BACKGROUND Depression,non-suicidal self-injury(NSSI),and suicide attempts(SA)often co-occur during adolescence and are associated with long-term adverse health outcomes.Unfortunately,neural mechanisms underlying self-...BACKGROUND Depression,non-suicidal self-injury(NSSI),and suicide attempts(SA)often co-occur during adolescence and are associated with long-term adverse health outcomes.Unfortunately,neural mechanisms underlying self-injury and SA are poorly understood in depressed adolescents but likely relate to the structural abnormalities in brain regions.AIM To investigate structural network communication within large-scale brain networks in adolescents with depression.METHODS We constructed five distinct network communication models to evaluate structural network efficiency at the whole-brain level in adolescents with depression.Diffusion magnetic resonance imaging data were acquired from 32 healthy controls and 85 depressed adolescents,including 17 depressed adolescents without SA or NSSI(major depressive disorder group),27 depressed adolescents with NSSI but no SA(NSSI group),and 41 depressed adolescents with SA and NSSI(NSSI+SA group).RESULTS Significant differences in structural network communication were observed across the four groups,involving spatially widespread brain regions,particularly encompassing cortico-cortical connections(e.g.,dorsal posterior cingulate gyrus and the right ventral posterior cingulate gyrus;connections based on precentral gyrus)and cortico-subcortical circuits(e.g.,the nucleus accumbens-frontal circuit).In addition,we examined whether compromised communication efficiency was linked to clinical symptoms in the depressed adolescents.We observed significant correlations between network communication efficiencies and clinical scale scores derived from depressed adolescents with NSSI and SA.CONCLUSION This study provides evidence of structural network communication differences in depressed adolescents with NSSI and SA,highlighting impaired neuroanatomical communication efficiency as a potential contributor to their symptoms.These findings offer new insights into the pathophysiological mechanisms underlying the comorbidity of NSSI and SA in adolescent depression.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
As a crucial storage and buffering apparatus for balancing the production and consumption of byproduct gases in industrial processes, accurate prediction of gas tank levels is essential for optimizing energy system sc...As a crucial storage and buffering apparatus for balancing the production and consumption of byproduct gases in industrial processes, accurate prediction of gas tank levels is essential for optimizing energy system scheduling. Considering that the continuous switching of the pressure and valve status(mechanism knowledge) would bring about multiple working conditions of the equipment, a multi-condition time sequential network ensembled method is proposed. In order to especially consider the time dependence of different conditions, a centralwise condition sequential network is developed, where the network branches are specially designed based on the condition switching sequences. A branch combination transfer learning strategy is developed to tackle the sample imbalance problem of different condition data. Since the condition or status data are real-time information that cannot be recognized during the prediction process, a pre-trained and ensemble learning approach is further proposed to fuse the outputs of the multi-condition networks and realize a transient-state involved prediction. The performance of the proposed method is validated on practical energy data coming from a domestic steel plant, comparing with the state-of-the-art algorithms. The results show that the proposed method can maintain a high prediction accuracy under different condition switching cases, which would provide effective guidance for the optimal scheduling of the industrial energy systems.展开更多
As the most important large-scale communication infrastructure in the world today,submarine cable can profoundly reflect the global Internet communication pattern,and is of great significance for understanding the glo...As the most important large-scale communication infrastructure in the world today,submarine cable can profoundly reflect the global Internet communication pattern,and is of great significance for understanding the global digital divide.We used multi-scale and network analysis methods to depict the distribution pattern,network structure and spatio-temporal evolution of global submarine cables at the national and landing point scales,in order to analyze the current situation,challenges and main directions of global digital divide governance.Results show that:(1)spatial distribution of global submarine cables is unbalanced,the United States and Europe are the concentrated distribution areas of submarine cables and global information flow centers;(2)core connections of the global submarine cable network are only composed of a tiny minority of countries or regions or landing points,and have strong geographical proximity and clustered-type characteristic,noting that multitudinous landing points of developed countries are at the semi-periphery or even periphery of the network;(3)submarine cables can alleviate the global digital divide through the three paths of infrastructure universalization,digital ecosystem reconstruction and economic empowerment,and the global digital divide governance still faces the dilemma of the differences in digital strategy development and the lack of a governance system.However,due to the increasingly important position of cities in developing countries in the international communication pattern,the global digital divide problem is being alleviated.展开更多
