiple alkynyl linear polyurethane resins（MAPU） were synthesized by polyaddition reaction using polyethylene adipate diethylene glycol（PADG），isophorone diisocyanate（IPDI） and 1，4-butynediol（BD）. The molecular structures of resins were characterized by Fourier transform infrared spectra and Raman spectra. Series of sulfhydryl-alkynyl UV curing polyurethane films（F-SAPU） and coatings（C-SAPU） were prepared using trimethylolpropane tris（3-mercaptopropionate）（TTMP） as a crosslinking agent. The synthetic and curing process of sulfhydryl-alkynyl UV curing resins were designed according to formulation parameters such as chain extension parameters，mass fraction of hard segment，curing parameters and photoinitiator parameters. The results showed that the tensile strength and elongation at break of F-SAPU were flexibly adjustable from 0.48 MPa to 5.32 MPa and 106% to 172%，respectively，and the glass transition temperature was in the range of -10.1 ℃ to 26.9 ℃ when changing the formulation parameters. In addition, the effect of mass fraction of hard segment on the performance of C-SAPU was explored. When mass fraction of hard segment was 45%，the coating had optimal performance.

Abstract:Non-edible jatropha oil was catalyzed by the sulfurated NiMo/activated clay catalyst to produce the second generation biodiesel. By the method of isovolumetric impregnation plus in-situ activation by CS2，a sulfurated NiMo/activated clay catalyst was prepared, and the structure and performance of the catalyst were studied by XRD, BET, Py-FTIR and NH3-TPD techniques. The effects of different reaction conditions such as reaction temperature, catalyst dosage, hydrogen pressure, reaction time on the reaction were investigated. The experimental results show that the optimal reaction conditions are as follows: the reaction temperature is 300 ℃，the catalyst mass fraction is 7.5%， the initial hydrogen pressure of the reaction is 3.5 MPa, and the reaction time is 60 min. Under these conditions，the conversion ratio of jatropha oil and the selectivity to C15-C18 reached 84.53% and 95.19%，respectively. The main components of optimal product were analyzed. With the sulfurated NiMo/activated clay, the second generation biodiesel with the main components of C15-C18 alkenes was obtained via the reactions of hydrogenation saturation, hydrodeoxygenation, hydrodecarbonylation and cracking.

Abstract:The phosphatidylinositol 3-kinase/protein kinase B (PI3K/AKT) signaling pathway is abnormally activated in hepatocellular carcinoma and promotes the occurrence and development of cancer. In hepatocellular carcinoma, the heat shock protein Hsp70 binding protein 21（Hsp70 binding protein 21） is in a low expression state, and overexpression of HBP21 significantly induces cancer cell apoptosis. Using qRT-PCR technology to detect the mRNA level of HBP21 in liver cancer tissues, it is found that the mRNA level of HBP21 in cancer tissues is lower than that in adjacent tissues. Hepatocellular carcinoma cell Huh7 is treated with insulin to activate the PI3K/AKT signaling pathway in the cells, and the transcription and translation levels of HBP21 in the cells are detected by qRT-PCR technology and Western blotting. With the prolonged insulin treatment time, the mRNA and protein levels of HBP21 show a downward trend. Overexpression of HBP21 in Huh7 cells significantly inhibits insulin-induced phosphorylation of AKT and mammalian target of rapamycin（mTOR）；through ubiquitination and western blotting experiments, it is found that HBP21 does not affect AKT K48 and K63 ubiquitination as well as phosphatase and tensin homolog deleted on chromosome ten（PTEN） protein levels. The inhibitor LY294002 was used to treat Huh7 cells to confirm that HBP21 acts on the PI3K/AKT signaling pathway. Further research shows that HBP21 does not affect the mRNA levels of IRS1 and IRS2, but inhibits the phosphorylation of insulin receptor beta（IRβ） and affects the activation of the PI3K/AKT signaling pathway. In Huh7 cells，HBP21 plays an important role in inhibiting abnormal activation of PI3K/AKT in liver cancer cells. The lack of expression of HBP21 in hepatocellular carcinoma and its inhibition of PI3K/AKT signaling pathway make it possible to become a potential target for cancer treatment.