Epilepsy can be defined as a dysfunction of the brain network,and each type of epilepsy involves different brain-network changes that are implicated diffe rently in the control and propagation of interictal or ictal d...Epilepsy can be defined as a dysfunction of the brain network,and each type of epilepsy involves different brain-network changes that are implicated diffe rently in the control and propagation of interictal or ictal discharges.Gaining more detailed information on brain network alterations can help us to further understand the mechanisms of epilepsy and pave the way for brain network-based precise therapeutic approaches in clinical practice.An increasing number of advanced neuroimaging techniques and electrophysiological techniques such as diffusion tensor imaging-based fiber tra ctography,diffusion kurtosis imaging-based fiber tractography,fiber ball imagingbased tra ctography,electroencephalography,functional magnetic resonance imaging,magnetoencephalography,positron emission tomography,molecular imaging,and functional ultrasound imaging have been extensively used to delineate epileptic networks.In this review,we summarize the relevant neuroimaging and neuroelectrophysiological techniques for assessing structural and functional brain networks in patients with epilepsy,and extensively analyze the imaging mechanisms,advantages,limitations,and clinical application ranges of each technique.A greater focus on emerging advanced technologies,new data analysis software,a combination of multiple techniques,and the construction of personalized virtual epilepsy models can provide a theoretical basis to better understand the brain network mechanisms of epilepsy and make surgical decisions.展开更多
Cross-region innovation is widely recognized as an important source of the long-term regional innovation capacity.In the recent past,a growing number of studies has investigated the network structure and mechanisms of...Cross-region innovation is widely recognized as an important source of the long-term regional innovation capacity.In the recent past,a growing number of studies has investigated the network structure and mechanisms of cross-region innovation collaboration in various contexts.However,existing research mainly focuses on physical effects,such as geographical distance and high-speed railway connections.These studies ignore the intangible drivers in a changing environment,the more digitalized economy and the increasingly solidified innovation network structure.Thus,the focus of this study is on estimating determinants of innovation networks,especially on intangible drivers,which have been largely neglected so far.Using city-level data of Chinese patents(excluding Hong Kong,Macao,and Taiwan Province of China),we trace innovation networks across Chinese cities over a long period of time.By integrating a measure on Information and Communications Technology(ICT)development gap and network structural effects into the general proximity framework,this paper explores the changing mechanisms of Chinese innovation networks from a new perspective.The results show that the structure of cross-region innovation networks has changed in China.As mechanisms behind this development,the results confirm the increasingly important role of intangible drivers in Chinese inter-city innovation collaboration when controlling for effects of physical proximity,such as geographical distance.Since digitalization and coordinated development are the mainstream trends in China and other developing countries,these countries'inter-city innovation collaboration patterns will witness dramatic changes under the influence of intangible drivers.展开更多
Structural network studies could give appropriate opportunities to understanding structural/hydrothermal events,transportation of ore-forming fluids and water/rock interaction process.Four structural deformation/hydro...Structural network studies could give appropriate opportunities to understanding structural/hydrothermal events,transportation of ore-forming fluids and water/rock interaction process.Four structural deformation/hydrothermal events have been identified in the Jiaojia fault zone according to microtexture and deformation of quartz and feldspars.Plagioclase experienced ductile deformation period with bended polysynthetic twin stripes(>450℃)in the early stage,followed by K-feldspar alteration period with ductile-brittle deformation and subgrain rotation recrystallization of quartz(380-450℃).Then,sericitization period occurred extensive ductile-brittle deformation(350-420℃)and extensive subgrain rotation recrystallization with a little bulging recrystallization in quartz.In the last,gold precipitation-related pyrite-sericite-quartz alteration was dominated by brittle deformation(300-380℃)and total bulging recrystallization of quartz.From the K-feldspar alteration zone and sericitization zone to pyrite-sericitequartz alteration zone,fractal dimension values of dynamically recrystallized quartz grains increase from 1.07 and 1.24 to 1.32,the calculated paleo strain rate values of dynamically recrystallized quartz range from 10^-10^.7(380℃)-10^-9.6(450℃)and 10^-9.3(350℃)-10^-8.2(420℃)to 10^-9.5(300℃)-10^-8.0(380℃),and the paleo differential stress values increase from 36.9 and 39.3,to 121.3 MPa.The increase of fractal dimension values and decrease of grain size from pyrite-sericite-quartz alteration zone and sericitization zone to K-feldspar alteration zone decreased average water/rock ratio values,which could lead to different acidity and redox conditions of ore-forming fluids and mineralization differences.Two kinds of orecontrolling fractures have been distinguished which include the gentle dip types(18°-50°)with NW(315°-355°)and SW(180°-235°)dip hosting No.Ⅰorebodies and the steep dip types(74°-90°)with NE(45°-85°)and SE(95°-165°)dip hosting No.Ⅲorebodies.These faults/fractures crosscut altered Linglong granite of footwall of the Jiaojia fault zone as rhombohedrons that promoted the connection between fractures in the K-feldspar alteration zone and fluid flow passages near the main fault face.Research results indicate No.Ⅰand No.Ⅲorebodies should be derived from the same mineralization event and belong to different orebody types in different mineralization sites under the same structural networks.展开更多
We propose molten polymer's entanglement network deformation to be nonaffine and use transient network structural theory with the revised Liu's kinetics rate equation and the revised upper convected Maxwell co...We propose molten polymer's entanglement network deformation to be nonaffine and use transient network structural theory with the revised Liu's kinetics rate equation and the revised upper convected Maxwell constitutive equation to establish a nonaffine network structural constitutive model for studying the rheological behavior of molten Low Density Polyethylene (LDPE) and High Density Polyethylene (HDPE) in oscillatory shear. As a result, when the strain amplitude or frequency increases, the shear stress amplitude increases. At the same time, the accuracy of the nonaffine network model is higher than that of affine network model. It is clear that there is a small amount of nonaffine network deformation for LDPE melts which have long chain branches, and there is a larger amount of nonaffine network deformation in oscillatory shear for HDPE melts which has no long chain branches. So we had better consider the network deformation nonaffine when we establish the constitutive equations of polymer melts in oscillatory shear.展开更多
Superconductive properties for oxides were predicted by artificial neural network (ANN) method with structural and chemical parameters as inputs. The predicted properties include superconductivity for oxides, distribu...Superconductive properties for oxides were predicted by artificial neural network (ANN) method with structural and chemical parameters as inputs. The predicted properties include superconductivity for oxides, distributed ranges of the superconductive transition temperature (Tc) for complex oxides, and Tc values for cuprate superconductors. The calculated results indicated that the adjusted ANN can be used to predict superconductive properties for unknown oxides.展开更多