The construction of“park cities”requires a systematic thinking to coordinate the networked development of park system and break through the limitation of emphasizing scale and grade and neglecting dynamic correlatio...The construction of“park cities”requires a systematic thinking to coordinate the networked development of park system and break through the limitation of emphasizing scale and grade and neglecting dynamic correlation in traditional planning.Taking Haidian District of Beijing as an example,the social network analysis method is introduced to construct the network model of park green spaces.Through indicators such as clustering coefficient,network density and node centrality,the characteristics of its spatial structure and hierarchical relationship are analyzed.It is found that the network integrity presents the characteristics of“highly local concentration and global fragmentation”,fragmented park green space network and missing spatial connection,isolated clusters and collaborative failure,as well as the spatial mismatch between population and resource supply and demand.Hierarchical issues include“structural imbalance and functional disorder”,disorder between network hierarchy and park level,misalignment of functional hierarchy leading to weakened network risk resistance capacity,and a relatively dense distribution of core nodes,etc.In response to the above problems,a multi-level spatial intervention strategy should be adopted to solve the overall problem of the network.Meanwhile,it is needed to clarify the positioning of a park itself and improve the hierarchical system,so as to construct a multi-level and multi-scale park green space network,contribute to the construction of a park city,and provide residents with more diverse activity venues.展开更多
To assess the high-temperature creep properties of titanium matrix composites for aircraft skin,the TA15 alloy,TiB/TA15 and TiB/(TA15−Si)composites with network structure were fabricated using low-energy milling and v...To assess the high-temperature creep properties of titanium matrix composites for aircraft skin,the TA15 alloy,TiB/TA15 and TiB/(TA15−Si)composites with network structure were fabricated using low-energy milling and vacuum hot pressing sintering techniques.The results show that introducing TiB and Si can reduce the steady-state creep rate by an order of magnitude at 600℃ compared to the alloy.However,the beneficial effect of Si can be maintained at 700℃ while the positive effect of TiB gradually diminishes due to the pores near TiB and interface debonding.The creep deformation mechanism of the as-sintered TiB/(TA15−Si)composite is primarily governed by dislocation climbing.The high creep resistance at 600℃ can be mainly attributed to the absence of grain boundaryαphases,load transfer by TiB whisker,and the hindrance of dislocation movement by silicides.The low steady-state creep rate at 700℃ is mainly resulted from the elimination of grain boundaryαphases as well as increased dynamic precipitation of silicides andα_(2).展开更多
Background Post-stroke depression(PSD)is a common neuropsychiatric problem associated with a high disease burden and reduced quality of life(QoL).To date,few studies have examined the network structure of depressive s...Background Post-stroke depression(PSD)is a common neuropsychiatric problem associated with a high disease burden and reduced quality of life(QoL).To date,few studies have examined the network structure of depressive symptoms and their relationships with QoL in stroke survivors.Aims This study aimed to explore the network structure of depressive symptoms in PSD and investigate the interrelationships between specific depressive symptoms and QoL among older stroke survivors.Methods This study was based on the 2017–2018 collection of data from a large national survey in China.Depressive symptoms were assessed using the 10-item Centre for Epidemiological Studies Depression Scale(CESD),while QoL was measured with the World Health Organization Quality of Life-brief version.Network analysis was employed to explore the structure of PSD,using expected influence(EI)to identify the most central symptoms and the flow function to investigate the association between depressive symptoms and QoL.Results A total of 1123 stroke survivors were included,with an overall prevalence of depression of 34.3%(n=385;95%confidence interval 31.5%to 37.2%).In the network model of depression,the most central symptoms were CESD3(‘feeling blue/depressed’,EI:1.180),CESD6(‘feeling nervous/fearful’,EI:0.864)and CESD8(‘loneliness’,EI:0.843).In addition,CESD5(‘hopelessness’,EI:−0.195),CESD10(‘sleep disturbances’,EI:−0.169)and CESD4(‘everything was an effort’,EI:−0.150)had strong negative associations with QoL.Conclusion This study found that PSD was common among older Chinese stroke survivors.Given its negative impact on QoL,appropriate interventions targeting central symptoms and those associated with QoL should be developed and implemented for stroke survivors with PSD.展开更多
The use of blended acquisition technology in marine seismic exploration has the advantages of high acquisition efficiency and low exploration costs.However,during acquisition,the primary source may be disturbed by adj...The use of blended acquisition technology in marine seismic exploration has the advantages of high acquisition efficiency and low exploration costs.However,during acquisition,the primary source may be disturbed by adjacent sources,resulting in blended noise that can adversely affect data processing and interpretation.Therefore,the de-blending method is needed to suppress blended noise and improve the quality of subsequent processing.Conventional de-blending methods,such as denoising and inversion methods,encounter challenges in parameter selection and entail high computational costs.In contrast,deep learning-based de-blending methods demonstrate reduced reliance on manual intervention and provide rapid calculation speeds post-training.In this study,we propose a Uformer network using a nonoverlapping window multihead attention mechanism designed for de-blending blended data in the common shot domain.We add the depthwise convolution to the feedforward network to improve Uformer’s ability to capture local context information.The loss function comprises SSIM and L1 loss.Our test results indicate that the Uformer outperforms convolutional neural networks and traditional denoising methods across various evaluation metrics,thus highlighting the effectiveness and advantages of Uformer in de-blending blended data.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
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
The inter-city linkage heat data provided by Baidu Migration is employed as a characterization of inter-city linkages in order to facilitate the study of the network linkage characteristics and hierarchical structure ...The inter-city linkage heat data provided by Baidu Migration is employed as a characterization of inter-city linkages in order to facilitate the study of the network linkage characteristics and hierarchical structure of urban agglomeration in the Greater Bay Area through the use of social network analysis method.This is the inaugural application of big data based on location services in the study of urban agglomeration network structure,which represents a novel research perspective on this topic.The study reveals that the density of network linkages in the Greater Bay Area urban agglomeration has reached 100%,indicating a mature network-like spatial structure.This structure has given rise to three distinct communities:Shenzhen-Dongguan-Huizhou,Guangzhou-Foshan-Zhaoqing,and Zhuhai-Zhongshan-Jiangmen.Additionally,cities within the Greater Bay Area urban agglomeration play different roles,suggesting that varying development strategies may be necessary to achieve staggered development.The study demonstrates that large datasets represented by LBS can offer novel insights and methodologies for the examination of urban agglomeration network structures,contingent on the appropriate mining and processing of the data.展开更多
Corrosion engineering is an effective way to improve the oxygen evolution reaction(OER)activity of al-loys.However,the impact of grain boundary corrosion on the structure and electrochemical performance of alloy is st...Corrosion engineering is an effective way to improve the oxygen evolution reaction(OER)activity of al-loys.However,the impact of grain boundary corrosion on the structure and electrochemical performance of alloy is still unknown.Herein,the vacuum arc-melted CrCoNiFe alloys with interlaced network struc-tures via grain boundary corrosion methods were fabricated.The grain boundaries that existed as de-fects were severely corroded and an interlaced network structure was formed,promoting the exposure of the active site and the release of gas bubbles.Besides,the(oxy)hydroxides layer(25 nm)on the sur-face could act as the true active center and improve the surface wettability.Benefiting from the unique structure and constructed surface,the CrCoNiFe-12 affords a high urea oxidation reaction(UOR)perfor-mance with the lowest overpotential of 250 mV at 10 mA/cm^(2)in 1 M KOH adding 0.33 M urea.The CrCoNiFe-12||Pt only required a cell voltage of 1.485 V to afford 10 mA/cm^(2)for UOR and long-term sta-bility of 100 h at 10 mA/cm^(2)(27.6 mV decrease).These findings offer a facile strategy for designing bulk multiple-principal-element alloy electrodes for energy conversion.展开更多
Objective Using graph theory analysis,this study compares the topological and node attributes of the brain network to explore the differences in gray matter structural and functional network topological properties bet...Objective Using graph theory analysis,this study compares the topological and node attributes of the brain network to explore the differences in gray matter structural and functional network topological properties between bipolar depression(BD)patients with and without obsessive-compulsive symptoms(OCS).Methods A total of 90 BD patients(27 males,63 females;median age 19.0(22.0,25.0)years)were recruited from the psychiatric outpatient and inpatient departments of the First Affiliated Hospital of Jinan University between March 2018 and December 2022.Fifty healthy controls(19 males,31 females;median age:23.0(20.0,27.0)years)were also enrolled.The BD patients were divided into two groups based on the presence of OCS:53 with OCS(OCS group)and 37 without OCS(NOCS group).Resting-state structural and functional MRI data were collected for all participants to construct gray matter structural and functional networks.Graph therory analysis was aapplied to calculate network topological metrics such as small-world properties.The structural and functional network topological properties were compared among the BD-OCS,BD-nOCS,and control groups.Partial correlation analysis was conducted to examine the association between network topological metrics with significant group differences and Yale-Brown Obsessive-Compulsive Scale(Y-BOCS)scores.Support vector machines(SVM)were used with these metrics as classificationfeaturevalues toimproveediagnostic accuracy through pairwise group classification.Results Structural network analysis of gray matter:compared to HC group,both OCS group and NOCS group showed increasedshortesttpathlengthand standardized characteristic path length(shortest path length:0.78 and 0.80 vs.0.69;normalized characteristic path length:0.48 and 0.49 vs.0.43),and decreased global efficiency(0.21 and 0.21 vs.0.24)compared to the HC group(permutation test,all P<0.05).Compared to NOCS and HC groups,the OCS group showed increased nodal centrality and betweenness centrality in the right rolandic operculum and left superior occipital gyrus(permutation test,all P<0.05).Functional network analysis of gray matter:compared to the NOCS group,the OCS group showed increased node efficiency and decreased betweenness centrality in the cerebellum(t=2.15,-3.04;all P<0.05);compared to HC groups,the OCS group showed decreased betweenness centrality in the cerebellum and left inferior frontal gyrus,along with increased node centrality and nodal efficiency in the right transverse temporal gyrus(t=-2.99,-3.61,3.06,3.10;all P<0.05).In the 0CS group,betweenness centrality in the left inferior frontal gyrus positively correlated with Y-BOCS scale obsessive thinking score(r=0.303,P=0.034).Nodal centrality and node efficiency of the right transverse temporal gyrus negatively correlated with Y-BOCS total score(r=-0.301,-0.311)and Y-BOCS obsessional thinking scores(r=-0.385,-0.380)separately(all P<0.05).SVM classification:the combined network features achieved an area under the curve of 0.80 in distinguising OCS from NOCS patients.Conclusion BDOCS and BD-nOCS patients both exhibit consistent changes in gray matter structural network topology,with theOCSSgroup displaying more pronounced nodal topological abnormalities.Multi-network feature integration demostrates potential for diagnostic classfication.展开更多
Effect of network structure on plasticity and fracture mode of Zr？Al？Ni？Cu bulk metallic glasses （BMGs） was investigated. The microstructures of transversal and longitudinal sections were exposed by chemical etch...Effect of network structure on plasticity and fracture mode of Zr？Al？Ni？Cu bulk metallic glasses （BMGs） was investigated. The microstructures of transversal and longitudinal sections were exposed by chemical etching and observed by scanning electron microscopy （SEM）. The mechanical properties were examined by room-temperature uniaxial compression test. The results show that both plasticity and fracture mode are significantly affected by the network structure and the alteration occurs when the size of the network structure reaches up to a critical value. When the cell size （dc） of the network structure is ~3μm, Zr-based BMGs characterize in plasticity that decreases with increasingdc. The fracture mode gradually transforms from single 45° shear fracture to double 45° shear fracture and then cleavage fracture with increasingdc. In addition, the mechanisms of the transition of the plasticity and the fracture mode for these Zr-based BMGs are also discussed.展开更多