Extracting useful details from images is essential for the Internet of Things project.However,in real life,various external environments,such as badweather conditions,will cause the occlusion of key target information...Extracting useful details from images is essential for the Internet of Things project.However,in real life,various external environments,such as badweather conditions,will cause the occlusion of key target information and image distortion,resulting in difficulties and obstacles to the extraction of key information,affecting the judgment of the real situation in the process of the Internet of Things,and causing system decision-making errors and accidents.In this paper,we mainly solve the problem of rain on the image occlusion,remove the rain grain in the image,and get a clear image without rain.Therefore,the single image deraining algorithm is studied,and a dual-branch network structure based on the attention module and convolutional neural network(CNN)module is proposed to accomplish the task of rain removal.In order to complete the rain removal of a single image with high quality,we apply the spatial attention module,channel attention module and CNN module to the network structure,and build the network using the coder-decoder structure.In the experiment,with the structural similarity(SSIM)and the peak signal-to-noise ratio(PSNR)as evaluation indexes,the training and testing results on the rain removal dataset show that the proposed structure has a good effect on the single image deraining task.展开更多
This paper investigates information spreading from the perspective of topological phase transition.Firstly,a new hybrid network is constructed based on the small-world networks and scale-free networks.Secondly,the att...This paper investigates information spreading from the perspective of topological phase transition.Firstly,a new hybrid network is constructed based on the small-world networks and scale-free networks.Secondly,the attention mechanism of online users in information spreading is studied from four aspects:social distance,individual influence,content richness,and individual activity,and a dynamic evolution model of connecting with spreading is designed.Eventually,numerical simulations are conducted in three types of networks to verify the validity of the proposed dynamic evolution model.The simulation results show that topological structure and node influence in different networks have undergone phase transition,which is consistent with the phenomenon that followers and individual influence in real social networks experience phase transition within a short period.The infection density of networks with the dynamic evolution rule changes faster and reaches higher values than that of networks without the dynamic evolution rule.Furthermore,the simulation results are compared with the real data,which shows that the infection density curve of the hybrid networks is closer to that of the real data than that of the small-world networks and scale-free networks,verifying the validity of the model proposed in this paper.展开更多
The double-network prepared with an in-situ monomer gel and a fast-crosslinked Cr(III) gel is introduced to develop a thixotropic and high-strength gel (THSG), which is found to have many advantages over the tradition...The double-network prepared with an in-situ monomer gel and a fast-crosslinked Cr(III) gel is introduced to develop a thixotropic and high-strength gel (THSG), which is found to have many advantages over the traditional gels. The THSG gel demonstrates remarkable thermal stability, and no syneresis is observed after 12 months with high salinity brine (95,500 mg/L). Moreover, the SEM and XRD results indicate that the gel is intercalated into the lamellar structures of Na-MMT, where the gel can form a uniform and compact structure. In addition, the THSG gel has an excellent swelling behavior, even in the high salinity brine. In the slim tube experiments, the THSG gel exhibits high rupture pressure and improves blocking capacity after being ruptured. The core flooding results show that a layer of gel filter cake is formed on the face of the fracture, which may be promoted by a high matrix permeability, a small aperture fracture, and a high injection rate. After the gel treatment, the fracture can be completely blocked by the THSG gel. It is found that a high incremental oil recovery (65.3%) can be achieved when the fracture was completely blocked, compared to 40.2% if the gel is ruptured. Although the swelling of ruptured gel can improve oil recovery, part of the injected brine may be channeled through the gel-filled fractures, resulting in a decrease in the sweep efficiency. Therefore, the improved blocking ability by gel swelling (e.g., in fresh water) may be less efficient to contribute to an enhancement of oil recovery. It is also found that the pressure gradient and residual resistance factor to water (Frrw) are higher if the matrix is less permeable, indicating that the fractured reservoir with lower matrix permeability may require a higher gel strength for treatment. The findings of this study may provide novel insights on designing robust double network gels for water shutoff in fractured reservoirs.展开更多
Improving the detection accuracy of rail internal defects and the generalization ability of detection models are not only the main problems in the field of defect detection but also the key to ensuring the safe operat...Improving the detection accuracy of rail internal defects and the generalization ability of detection models are not only the main problems in the field of defect detection but also the key to ensuring the safe operation of high-speed trains.For this reason,a rail internal defect detection method based on an enhanced network structure and module design using ultrasonic images is proposed in this paper.First,a data augmentation method was used to extend the existing image dataset to obtain appropriate image samples.Second,an enhanced network structure was designed to make full use of the high-level and low-level feature information in the image,which improved the accuracy of defect detection.Subsequently,to optimize the detection performance of the proposed model,the Mish activation function was used to design the block module of the feature extraction network.Finally,the pro-posed rail defect detection model was trained.The experimental results showed that the precision rate and F1score of the proposed method were as high as 98%,while the model’s recall rate reached 99%.Specifically,good detec-tion results were achieved for different types of defects,which provides a reference for the engineering application of internal defect detection.Experimental results verified the effectiveness of the proposed method.展开更多
Deep neural networks have achieved tremendous success in various fields,and the structure of these networks is a key factor in their success.In this paper,we focus on the research of ensemble learning based on deep ne...Deep neural networks have achieved tremendous success in various fields,and the structure of these networks is a key factor in their success.In this paper,we focus on the research of ensemble learning based on deep network structure and propose a new deep network ensemble framework(DNEF).Unlike other ensemble learning models,DNEF is an ensemble learning architecture of network structures,with serial iteration between the hidden layers,while base classifiers are trained in parallel within these hidden layers.Specifically,DNEF uses randomly sampled data as input and implements serial iteration based on the weighting strategy between hidden layers.In the hidden layers,each node represents a base classifier,and multiple nodes generate training data for the next hidden layer according to the transfer strategy.The DNEF operates based on two strategies:(1)The weighting strategy calculates the training instance weights of the nodes according to their weaknesses in the previous layer.(2)The transfer strategy adaptively selects each node’s instances with weights as transfer instances and transfer weights,which are combined with the training data of nodes as input for the next hidden layer.These two strategies improve the accuracy and generalization of DNEF.This research integrates the ensemble of all nodes as the final output of DNEF.The experimental results reveal that the DNEF framework surpasses the traditional ensemble models and functions with high accuracy and innovative deep ensemble methods.展开更多
Next-generation networks,including the Internet of Things(IoT),fifth-generation cellular systems(5G),and sixth-generation cellular systems(6G),suf-fer from the dramatic increase of the number of deployed devices.This p...Next-generation networks,including the Internet of Things(IoT),fifth-generation cellular systems(5G),and sixth-generation cellular systems(6G),suf-fer from the dramatic increase of the number of deployed devices.This puts high constraints and challenges on the design of such networks.Structural changing of the network is one of such challenges that affect the network performance,includ-ing the required quality of service(QoS).The fractal dimension(FD)is consid-ered one of the main indicators used to represent the structure of the communication network.To this end,this work analyzes the FD of the network and its use for telecommunication networks investigation and planning.The clus-ter growing method for assessing the FD is introduced and analyzed.The article proposes a novel method for estimating the FD of a communication network,based on assessing the network’s connectivity,by searching for the shortest routes.Unlike the cluster growing method,the proposed method does not require multiple iterations,which reduces the number of calculations,and increases the stability of the results obtained.Thus,the proposed method requires less compu-tational cost than the cluster growing method and achieves higher stability.The method is quite simple to implement and can be used in the tasks of research and planning of modern and promising communication networks.The developed method is evaluated for two different network structures and compared with the cluster growing method.Results validate the developed method.展开更多