Non-stoichiometric carbides have been proven to be effective electromagnetic wave(EMW)absorbing materials.In this study,phase and morphology of XZnC(X=Fe/Co/Cu)loaded on a three dimensional(3D)network structure melami...Non-stoichiometric carbides have been proven to be effective electromagnetic wave(EMW)absorbing materials.In this study,phase and morphology of XZnC(X=Fe/Co/Cu)loaded on a three dimensional(3D)network structure melamine sponge(MS)carbon composites were investigated through vacuum filtration followed by calcination.The FeZnC/CoZnC/CuZnC with carbon nanotubes(CNTs)were uniformly dispersed on the surface of melamine sponge carbon skeleton and Co-containing sample exhibits the highest CNTs concentration.The minimum reflection loss(RL_(min))of the CoZnC/MS composite(m_(composite):m_(paraffin)=1:1,m represents mass)reached-33.60 dB,and the effective absorption bandwidth(EAB)reached 9.60 GHz.The outstanding electromagnetic wave absorption(EMWA)properties of the CoZnC/MS composite can be attributed to its unique hollow structure,which leads to multiple reflections and scattering.The formed conductive network improves dielectric and conductive loss.The incorporation of Co enhances the magnetic loss capability and optimizes interfacial polarization and dipole polarization.By simultaneously improving dielectric and magnetic losses,ex-cellent impedance matching performance is achieved.The clarification of element replacement in XZnC/MS composites provides an effi-cient design perspective for high-performance non-stoichiometric carbide EMW absorbers.展开更多
In order to simulate the real growing process, a new type of knowledge network growth mechanism based on local world connectivity is constructed. By the mean-field method, theoretical prediction of the degree distribu...In order to simulate the real growing process, a new type of knowledge network growth mechanism based on local world connectivity is constructed. By the mean-field method, theoretical prediction of the degree distribution of the knowledge network is given, which is verified by Matlab simulations. When the new added node＇s local world size is very small, the degree distribution of the knowledge network approximately has the property of scale-free. When the new added node＇s local world size is not very small, the degree distribution transforms from pure power-law to the power-law with an exponential tailing. And the scale-free index increases as the number of new added edges decreases and the tunable parameters increase. Finally, comparisons of some knowledge indices in knowledge networks generated by the local world mechanism and the global mechanism are given. In the long run, compared with the global mechanism, the local world mechanism leads the average knowledge levels to slower growth and brings homogenous phenomena.展开更多
Amidst the rapid pace of urban development,rural communities continually face the challenges posed by erratic natural disasters and human-induced disturbances.Evaluating and improving the resilience of rural areas is ...Amidst the rapid pace of urban development,rural communities continually face the challenges posed by erratic natural disasters and human-induced disturbances.Evaluating and improving the resilience of rural areas is crucial for achieving sustainable development.Examining the rural network framework serves as a method to achieve rural resilience.This study established a contact network encompassing 13 villages in Shiba town,Mingguang City,through the collection of time-distance data,questionnaire interview data,and map vector data to examine the spatial patterns of the rural network.The examination of structural resilience was conducted through the framework of complex network theory.The examination of the network’s transitivity and diversity through the frameworks of hierarchy,matching,transitivity,and aggregation reveals its resilience to disruption simulations,such as node failure.The findings indicate that the network exhibits a configuration marked by a dense central region,sparse connections in the north,and a lack of connectivity in the south.The network exhibits a flat structure,with nodes that are relatively uniform in nature.The network exhibits significant disassortativity,classifying it as a disassortative network,where villages with higher node degrees tend to connect with those having lower node degrees.The local transitivity of the network is significantly elevated,with approximately 90%of settlements necessitating just one transfer to establish direct communication.The network exhibits significant clustering effects,marked by robust connections among villages and a few isolated node villages.The transitivity of the network and its diverse spatial patterns show markedly different characteristics when subjected to interruption simulation.The study identified two primary nodes and one susceptible node.The findings from the study precisely reflect the characteristics of the rural network.This can provide theoretical perspectives for analyzing the resilience of rural network structures and support decision-making in rural planning and development.展开更多
In recent years,deep learning has been introduced into the field of Single-pixel imaging(SPI),garnering significant attention.However,conventional networks still exhibit limitations in preserving image details.To addr...In recent years,deep learning has been introduced into the field of Single-pixel imaging(SPI),garnering significant attention.However,conventional networks still exhibit limitations in preserving image details.To address this issue,we integrate Large Kernel Convolution(LKconv)into the U-Net framework,proposing an enhanced network structure named U-LKconv network,which significantly enhances the capability to recover image details even under low sampling conditions.展开更多
基金Supported by the National Natural Science Foundation of China,No.81871081 and No.62201265the Fundamental Research Funds for the Central Universities,No.NJ2024029-14the Talent Support Programs of Wuxi Health Commission,No.BJ2023085,No.FZXK2021012,and No.M202358.
文摘BACKGROUND Depression,non-suicidal self-injury(NSSI),and suicide attempts(SA)often co-occur during adolescence and are associated with long-term adverse health outcomes.Unfortunately,neural mechanisms underlying self-injury and SA are poorly understood in depressed adolescents but likely relate to the structural abnormalities in brain regions.AIM To investigate structural network communication within large-scale brain networks in adolescents with depression.METHODS We constructed five distinct network communication models to evaluate structural network efficiency at the whole-brain level in adolescents with depression.Diffusion magnetic resonance imaging data were acquired from 32 healthy controls and 85 depressed adolescents,including 17 depressed adolescents without SA or NSSI(major depressive disorder group),27 depressed adolescents with NSSI but no SA(NSSI group),and 41 depressed adolescents with SA and NSSI(NSSI+SA group).RESULTS Significant differences in structural network communication were observed across the four groups,involving spatially widespread brain regions,particularly encompassing cortico-cortical connections(e.g.,dorsal posterior cingulate gyrus and the right ventral posterior cingulate gyrus;connections based on precentral gyrus)and cortico-subcortical circuits(e.g.,the nucleus accumbens-frontal circuit).In addition,we examined whether compromised communication efficiency was linked to clinical symptoms in the depressed adolescents.We observed significant correlations between network communication efficiencies and clinical scale scores derived from depressed adolescents with NSSI and SA.CONCLUSION This study provides evidence of structural network communication differences in depressed adolescents with NSSI and SA,highlighting impaired neuroanatomical communication efficiency as a potential contributor to their symptoms.These findings offer new insights into the pathophysiological mechanisms underlying the comorbidity of NSSI and SA in adolescent depression.
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.
基金supported by the National Natural Sciences Foundation of China(62125302,62203087)Liaoning Revitalization Talents Program(XLYC2002087)+1 种基金Sci-Tech Talent Innovation Support Program of Dalian(2022RG03)Young Elite Scientist Sponsorship Program by China Association for Science and Technology(YESS20220018)
文摘As a crucial storage and buffering apparatus for balancing the production and consumption of byproduct gases in industrial processes, accurate prediction of gas tank levels is essential for optimizing energy system scheduling. Considering that the continuous switching of the pressure and valve status(mechanism knowledge) would bring about multiple working conditions of the equipment, a multi-condition time sequential network ensembled method is proposed. In order to especially consider the time dependence of different conditions, a centralwise condition sequential network is developed, where the network branches are specially designed based on the condition switching sequences. A branch combination transfer learning strategy is developed to tackle the sample imbalance problem of different condition data. Since the condition or status data are real-time information that cannot be recognized during the prediction process, a pre-trained and ensemble learning approach is further proposed to fuse the outputs of the multi-condition networks and realize a transient-state involved prediction. The performance of the proposed method is validated on practical energy data coming from a domestic steel plant, comparing with the state-of-the-art algorithms. The results show that the proposed method can maintain a high prediction accuracy under different condition switching cases, which would provide effective guidance for the optimal scheduling of the industrial energy systems.
基金National Natural Science Foundation of China,No.42371175。
文摘As the most important large-scale communication infrastructure in the world today,submarine cable can profoundly reflect the global Internet communication pattern,and is of great significance for understanding the global digital divide.We used multi-scale and network analysis methods to depict the distribution pattern,network structure and spatio-temporal evolution of global submarine cables at the national and landing point scales,in order to analyze the current situation,challenges and main directions of global digital divide governance.Results show that:(1)spatial distribution of global submarine cables is unbalanced,the United States and Europe are the concentrated distribution areas of submarine cables and global information flow centers;(2)core connections of the global submarine cable network are only composed of a tiny minority of countries or regions or landing points,and have strong geographical proximity and clustered-type characteristic,noting that multitudinous landing points of developed countries are at the semi-periphery or even periphery of the network;(3)submarine cables can alleviate the global digital divide through the three paths of infrastructure universalization,digital ecosystem reconstruction and economic empowerment,and the global digital divide governance still faces the dilemma of the differences in digital strategy development and the lack of a governance system.However,due to the increasingly important position of cities in developing countries in the international communication pattern,the global digital divide problem is being alleviated.
文摘The construction of“park cities”requires a systematic thinking to coordinate the networked development of park system and break through the limitation of emphasizing scale and grade and neglecting dynamic correlation in traditional planning.Taking Haidian District of Beijing as an example,the social network analysis method is introduced to construct the network model of park green spaces.Through indicators such as clustering coefficient,network density and node centrality,the characteristics of its spatial structure and hierarchical relationship are analyzed.It is found that the network integrity presents the characteristics of“highly local concentration and global fragmentation”,fragmented park green space network and missing spatial connection,isolated clusters and collaborative failure,as well as the spatial mismatch between population and resource supply and demand.Hierarchical issues include“structural imbalance and functional disorder”,disorder between network hierarchy and park level,misalignment of functional hierarchy leading to weakened network risk resistance capacity,and a relatively dense distribution of core nodes,etc.In response to the above problems,a multi-level spatial intervention strategy should be adopted to solve the overall problem of the network.Meanwhile,it is needed to clarify the positioning of a park itself and improve the hierarchical system,so as to construct a multi-level and multi-scale park green space network,contribute to the construction of a park city,and provide residents with more diverse activity venues.
基金financially supported by the National Key R&D Program of China(No.2022YFB3707405)the National Natural Science Foundation of China(Nos.U22A20113,52171137,52071116)+1 种基金Heilongjiang Provincial Natural Science Foundation,China(No.TD2020E001)Heilongjiang Touyan Team Program,China.