The exchanges between cities and counties in the northern slope economic belt of Tianshan Mountains(NSEBTM)are increasingly frequent and the economic linkages are increasingly close,but the spatial distribution of eco...The exchanges between cities and counties in the northern slope economic belt of Tianshan Mountains(NSEBTM)are increasingly frequent and the economic linkages are increasingly close,but the spatial distribution of economic development and linkages among the cities and counties within NSEBTM is uneven.Therefore,it is of great significance to study the evolution of spatial-temporal pattern of the economic linkage network of cities and counties on NSEBTM to promote the coordinated and integrated development of the regional economy on NSEBTM.In this study,we used the modified gravity model and social network analysis method to analyze the spatio-temporal evolution characteristics of the economic linkage network structure of cities and counties on NSEBTM in 2000,2010,and 2020.The results showed that the comprehensive development quality level of cities and counties on NSEBTM increased from 2000 to 2020,its growth rate also increased,and its gap between cities and counties continued expanding.Both the spatial distribution patterns of the comprehensive development quality level of cities and counties on NSEBTM in 2000 and 2010 were presented as“high in the middle and low at both ends”,while the spatial distribution pattern of 2020 was exhibited as“high value and low value staggered”.The total amount of external economic linkages of cities and counties on NSEBTM showed an obvious upward trend,and its gap between cities and counties continued expanding,presenting a pattern of“a strong middle section and weak ends”.The direction of economic linkages of NSEBTM existed obvious central orientation and geographical proximity.The density of economic linkage network of NSEBTM increased from 2000 to 2020,and the structure of economic linkage network changed from single-core structure centered with Urumqi City to multicore structure centered with Urumqi City,Karamay City,Shihezi City,and Changji City,shifting from unbalanced development to balanced development.In the future,we should accelerate the construction of urban agglomeration on NSEBTM,cultivate a modern Urumqi metropolitan area,improve comprehensive development quality of the cities and counties at the eastern and western ends,strengthen the intensity of economic linkages between cities and counties,optimize the economic linkage network,and promote the coordinated and integrated development of regional economy.展开更多
In this work,the structure,viscosity and ion-exchange process of Na_(2)O-MgO-Al_(2)O_(3)-SiO_(2) glasses with different Al_(2)O_(3)/SiO_(2) molar ratios were investigated.The results showed that,with increasing Al_(2)...In this work,the structure,viscosity and ion-exchange process of Na_(2)O-MgO-Al_(2)O_(3)-SiO_(2) glasses with different Al_(2)O_(3)/SiO_(2) molar ratios were investigated.The results showed that,with increasing Al_(2)O_(3)/SiO_(2) ratio,the simple structural units Q_(1) and Q_(2) transformed into highly aggregated structural units Q_(3) and Q_(4),indicating the increase of polymerization degree of glass network.Meanwhile,the coefficient of thermal expansion decreased from 9.23×10^(-6)℃^(-1) to 8.88×10^(-6)℃^(-1).The characteristic temperatures such as melting,forming,softening and glass transition temperatures increased with the increase of Al_(2)O_(3)/SiO_(2) ratio,while the glasses working temperature range became narrow.The increasing Al_(2)O_(3)/SiO_(2) ratio and prolonging ion-exchange time enhanced the surface compressive stress(CS)and depth of stress layer(DOL).However,the increase of ion exchange temperature increased the DOL and decreased the CS affected by stress relaxation.There was a good linear relationship between stress relaxation and surface compressive stress.Chemical strengthening significantly improved the hardness of glasses,which reached the maximum value of(622.1±10)MPa for sample with Al_(2)O_(3)/SiO_(2) ratio of 0.27 after heat treated at 410℃for 2 h.展开更多
The calcium aluminosilicate-based glasses(CaO-Al_(2)O_(3)-SiO_(2),CAS)with different Fe_(2)O_(3)content(0.10wt%,0.50wt%,0.90wt%,and 1.30wt%)were prepared by traditional melt-quenching method.The glass network structur...The calcium aluminosilicate-based glasses(CaO-Al_(2)O_(3)-SiO_(2),CAS)with different Fe_(2)O_(3)content(0.10wt%,0.50wt%,0.90wt%,and 1.30wt%)were prepared by traditional melt-quenching method.The glass network structure,thermal and mechanical properties,and crystallization behavior changes were investigated by nuclear magnetic resonance spectrometer,Fourier-transform infrared spectro-photometer,X-ray diffractometer,differential scanning calorimetry and field emission scanning electron microscope measurements.The change of Q^(n)in glass structures reveals the glass network connectivity decreases due to the increasing content of Fe_(2)O_(3)addition,resulting in the increasing of non-bridging number in glass structure.The glass densities slightly rise from 2.644 to 2.681 g/cm^(3),while Vickers’s hardness increases at first,from 6.469 to 6.901 GPa,then slightly drops to 6.745 GPa,with Fe_(2)O_(3)content increase.There is almost no thermal expansion coefficient change from different Fe_(2)O_(3)content.The glass transmittance in visible range gradually decreases with higher Fe_(2)O_(3)content,resulting from the strong absorption of Fe^(2+)and Fe^(3+)ions.The calculated activation energy from thermal analysis results first decreases from 282.70 to 231.18 kJ/mol,and then increases to 244.02 kJ/mol,with the Fe_(2)O_(3)content increasing from 0.10wt%to 1.30wt%.Meanwhile,the maximum Avrami constant of 2.33 means the CAS glasses exhibit two-dimensional crystallization.All of the CAS glass-ceramics samples contain main crystal phase of anorthite,the microstructure appears lamellar and columnar crystals.展开更多
In this paper,we introduce a novel Multi-scale and Auto-tuned Semi-supervised Deep Subspace Clustering(MAS-DSC)algorithm,aimed at addressing the challenges of deep subspace clustering in high-dimensional real-world da...In this paper,we introduce a novel Multi-scale and Auto-tuned Semi-supervised Deep Subspace Clustering(MAS-DSC)algorithm,aimed at addressing the challenges of deep subspace clustering in high-dimensional real-world data,particularly in the field of medical imaging.Traditional deep subspace clustering algorithms,which are mostly unsupervised,are limited in their ability to effectively utilize the inherent prior knowledge in medical images.Our MAS-DSC algorithm incorporates a semi-supervised learning framework that uses a small amount of labeled data to guide the clustering process,thereby enhancing the discriminative power of the feature representations.Additionally,the multi-scale feature extraction mechanism is designed to adapt to the complexity of medical imaging data,resulting in more accurate clustering performance.To address the difficulty of hyperparameter selection in deep subspace clustering,this paper employs a Bayesian optimization algorithm for adaptive tuning of hyperparameters related to subspace clustering,prior knowledge constraints,and model loss weights.Extensive experiments on standard clustering datasets,including ORL,Coil20,and Coil100,validate the effectiveness of the MAS-DSC algorithm.The results show that with its multi-scale network structure and Bayesian hyperparameter optimization,MAS-DSC achieves excellent clustering results on these datasets.Furthermore,tests on a brain tumor dataset demonstrate the robustness of the algorithm and its ability to leverage prior knowledge for efficient feature extraction and enhanced clustering performance within a semi-supervised learning framework.展开更多