文摘To assess the high-temperature creep properties of titanium matrix composites for aircraft skin,the TA15 alloy,TiB/TA15 and TiB/(TA15−Si)composites with network structure were fabricated using low-energy milling and vacuum hot pressing sintering techniques.The results show that introducing TiB and Si can reduce the steady-state creep rate by an order of magnitude at 600℃ compared to the alloy.However,the beneficial effect of Si can be maintained at 700℃ while the positive effect of TiB gradually diminishes due to the pores near TiB and interface debonding.The creep deformation mechanism of the as-sintered TiB/(TA15−Si)composite is primarily governed by dislocation climbing.The high creep resistance at 600℃ can be mainly attributed to the absence of grain boundaryαphases,load transfer by TiB whisker,and the hindrance of dislocation movement by silicides.The low steady-state creep rate at 700℃ is mainly resulted from the elimination of grain boundaryαphases as well as increased dynamic precipitation of silicides andα_(2).
基金supported by Beijing High Level Public Health Technology Talent Construction Project(Discipline Backbone-01-028)the Beijing Municipal Science&Technology Commission(No.Z181100001518005)+2 种基金the Capital's Funds for Health Improvement and Research(CFH 2024-2-1174)the University of Macao(MYRG-GRG2023-00141-FHS,CPG2025-00021-FHS)the Science and Technology Plan Foundation of Guangzhou(No.202201011663).
文摘Background Post-stroke depression(PSD)is a common neuropsychiatric problem associated with a high disease burden and reduced quality of life(QoL).To date,few studies have examined the network structure of depressive symptoms and their relationships with QoL in stroke survivors.Aims This study aimed to explore the network structure of depressive symptoms in PSD and investigate the interrelationships between specific depressive symptoms and QoL among older stroke survivors.Methods This study was based on the 2017–2018 collection of data from a large national survey in China.Depressive symptoms were assessed using the 10-item Centre for Epidemiological Studies Depression Scale(CESD),while QoL was measured with the World Health Organization Quality of Life-brief version.Network analysis was employed to explore the structure of PSD,using expected influence(EI)to identify the most central symptoms and the flow function to investigate the association between depressive symptoms and QoL.Results A total of 1123 stroke survivors were included,with an overall prevalence of depression of 34.3%(n=385;95%confidence interval 31.5%to 37.2%).In the network model of depression,the most central symptoms were CESD3(‘feeling blue/depressed’,EI:1.180),CESD6(‘feeling nervous/fearful’,EI:0.864)and CESD8(‘loneliness’,EI:0.843).In addition,CESD5(‘hopelessness’,EI:−0.195),CESD10(‘sleep disturbances’,EI:−0.169)and CESD4(‘everything was an effort’,EI:−0.150)had strong negative associations with QoL.Conclusion This study found that PSD was common among older Chinese stroke survivors.Given its negative impact on QoL,appropriate interventions targeting central symptoms and those associated with QoL should be developed and implemented for stroke survivors with PSD.
基金supported by the National Natural Science Foundation of China(Research on Dynamic Location of Receiving Points and Wave Field Separation Technology Based on Deep Learning in OBN Seismic Exploration,No.42074140)the Sinopec Geophysical Corporation,Project of OBC/OBN Seismic Data Wave Field Characteristics Analysis and Ghost Wave Suppression(No.SGC-202206)。
文摘The use of blended acquisition technology in marine seismic exploration has the advantages of high acquisition efficiency and low exploration costs.However,during acquisition,the primary source may be disturbed by adjacent sources,resulting in blended noise that can adversely affect data processing and interpretation.Therefore,the de-blending method is needed to suppress blended noise and improve the quality of subsequent processing.Conventional de-blending methods,such as denoising and inversion methods,encounter challenges in parameter selection and entail high computational costs.In contrast,deep learning-based de-blending methods demonstrate reduced reliance on manual intervention and provide rapid calculation speeds post-training.In this study,we propose a Uformer network using a nonoverlapping window multihead attention mechanism designed for de-blending blended data in the common shot domain.We add the depthwise convolution to the feedforward network to improve Uformer’s ability to capture local context information.The loss function comprises SSIM and L1 loss.Our test results indicate that the Uformer outperforms convolutional neural networks and traditional denoising methods across various evaluation metrics,thus highlighting the effectiveness and advantages of Uformer in de-blending blended data.
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 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.
文摘The inter-city linkage heat data provided by Baidu Migration is employed as a characterization of inter-city linkages in order to facilitate the study of the network linkage characteristics and hierarchical structure of urban agglomeration in the Greater Bay Area through the use of social network analysis method.This is the inaugural application of big data based on location services in the study of urban agglomeration network structure,which represents a novel research perspective on this topic.The study reveals that the density of network linkages in the Greater Bay Area urban agglomeration has reached 100%,indicating a mature network-like spatial structure.This structure has given rise to three distinct communities:Shenzhen-Dongguan-Huizhou,Guangzhou-Foshan-Zhaoqing,and Zhuhai-Zhongshan-Jiangmen.Additionally,cities within the Greater Bay Area urban agglomeration play different roles,suggesting that varying development strategies may be necessary to achieve staggered development.The study demonstrates that large datasets represented by LBS can offer novel insights and methodologies for the examination of urban agglomeration network structures,contingent on the appropriate mining and processing of the data.