Structure learning of Bayesian networks is a wellresearched but computationally hard task.For learning Bayesian networks,this paper proposes an improved algorithm based on unconstrained optimization and ant colony opt...Structure learning of Bayesian networks is a wellresearched but computationally hard task.For learning Bayesian networks,this paper proposes an improved algorithm based on unconstrained optimization and ant colony optimization(U-ACO-B) to solve the drawbacks of the ant colony optimization(ACO-B).In this algorithm,firstly,an unconstrained optimization problem is solved to obtain an undirected skeleton,and then the ACO algorithm is used to orientate the edges,thus returning the final structure.In the experimental part of the paper,we compare the performance of the proposed algorithm with ACO-B algorithm.The experimental results show that our method is effective and greatly enhance convergence speed than ACO-B algorithm.展开更多
Reticulated polyurethane was chosen as the preceramic material for preparing the porous preform using the replication process. The immersing and sintering processes were each performed twice for fabricating a high-por...Reticulated polyurethane was chosen as the preceramic material for preparing the porous preform using the replication process. The immersing and sintering processes were each performed twice for fabricating a high-porosity and super-strong skeleton. The aluminum magnesium matrix composites reinforced with three-dimensional network structure were prepared using the infiltration technique by pressure assisting and vacuum driving. Light interfacial reactions have played a profitable role in most of the ceramic-metal systems. The metal matrix composites interpenetrated with the ceramic phase have a higher wear resistance than the metal matrix phase. The volume fraction of ceramic reinforcement has a significant effect on the abrasive wear, and the wear rate can be decreased with the increase of the volume fraction of reinforcement.展开更多
In this paper, the general efficiency, which is the average of the global efficiency and the local efficiency, is defined to measure the communication efficiency of a network. The increasing ratio of the general effic...In this paper, the general efficiency, which is the average of the global efficiency and the local efficiency, is defined to measure the communication efficiency of a network. The increasing ratio of the general efficiency of a small-world network relative to that of the corresponding regular network is used to measure the small-world effect quantitatively. The more considerable the small-world effect, the higher the general efficiency of a network with a certain cost is. It is shown that the small-world effect increases monotonically with the increase of the vertex number. The optimal rewiring probability to induce the best small-world effect is approximately 0.02 and the optimal average connection probability decreases monotonically with the increase of the vertex number. Therefore, the optimal network structure to induce the maximal small-world effect is the structure with the large vertex number (〉 500), the small rewiring probability (≈0.02) and the small average connection probability (〈 0.1). Many previous research results support our results.展开更多
The construction of high-speed rail(HSR)network has promoted the social-economic ties of cities,accelerated the compression of time and space,and changed the pattern of regional development.In this paper,with the adop...The construction of high-speed rail(HSR)network has promoted the social-economic ties of cities,accelerated the compression of time and space,and changed the pattern of regional development.In this paper,with the adoption of the operation frequency data of HSR from 12306 website,and based on the HSR connection strength model and social network analysis model,as well as according to the HSR connection strength,HSR network density,centrality,agglomeration subgroup,and other indicators,we analyzed the characteristics of HSR network structure in Northeast China.Results show that the number of HSR cities in Northeast China is small,cities in HSR network generally exhibit weak connectivity,and the existence of HSR network marginalizes cities such as Ulanhot,Baicheng,and Songyuan,which significantly reduce the overall network connectivity of Northeast China.The overall centrality of HSR network in Northeast China is characterized by“one axis,four edges”;specifically,the one axis is located in Harbin-Dalian transportation line and the four edges are located on both sides of the main axis of Harbin-Dalian transportation line.Eight agglomeration subgroups(four double city subgroups and four multi city subgroups)have formed in Northeast China.The core status of Shenyang in HSR network is improved significantly,and“one axis and two wings”HSR network in Liaoning Province is improved significantly.With the gradual expansion of Chaoyang-Fuxin,Dandong-Benxi,and Jilin-Yanji branch networks,the“point axis”HSR network mode in Northeast China has gradually developed and matured.In the future,it is recommended to rely on eight agglomerating subgroups to encrypt HSR network structure,create secondary node central cities,and gradually build a new pattern of opening up in Northeast China.展开更多
Two crystals of receptor 1, C(42)H(52)N(10)O4S2(anthracene-9,10-dicarbaldehyde bis-(phenyl-semithiocarbazone)) and-1-H2PO4, C(68)H(114)N(10)O(10)P2S2 were obtained at room temperature successfully, a...Two crystals of receptor 1, C(42)H(52)N(10)O4S2(anthracene-9,10-dicarbaldehyde bis-(phenyl-semithiocarbazone)) and-1-H2PO4, C(68)H(114)N(10)O(10)P2S2 were obtained at room temperature successfully, and their structures were characterized by X-ray crystallography diffraction. X-ray diffraction reveals that, receptor 1 crystallizes in monoclinic, space group P21/c, with a = 9.487(3),b = 20.674(6), c = 11.821(4)A, β = 113.416(8)o, Mr = 825.06, V = 2127.5(12) A^3, Z = 2, Dc = 1.288g/cm^3, μ = 0.18 mm^-1, F(000) = 876, MoK α radiation(λ = 0.71073 A), the final R = 0.0472 and wR = 0.0930. A total of 3758 unique reflections were collected, of which 3313 with I 〉 2σ(I) were observed. Compound 1-H2PO4^-crystallizes in triclinic, space group P21/n, with a = 8.767(1), b =13.6190(15), c = 16.615(2) ?, α = 98.727(14), β = 103.061(14), γ = 91.382(16)°, Mr = 1357.75, V =1906.6(4) A^3, Z = 1, Dc = 1.183 g/cm^3, μ = 0.17 mm-(-1), F(000) = 734, MoK α radiation(λ = 0.71073?), the final R = 0.0769 and wR = 0.1884. A total of 6699 unique reflections were collected, of which 2989 with I 〉 2σ(I) were observed. As it was observed in the crystal structure of 1-H2PO4^-, 1bound H2PO4^-at a 1:2 ratio by intermolecular interaction of N-H···O hydrogen bond obviously.Another interesting feature was that H2PO4--groups assembled chains themselves via intramolecular hydrogen bond O-H···O and connected the 1 molecules together through the interaction of H-bonds,which improved the planarity of 1 and increased the stability of the entire structure.展开更多
基金supported by the Natural Science Foundation of Sichuan Province of China,Nos.2022NSFSC1545 (to YG),2022NSFSC1387 (to ZF)the Natural Science Foundation of Chongqing of China,Nos.CSTB2022NSCQ-LZX0038,cstc2021ycjh-bgzxm0035 (both to XT)+3 种基金the National Natural Science Foundation of China,No.82001378 (to XT)the Joint Project of Chongqing Health Commission and Science and Technology Bureau,No.2023QNXM009 (to XT)the Science and Technology Research Program of Chongqing Education Commission of China,No.KJQN202200435 (to XT)the Chongqing Talents:Exceptional Young Talents Project,No.CQYC202005014 (to XT)。
文摘Epilepsy can be defined as a dysfunction of the brain network,and each type of epilepsy involves different brain-network changes that are implicated diffe rently in the control and propagation of interictal or ictal discharges.Gaining more detailed information on brain network alterations can help us to further understand the mechanisms of epilepsy and pave the way for brain network-based precise therapeutic approaches in clinical practice.An increasing number of advanced neuroimaging techniques and electrophysiological techniques such as diffusion tensor imaging-based fiber tra ctography,diffusion kurtosis imaging-based fiber tractography,fiber ball imagingbased tra ctography,electroencephalography,functional magnetic resonance imaging,magnetoencephalography,positron emission tomography,molecular imaging,and functional ultrasound imaging have been extensively used to delineate epileptic networks.In this review,we summarize the relevant neuroimaging and neuroelectrophysiological techniques for assessing structural and functional brain networks in patients with epilepsy,and extensively analyze the imaging mechanisms,advantages,limitations,and clinical application ranges of each technique.A greater focus on emerging advanced technologies,new data analysis software,a combination of multiple techniques,and the construction of personalized virtual epilepsy models can provide a theoretical basis to better understand the brain network mechanisms of epilepsy and make surgical decisions.
基金Under the auspices of China Scholarship Council。
文摘Cross-region innovation is widely recognized as an important source of the long-term regional innovation capacity.In the recent past,a growing number of studies has investigated the network structure and mechanisms of cross-region innovation collaboration in various contexts.However,existing research mainly focuses on physical effects,such as geographical distance and high-speed railway connections.These studies ignore the intangible drivers in a changing environment,the more digitalized economy and the increasingly solidified innovation network structure.Thus,the focus of this study is on estimating determinants of innovation networks,especially on intangible drivers,which have been largely neglected so far.Using city-level data of Chinese patents(excluding Hong Kong,Macao,and Taiwan Province of China),we trace innovation networks across Chinese cities over a long period of time.By integrating a measure on Information and Communications Technology(ICT)development gap and network structural effects into the general proximity framework,this paper explores the changing mechanisms of Chinese innovation networks from a new perspective.The results show that the structure of cross-region innovation networks has changed in China.As mechanisms behind this development,the results confirm the increasingly important role of intangible drivers in Chinese inter-city innovation collaboration when controlling for effects of physical proximity,such as geographical distance.Since digitalization and coordinated development are the mainstream trends in China and other developing countries,these countries'inter-city innovation collaboration patterns will witness dramatic changes under the influence of intangible drivers.
基金the National Key Research and Development Program(No.2016YFC0600105)the National Natural Science Foundation of China(No.41672094).
文摘Structural network studies could give appropriate opportunities to understanding structural/hydrothermal events,transportation of ore-forming fluids and water/rock interaction process.Four structural deformation/hydrothermal events have been identified in the Jiaojia fault zone according to microtexture and deformation of quartz and feldspars.Plagioclase experienced ductile deformation period with bended polysynthetic twin stripes(>450℃)in the early stage,followed by K-feldspar alteration period with ductile-brittle deformation and subgrain rotation recrystallization of quartz(380-450℃).Then,sericitization period occurred extensive ductile-brittle deformation(350-420℃)and extensive subgrain rotation recrystallization with a little bulging recrystallization in quartz.In the last,gold precipitation-related pyrite-sericite-quartz alteration was dominated by brittle deformation(300-380℃)and total bulging recrystallization of quartz.From the K-feldspar alteration zone and sericitization zone to pyrite-sericitequartz alteration zone,fractal dimension values of dynamically recrystallized quartz grains increase from 1.07 and 1.24 to 1.32,the calculated paleo strain rate values of dynamically recrystallized quartz range from 10^-10^.7(380℃)-10^-9.6(450℃)and 10^-9.3(350℃)-10^-8.2(420℃)to 10^-9.5(300℃)-10^-8.0(380℃),and the paleo differential stress values increase from 36.9 and 39.3,to 121.3 MPa.The increase of fractal dimension values and decrease of grain size from pyrite-sericite-quartz alteration zone and sericitization zone to K-feldspar alteration zone decreased average water/rock ratio values,which could lead to different acidity and redox conditions of ore-forming fluids and mineralization differences.Two kinds of orecontrolling fractures have been distinguished which include the gentle dip types(18°-50°)with NW(315°-355°)and SW(180°-235°)dip hosting No.Ⅰorebodies and the steep dip types(74°-90°)with NE(45°-85°)and SE(95°-165°)dip hosting No.Ⅲorebodies.These faults/fractures crosscut altered Linglong granite of footwall of the Jiaojia fault zone as rhombohedrons that promoted the connection between fractures in the K-feldspar alteration zone and fluid flow passages near the main fault face.Research results indicate No.Ⅰand No.Ⅲorebodies should be derived from the same mineralization event and belong to different orebody types in different mineralization sites under the same structural networks.
文摘We propose molten polymer's entanglement network deformation to be nonaffine and use transient network structural theory with the revised Liu's kinetics rate equation and the revised upper convected Maxwell constitutive equation to establish a nonaffine network structural constitutive model for studying the rheological behavior of molten Low Density Polyethylene (LDPE) and High Density Polyethylene (HDPE) in oscillatory shear. As a result, when the strain amplitude or frequency increases, the shear stress amplitude increases. At the same time, the accuracy of the nonaffine network model is higher than that of affine network model. It is clear that there is a small amount of nonaffine network deformation for LDPE melts which have long chain branches, and there is a larger amount of nonaffine network deformation in oscillatory shear for HDPE melts which has no long chain branches. So we had better consider the network deformation nonaffine when we establish the constitutive equations of polymer melts in oscillatory shear.
文摘Superconductive properties for oxides were predicted by artificial neural network (ANN) method with structural and chemical parameters as inputs. The predicted properties include superconductivity for oxides, distributed ranges of the superconductive transition temperature (Tc) for complex oxides, and Tc values for cuprate superconductors. The calculated results indicated that the adjusted ANN can be used to predict superconductive properties for unknown oxides.
基金supported by the NationalNatural Science Foundation of China(No.62001272).