基金supported by the National Natu-ral Science Foundation of China(No.52102210)the Natural Sci-ence Foundation of Sichuan Province(Nos.2022NSFSC2005 and 2022NSFSC1255)+1 种基金the Opening Project of Key Laboratory of Op-toelectronic Chemical Materials and Devices of Ministry of Educa-tion,Jianghan University(No.JDGD-202218)Supplementary materials Supplementary material associated with this article can be found,in the online version,at doi:10.1016/j.jmst.2024.01.096.106。
文摘Corrosion engineering is an effective way to improve the oxygen evolution reaction(OER)activity of al-loys.However,the impact of grain boundary corrosion on the structure and electrochemical performance of alloy is still unknown.Herein,the vacuum arc-melted CrCoNiFe alloys with interlaced network struc-tures via grain boundary corrosion methods were fabricated.The grain boundaries that existed as de-fects were severely corroded and an interlaced network structure was formed,promoting the exposure of the active site and the release of gas bubbles.Besides,the(oxy)hydroxides layer(25 nm)on the sur-face could act as the true active center and improve the surface wettability.Benefiting from the unique structure and constructed surface,the CrCoNiFe-12 affords a high urea oxidation reaction(UOR)perfor-mance with the lowest overpotential of 250 mV at 10 mA/cm^(2)in 1 M KOH adding 0.33 M urea.The CrCoNiFe-12||Pt only required a cell voltage of 1.485 V to afford 10 mA/cm^(2)for UOR and long-term sta-bility of 100 h at 10 mA/cm^(2)(27.6 mV decrease).These findings offer a facile strategy for designing bulk multiple-principal-element alloy electrodes for energy conversion.
文摘Objective Using graph theory analysis,this study compares the topological and node attributes of the brain network to explore the differences in gray matter structural and functional network topological properties between bipolar depression(BD)patients with and without obsessive-compulsive symptoms(OCS).Methods A total of 90 BD patients(27 males,63 females;median age 19.0(22.0,25.0)years)were recruited from the psychiatric outpatient and inpatient departments of the First Affiliated Hospital of Jinan University between March 2018 and December 2022.Fifty healthy controls(19 males,31 females;median age:23.0(20.0,27.0)years)were also enrolled.The BD patients were divided into two groups based on the presence of OCS:53 with OCS(OCS group)and 37 without OCS(NOCS group).Resting-state structural and functional MRI data were collected for all participants to construct gray matter structural and functional networks.Graph therory analysis was aapplied to calculate network topological metrics such as small-world properties.The structural and functional network topological properties were compared among the BD-OCS,BD-nOCS,and control groups.Partial correlation analysis was conducted to examine the association between network topological metrics with significant group differences and Yale-Brown Obsessive-Compulsive Scale(Y-BOCS)scores.Support vector machines(SVM)were used with these metrics as classificationfeaturevalues toimproveediagnostic accuracy through pairwise group classification.Results Structural network analysis of gray matter:compared to HC group,both OCS group and NOCS group showed increasedshortesttpathlengthand standardized characteristic path length(shortest path length:0.78 and 0.80 vs.0.69;normalized characteristic path length:0.48 and 0.49 vs.0.43),and decreased global efficiency(0.21 and 0.21 vs.0.24)compared to the HC group(permutation test,all P<0.05).Compared to NOCS and HC groups,the OCS group showed increased nodal centrality and betweenness centrality in the right rolandic operculum and left superior occipital gyrus(permutation test,all P<0.05).Functional network analysis of gray matter:compared to the NOCS group,the OCS group showed increased node efficiency and decreased betweenness centrality in the cerebellum(t=2.15,-3.04;all P<0.05);compared to HC groups,the OCS group showed decreased betweenness centrality in the cerebellum and left inferior frontal gyrus,along with increased node centrality and nodal efficiency in the right transverse temporal gyrus(t=-2.99,-3.61,3.06,3.10;all P<0.05).In the 0CS group,betweenness centrality in the left inferior frontal gyrus positively correlated with Y-BOCS scale obsessive thinking score(r=0.303,P=0.034).Nodal centrality and node efficiency of the right transverse temporal gyrus negatively correlated with Y-BOCS total score(r=-0.301,-0.311)and Y-BOCS obsessional thinking scores(r=-0.385,-0.380)separately(all P<0.05).SVM classification:the combined network features achieved an area under the curve of 0.80 in distinguising OCS from NOCS patients.Conclusion BDOCS and BD-nOCS patients both exhibit consistent changes in gray matter structural network topology,with theOCSSgroup displaying more pronounced nodal topological abnormalities.Multi-network feature integration demostrates potential for diagnostic classfication.
基金Projects(50874045,51301194)supported by the National Natural Science Foundation of ChinaProject(2144057)supported by the Natural Science Foundation of Beijing Municipality,China
文摘Effect of network structure on plasticity and fracture mode of Zr？Al？Ni？Cu bulk metallic glasses （BMGs） was investigated. The microstructures of transversal and longitudinal sections were exposed by chemical etching and observed by scanning electron microscopy （SEM）. The mechanical properties were examined by room-temperature uniaxial compression test. The results show that both plasticity and fracture mode are significantly affected by the network structure and the alteration occurs when the size of the network structure reaches up to a critical value. When the cell size （dc） of the network structure is ~3μm, Zr-based BMGs characterize in plasticity that decreases with increasingdc. The fracture mode gradually transforms from single 45° shear fracture to double 45° shear fracture and then cleavage fracture with increasingdc. In addition, the mechanisms of the transition of the plasticity and the fracture mode for these Zr-based BMGs are also discussed.