文摘Extracting useful details from images is essential for the Internet of Things project.However,in real life,various external environments,such as badweather conditions,will cause the occlusion of key target information and image distortion,resulting in difficulties and obstacles to the extraction of key information,affecting the judgment of the real situation in the process of the Internet of Things,and causing system decision-making errors and accidents.In this paper,we mainly solve the problem of rain on the image occlusion,remove the rain grain in the image,and get a clear image without rain.Therefore,the single image deraining algorithm is studied,and a dual-branch network structure based on the attention module and convolutional neural network(CNN)module is proposed to accomplish the task of rain removal.In order to complete the rain removal of a single image with high quality,we apply the spatial attention module,channel attention module and CNN module to the network structure,and build the network using the coder-decoder structure.In the experiment,with the structural similarity(SSIM)and the peak signal-to-noise ratio(PSNR)as evaluation indexes,the training and testing results on the rain removal dataset show that the proposed structure has a good effect on the single image deraining task.
基金the National Natural Science Foundation of China(Grant Nos.61863025 and 62266030)Program for International S&T Cooperation Projects of Gansu Province of China(Grant No.144WCGA166)Program for Longyuan Young Innovation Talents and the Doctoral Foundation of LUT.
文摘This paper investigates information spreading from the perspective of topological phase transition.Firstly,a new hybrid network is constructed based on the small-world networks and scale-free networks.Secondly,the attention mechanism of online users in information spreading is studied from four aspects:social distance,individual influence,content richness,and individual activity,and a dynamic evolution model of connecting with spreading is designed.Eventually,numerical simulations are conducted in three types of networks to verify the validity of the proposed dynamic evolution model.The simulation results show that topological structure and node influence in different networks have undergone phase transition,which is consistent with the phenomenon that followers and individual influence in real social networks experience phase transition within a short period.The infection density of networks with the dynamic evolution rule changes faster and reaches higher values than that of networks without the dynamic evolution rule.Furthermore,the simulation results are compared with the real data,which shows that the infection density curve of the hybrid networks is closer to that of the real data than that of the small-world networks and scale-free networks,verifying the validity of the model proposed in this paper.
基金financial support from the Major Scientific and Technological Projects of CNPC under Grant(ZD2019-183-007)is gratefully acknowledge.
文摘The double-network prepared with an in-situ monomer gel and a fast-crosslinked Cr(III) gel is introduced to develop a thixotropic and high-strength gel (THSG), which is found to have many advantages over the traditional gels. The THSG gel demonstrates remarkable thermal stability, and no syneresis is observed after 12 months with high salinity brine (95,500 mg/L). Moreover, the SEM and XRD results indicate that the gel is intercalated into the lamellar structures of Na-MMT, where the gel can form a uniform and compact structure. In addition, the THSG gel has an excellent swelling behavior, even in the high salinity brine. In the slim tube experiments, the THSG gel exhibits high rupture pressure and improves blocking capacity after being ruptured. The core flooding results show that a layer of gel filter cake is formed on the face of the fracture, which may be promoted by a high matrix permeability, a small aperture fracture, and a high injection rate. After the gel treatment, the fracture can be completely blocked by the THSG gel. It is found that a high incremental oil recovery (65.3%) can be achieved when the fracture was completely blocked, compared to 40.2% if the gel is ruptured. Although the swelling of ruptured gel can improve oil recovery, part of the injected brine may be channeled through the gel-filled fractures, resulting in a decrease in the sweep efficiency. Therefore, the improved blocking ability by gel swelling (e.g., in fresh water) may be less efficient to contribute to an enhancement of oil recovery. It is also found that the pressure gradient and residual resistance factor to water (Frrw) are higher if the matrix is less permeable, indicating that the fractured reservoir with lower matrix permeability may require a higher gel strength for treatment. The findings of this study may provide novel insights on designing robust double network gels for water shutoff in fractured reservoirs.
基金Supported by National Natural Science Foundation of China(Grant No.61573233)Guangdong Provincial Natural Science Foundation of China(Grant No.2021A1515010661)Guangdong Provincial Special Projects in Key Fields of Colleges and Universities of China(Grant No.2020ZDZX2005).
文摘Improving the detection accuracy of rail internal defects and the generalization ability of detection models are not only the main problems in the field of defect detection but also the key to ensuring the safe operation of high-speed trains.For this reason,a rail internal defect detection method based on an enhanced network structure and module design using ultrasonic images is proposed in this paper.First,a data augmentation method was used to extend the existing image dataset to obtain appropriate image samples.Second,an enhanced network structure was designed to make full use of the high-level and low-level feature information in the image,which improved the accuracy of defect detection.Subsequently,to optimize the detection performance of the proposed model,the Mish activation function was used to design the block module of the feature extraction network.Finally,the pro-posed rail defect detection model was trained.The experimental results showed that the precision rate and F1score of the proposed method were as high as 98%,while the model’s recall rate reached 99%.Specifically,good detec-tion results were achieved for different types of defects,which provides a reference for the engineering application of internal defect detection.Experimental results verified the effectiveness of the proposed method.
基金supported by the National Natural Science Foundation of China under Grant 62002122Guangzhou Municipal Science and Technology Bureau under Grant 202102080492Key Scientific and Technological Research and Department of Education of Guangdong Province under Grant 2019KTSCX014.
文摘Deep neural networks have achieved tremendous success in various fields,and the structure of these networks is a key factor in their success.In this paper,we focus on the research of ensemble learning based on deep network structure and propose a new deep network ensemble framework(DNEF).Unlike other ensemble learning models,DNEF is an ensemble learning architecture of network structures,with serial iteration between the hidden layers,while base classifiers are trained in parallel within these hidden layers.Specifically,DNEF uses randomly sampled data as input and implements serial iteration based on the weighting strategy between hidden layers.In the hidden layers,each node represents a base classifier,and multiple nodes generate training data for the next hidden layer according to the transfer strategy.The DNEF operates based on two strategies:(1)The weighting strategy calculates the training instance weights of the nodes according to their weaknesses in the previous layer.(2)The transfer strategy adaptively selects each node’s instances with weights as transfer instances and transfer weights,which are combined with the training data of nodes as input for the next hidden layer.These two strategies improve the accuracy and generalization of DNEF.This research integrates the ensemble of all nodes as the final output of DNEF.The experimental results reveal that the DNEF framework surpasses the traditional ensemble models and functions with high accuracy and innovative deep ensemble methods.
基金supported by Princess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2022R66),Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.
文摘Next-generation networks,including the Internet of Things(IoT),fifth-generation cellular systems(5G),and sixth-generation cellular systems(6G),suf-fer from the dramatic increase of the number of deployed devices.This puts high constraints and challenges on the design of such networks.Structural changing of the network is one of such challenges that affect the network performance,includ-ing the required quality of service(QoS).The fractal dimension(FD)is consid-ered one of the main indicators used to represent the structure of the communication network.To this end,this work analyzes the FD of the network and its use for telecommunication networks investigation and planning.The clus-ter growing method for assessing the FD is introduced and analyzed.The article proposes a novel method for estimating the FD of a communication network,based on assessing the network’s connectivity,by searching for the shortest routes.Unlike the cluster growing method,the proposed method does not require multiple iterations,which reduces the number of calculations,and increases the stability of the results obtained.Thus,the proposed method requires less compu-tational cost than the cluster growing method and achieves higher stability.The method is quite simple to implement and can be used in the tasks of research and planning of modern and promising communication networks.The developed method is evaluated for two different network structures and compared with the cluster growing method.Results validate the developed method.
基金supported by the Ministry of Science and Technology of the People’s Republic of China(2021xjkk0905).
文摘The exchanges between cities and counties in the northern slope economic belt of Tianshan Mountains(NSEBTM)are increasingly frequent and the economic linkages are increasingly close,but the spatial distribution of economic development and linkages among the cities and counties within NSEBTM is uneven.Therefore,it is of great significance to study the evolution of spatial-temporal pattern of the economic linkage network of cities and counties on NSEBTM to promote the coordinated and integrated development of the regional economy on NSEBTM.In this study,we used the modified gravity model and social network analysis method to analyze the spatio-temporal evolution characteristics of the economic linkage network structure of cities and counties on NSEBTM in 2000,2010,and 2020.The results showed that the comprehensive development quality level of cities and counties on NSEBTM increased from 2000 to 2020,its growth rate also increased,and its gap between cities and counties continued expanding.Both the spatial distribution patterns of the comprehensive development quality level of cities and counties on NSEBTM in 2000 and 2010 were presented as“high in the middle and low at both ends”,while the spatial distribution pattern of 2020 was exhibited as“high value and low value staggered”.The total amount of external economic linkages of cities and counties on NSEBTM showed an obvious upward trend,and its gap between cities and counties continued expanding,presenting a pattern of“a strong middle section and weak ends”.The direction of economic linkages of NSEBTM existed obvious central orientation and geographical proximity.The density of economic linkage network of NSEBTM increased from 2000 to 2020,and the structure of economic linkage network changed from single-core structure centered with Urumqi City to multicore structure centered with Urumqi City,Karamay City,Shihezi City,and Changji City,shifting from unbalanced development to balanced development.In the future,we should accelerate the construction of urban agglomeration on NSEBTM,cultivate a modern Urumqi metropolitan area,improve comprehensive development quality of the cities and counties at the eastern and western ends,strengthen the intensity of economic linkages between cities and counties,optimize the economic linkage network,and promote the coordinated and integrated development of regional economy.
基金Funded by National Natural Science Foundation of China(Nos.52172019 and 52072148)Shandong Provincial Youth Innovation Team Development Plan of Colleges and Universities(No.2022K1100)。
文摘In this work,the structure,viscosity and ion-exchange process of Na_(2)O-MgO-Al_(2)O_(3)-SiO_(2) glasses with different Al_(2)O_(3)/SiO_(2) molar ratios were investigated.The results showed that,with increasing Al_(2)O_(3)/SiO_(2) ratio,the simple structural units Q_(1) and Q_(2) transformed into highly aggregated structural units Q_(3) and Q_(4),indicating the increase of polymerization degree of glass network.Meanwhile,the coefficient of thermal expansion decreased from 9.23×10^(-6)℃^(-1) to 8.88×10^(-6)℃^(-1).The characteristic temperatures such as melting,forming,softening and glass transition temperatures increased with the increase of Al_(2)O_(3)/SiO_(2) ratio,while the glasses working temperature range became narrow.The increasing Al_(2)O_(3)/SiO_(2) ratio and prolonging ion-exchange time enhanced the surface compressive stress(CS)and depth of stress layer(DOL).However,the increase of ion exchange temperature increased the DOL and decreased the CS affected by stress relaxation.There was a good linear relationship between stress relaxation and surface compressive stress.Chemical strengthening significantly improved the hardness of glasses,which reached the maximum value of(622.1±10)MPa for sample with Al_(2)O_(3)/SiO_(2) ratio of 0.27 after heat treated at 410℃for 2 h.
基金Funded by the Key Research and Development Program of Han Nan province(No.ZDYF2021GXJS027)the Project of Sanya Yazhou Bay Science and Technology City(No.SCKJJYRC-2022-44)the Shenzhen Virtual University Park(SZVUP)Free Exploration Basic Research Project(No.2021Szvup107)。
文摘The calcium aluminosilicate-based glasses(CaO-Al_(2)O_(3)-SiO_(2),CAS)with different Fe_(2)O_(3)content(0.10wt%,0.50wt%,0.90wt%,and 1.30wt%)were prepared by traditional melt-quenching method.The glass network structure,thermal and mechanical properties,and crystallization behavior changes were investigated by nuclear magnetic resonance spectrometer,Fourier-transform infrared spectro-photometer,X-ray diffractometer,differential scanning calorimetry and field emission scanning electron microscope measurements.The change of Q^(n)in glass structures reveals the glass network connectivity decreases due to the increasing content of Fe_(2)O_(3)addition,resulting in the increasing of non-bridging number in glass structure.The glass densities slightly rise from 2.644 to 2.681 g/cm^(3),while Vickers’s hardness increases at first,from 6.469 to 6.901 GPa,then slightly drops to 6.745 GPa,with Fe_(2)O_(3)content increase.There is almost no thermal expansion coefficient change from different Fe_(2)O_(3)content.The glass transmittance in visible range gradually decreases with higher Fe_(2)O_(3)content,resulting from the strong absorption of Fe^(2+)and Fe^(3+)ions.The calculated activation energy from thermal analysis results first decreases from 282.70 to 231.18 kJ/mol,and then increases to 244.02 kJ/mol,with the Fe_(2)O_(3)content increasing from 0.10wt%to 1.30wt%.Meanwhile,the maximum Avrami constant of 2.33 means the CAS glasses exhibit two-dimensional crystallization.All of the CAS glass-ceramics samples contain main crystal phase of anorthite,the microstructure appears lamellar and columnar crystals.
基金supported in part by the National Natural Science Foundation of China under Grant 62171203in part by the Jiangsu Province“333 Project”High-Level Talent Cultivation Subsidized Project+2 种基金in part by the SuzhouKey Supporting Subjects for Health Informatics under Grant SZFCXK202147in part by the Changshu Science and Technology Program under Grants CS202015 and CS202246in part by Changshu Key Laboratory of Medical Artificial Intelligence and Big Data under Grants CYZ202301 and CS202314.
文摘In this paper,we introduce a novel Multi-scale and Auto-tuned Semi-supervised Deep Subspace Clustering(MAS-DSC)algorithm,aimed at addressing the challenges of deep subspace clustering in high-dimensional real-world data,particularly in the field of medical imaging.Traditional deep subspace clustering algorithms,which are mostly unsupervised,are limited in their ability to effectively utilize the inherent prior knowledge in medical images.Our MAS-DSC algorithm incorporates a semi-supervised learning framework that uses a small amount of labeled data to guide the clustering process,thereby enhancing the discriminative power of the feature representations.Additionally,the multi-scale feature extraction mechanism is designed to adapt to the complexity of medical imaging data,resulting in more accurate clustering performance.To address the difficulty of hyperparameter selection in deep subspace clustering,this paper employs a Bayesian optimization algorithm for adaptive tuning of hyperparameters related to subspace clustering,prior knowledge constraints,and model loss weights.Extensive experiments on standard clustering datasets,including ORL,Coil20,and Coil100,validate the effectiveness of the MAS-DSC algorithm.The results show that with its multi-scale network structure and Bayesian hyperparameter optimization,MAS-DSC achieves excellent clustering results on these datasets.Furthermore,tests on a brain tumor dataset demonstrate the robustness of the algorithm and its ability to leverage prior knowledge for efficient feature extraction and enhanced clustering performance within a semi-supervised learning framework.