基金supported by the National Natural Science Foundation of China(Nos.52101274,52377026 and 52472131)Taishan Scholars and Young Experts Program of Shandong Province,China(No.tsqn202103057)+4 种基金Natural Science Foundation of Shandong Province,China(Nos.ZR2020QE011 and ZR2022ME089)the Qingchuang Talents Induction Program of Shandong Higher Education Institution,China(Research and Innovation Team of Structural-Functional Polymer Composites)Youth Top Talent Foundation of Yantai University,China(No.2219008)Graduate Innovation Foundation of Yantai University,China(No.GIFYTU2240)College Student Innovation and Entrepreneurship Training Program Project,China(No.202311066088).
文摘Non-stoichiometric carbides have been proven to be effective electromagnetic wave(EMW)absorbing materials.In this study,phase and morphology of XZnC(X=Fe/Co/Cu)loaded on a three dimensional(3D)network structure melamine sponge(MS)carbon composites were investigated through vacuum filtration followed by calcination.The FeZnC/CoZnC/CuZnC with carbon nanotubes(CNTs)were uniformly dispersed on the surface of melamine sponge carbon skeleton and Co-containing sample exhibits the highest CNTs concentration.The minimum reflection loss(RL_(min))of the CoZnC/MS composite(m_(composite):m_(paraffin)=1:1,m represents mass)reached-33.60 dB,and the effective absorption bandwidth(EAB)reached 9.60 GHz.The outstanding electromagnetic wave absorption(EMWA)properties of the CoZnC/MS composite can be attributed to its unique hollow structure,which leads to multiple reflections and scattering.The formed conductive network improves dielectric and conductive loss.The incorporation of Co enhances the magnetic loss capability and optimizes interfacial polarization and dipole polarization.By simultaneously improving dielectric and magnetic losses,ex-cellent impedance matching performance is achieved.The clarification of element replacement in XZnC/MS composites provides an effi-cient design perspective for high-performance non-stoichiometric carbide EMW absorbers.
基金The National Natural Science Foundation of China(No70571013,70973017)Program for New Century Excellent Talentsin University (NoNCET-06-0471)Human Social Science Fund Project ofMinistry of Education (No09YJA630020)
文摘In order to simulate the real growing process, a new type of knowledge network growth mechanism based on local world connectivity is constructed. By the mean-field method, theoretical prediction of the degree distribution of the knowledge network is given, which is verified by Matlab simulations. When the new added node＇s local world size is very small, the degree distribution of the knowledge network approximately has the property of scale-free. When the new added node＇s local world size is not very small, the degree distribution transforms from pure power-law to the power-law with an exponential tailing. And the scale-free index increases as the number of new added edges decreases and the tunable parameters increase. Finally, comparisons of some knowledge indices in knowledge networks generated by the local world mechanism and the global mechanism are given. In the long run, compared with the global mechanism, the local world mechanism leads the average knowledge levels to slower growth and brings homogenous phenomena.
基金they have received the following grants during the research,writing,and/or publication of this paper:Anhui Province Social Science Planning Key Project(No.AHSKD2023D028)Research on the Construction of Historical Spatial Information Mapping of Traditional Villages in Huizhou and its Protection Methods.
文摘Amidst the rapid pace of urban development,rural communities continually face the challenges posed by erratic natural disasters and human-induced disturbances.Evaluating and improving the resilience of rural areas is crucial for achieving sustainable development.Examining the rural network framework serves as a method to achieve rural resilience.This study established a contact network encompassing 13 villages in Shiba town,Mingguang City,through the collection of time-distance data,questionnaire interview data,and map vector data to examine the spatial patterns of the rural network.The examination of structural resilience was conducted through the framework of complex network theory.The examination of the network’s transitivity and diversity through the frameworks of hierarchy,matching,transitivity,and aggregation reveals its resilience to disruption simulations,such as node failure.The findings indicate that the network exhibits a configuration marked by a dense central region,sparse connections in the north,and a lack of connectivity in the south.The network exhibits a flat structure,with nodes that are relatively uniform in nature.The network exhibits significant disassortativity,classifying it as a disassortative network,where villages with higher node degrees tend to connect with those having lower node degrees.The local transitivity of the network is significantly elevated,with approximately 90%of settlements necessitating just one transfer to establish direct communication.The network exhibits significant clustering effects,marked by robust connections among villages and a few isolated node villages.The transitivity of the network and its diverse spatial patterns show markedly different characteristics when subjected to interruption simulation.The study identified two primary nodes and one susceptible node.The findings from the study precisely reflect the characteristics of the rural network.This can provide theoretical perspectives for analyzing the resilience of rural network structures and support decision-making in rural planning and development.
文摘In recent years,deep learning has been introduced into the field of Single-pixel imaging(SPI),garnering significant attention.However,conventional networks still exhibit limitations in preserving image details.To address this issue,we integrate Large Kernel Convolution(LKconv)into the U-Net framework,proposing an enhanced network structure named U-LKconv network,which significantly enhances the capability to recover image details even under low sampling conditions.