基金supported by the National Natural Science Foundation of China (60974082,11171094)the Fundamental Research Funds for the Central Universities (K50510700004)+1 种基金the Foundation and Advanced Technology Research Program of Henan Province (102300410264)the Basic Research Program of the Education Department of Henan Province (2010A110010)
文摘Structure learning of Bayesian networks is a wellresearched but computationally hard task.For learning Bayesian networks,this paper proposes an improved algorithm based on unconstrained optimization and ant colony optimization(U-ACO-B) to solve the drawbacks of the ant colony optimization(ACO-B).In this algorithm,firstly,an unconstrained optimization problem is solved to obtain an undirected skeleton,and then the ACO algorithm is used to orientate the edges,thus returning the final structure.In the experimental part of the paper,we compare the performance of the proposed algorithm with ACO-B algorithm.The experimental results show that our method is effective and greatly enhance convergence speed than ACO-B algorithm.
基金This work was financially supported by the Natural Science Foundation of Shandong Province, China (Y2006F03).
文摘Reticulated polyurethane was chosen as the preceramic material for preparing the porous preform using the replication process. The immersing and sintering processes were each performed twice for fabricating a high-porosity and super-strong skeleton. The aluminum magnesium matrix composites reinforced with three-dimensional network structure were prepared using the infiltration technique by pressure assisting and vacuum driving. Light interfacial reactions have played a profitable role in most of the ceramic-metal systems. The metal matrix composites interpenetrated with the ceramic phase have a higher wear resistance than the metal matrix phase. The volume fraction of ceramic reinforcement has a significant effect on the abrasive wear, and the wear rate can be decreased with the increase of the volume fraction of reinforcement.
基金Project supported by the National Natural Science Foundation of China (Grant Nos.61101117,61171099,and 61362008)the National Key Scientific and Technological Project of China (Grant No.2012ZX03004005002)+1 种基金the Fundamental Research Funds for the Central Universities,China (Grant No.BUPT2012RC0112)the Natural Science Foundation of Jiangxi Province,China (Grant No.20132BAB201018)
文摘In this paper, the general efficiency, which is the average of the global efficiency and the local efficiency, is defined to measure the communication efficiency of a network. The increasing ratio of the general efficiency of a small-world network relative to that of the corresponding regular network is used to measure the small-world effect quantitatively. The more considerable the small-world effect, the higher the general efficiency of a network with a certain cost is. It is shown that the small-world effect increases monotonically with the increase of the vertex number. The optimal rewiring probability to induce the best small-world effect is approximately 0.02 and the optimal average connection probability decreases monotonically with the increase of the vertex number. Therefore, the optimal network structure to induce the maximal small-world effect is the structure with the large vertex number (〉 500), the small rewiring probability (≈0.02) and the small average connection probability (〈 0.1). Many previous research results support our results.
基金the National Natural Science Foundation of China(41871151).
文摘The construction of high-speed rail(HSR)network has promoted the social-economic ties of cities,accelerated the compression of time and space,and changed the pattern of regional development.In this paper,with the adoption of the operation frequency data of HSR from 12306 website,and based on the HSR connection strength model and social network analysis model,as well as according to the HSR connection strength,HSR network density,centrality,agglomeration subgroup,and other indicators,we analyzed the characteristics of HSR network structure in Northeast China.Results show that the number of HSR cities in Northeast China is small,cities in HSR network generally exhibit weak connectivity,and the existence of HSR network marginalizes cities such as Ulanhot,Baicheng,and Songyuan,which significantly reduce the overall network connectivity of Northeast China.The overall centrality of HSR network in Northeast China is characterized by“one axis,four edges”;specifically,the one axis is located in Harbin-Dalian transportation line and the four edges are located on both sides of the main axis of Harbin-Dalian transportation line.Eight agglomeration subgroups(four double city subgroups and four multi city subgroups)have formed in Northeast China.The core status of Shenyang in HSR network is improved significantly,and“one axis and two wings”HSR network in Liaoning Province is improved significantly.With the gradual expansion of Chaoyang-Fuxin,Dandong-Benxi,and Jilin-Yanji branch networks,the“point axis”HSR network mode in Northeast China has gradually developed and matured.In the future,it is recommended to rely on eight agglomerating subgroups to encrypt HSR network structure,create secondary node central cities,and gradually build a new pattern of opening up in Northeast China.
基金supported by the China Postdoctoral Science Foundation(No.2014M551053)Natural Science Foundation of Hebei Province(No.B2015203124)Key Laboratory of Advanced Energy Materials Chemistry(Ministry of Education),Nankai University
文摘Two crystals of receptor 1, C(42)H(52)N(10)O4S2(anthracene-9,10-dicarbaldehyde bis-(phenyl-semithiocarbazone)) and-1-H2PO4, C(68)H(114)N(10)O(10)P2S2 were obtained at room temperature successfully, and their structures were characterized by X-ray crystallography diffraction. X-ray diffraction reveals that, receptor 1 crystallizes in monoclinic, space group P21/c, with a = 9.487(3),b = 20.674(6), c = 11.821(4)A, β = 113.416(8)o, Mr = 825.06, V = 2127.5(12) A^3, Z = 2, Dc = 1.288g/cm^3, μ = 0.18 mm^-1, F(000) = 876, MoK α radiation(λ = 0.71073 A), the final R = 0.0472 and wR = 0.0930. A total of 3758 unique reflections were collected, of which 3313 with I 〉 2σ(I) were observed. Compound 1-H2PO4^-crystallizes in triclinic, space group P21/n, with a = 8.767(1), b =13.6190(15), c = 16.615(2) ?, α = 98.727(14), β = 103.061(14), γ = 91.382(16)°, Mr = 1357.75, V =1906.6(4) A^3, Z = 1, Dc = 1.183 g/cm^3, μ = 0.17 mm-(-1), F(000) = 734, MoK α radiation(λ = 0.71073?), the final R = 0.0769 and wR = 0.1884. A total of 6699 unique reflections were collected, of which 2989 with I 〉 2σ(I) were observed. As it was observed in the crystal structure of 1-H2PO4^-, 1bound H2PO4^-at a 1:2 ratio by intermolecular interaction of N-H···O hydrogen bond obviously.Another interesting feature was that H2PO4--groups assembled chains themselves via intramolecular hydrogen bond O-H···O and connected the 1 molecules together through the interaction of H-bonds,which improved the planarity of 1 and increased the stability of the entire structure.