The rapid growth of distributed data-centric applications and AI workloads increases demand for low-latency,high-throughput communication,necessitating frequent and flexible updates to network routing configurations.H...The rapid growth of distributed data-centric applications and AI workloads increases demand for low-latency,high-throughput communication,necessitating frequent and flexible updates to network routing configurations.However,maintaining consistent forwarding states during these updates is challenging,particularly when rerouting multiple flows simultaneously.Existing approaches pay little attention to multi-flow update,where improper update sequences across data plane nodes may construct deadlock dependencies.Moreover,these methods typically involve excessive control-data plane interactions,incurring significant resource overhead and performance degradation.This paper presents P4LoF,an efficient loop-free update approach that enables the controller to reroute multiple flows through minimal interactions.P4LoF first utilizes a greedy-based algorithm to generate the shortest update dependency chain for the single-flow update.These chains are then dynamically merged into a dependency graph and resolved as a Shortest Common Super-sequence(SCS)problem to produce the update sequence of multi-flow update.To address deadlock dependencies in multi-flow updates,P4LoF builds a deadlock-fix forwarding model that leverages the flexible packet processing capabilities of the programmable data plane.Experimental results show that P4LoF reduces control-data plane interactions by at least 32.6%with modest overhead,while effectively guaranteeing loop-free consistency.展开更多
Shape memory polymers used in 4D printing only had one permanent shape after molding,which limited their applications in requiring multiple reconstructions and multifunctional shapes.Furthermore,the inherent stability...Shape memory polymers used in 4D printing only had one permanent shape after molding,which limited their applications in requiring multiple reconstructions and multifunctional shapes.Furthermore,the inherent stability of the triazine ring structure within cyanate ester(CE)crosslinked networks after molding posed significant challenges for both recycling,repairing,and degradation of resin.To address these obstacles,dynamic thiocyanate ester(TCE)bonds and photocurable group were incorporated into CE,obtaining the recyclable and 3D printable CE covalent adaptable networks(CANs),denoted as PTCE1.5.This material exhibits a Young's modulus of 810 MPa and a tensile strength of 50.8 MPa.Notably,damaged printed PTCE1.5 objects can be readily repaired through reprinting and interface rejoining by thermal treatment.Leveraging the solid-state plasticity,PTCE1.5 also demonstrated attractive shape memory ability and permanent shape reconfigurability,enabling its reconfigurable 4D printing.The printed PTCE1.5 hinges and a main body were assembled into a deployable and retractable satellite model,validating its potential application as a controllable component in the aerospace field.Moreover,printed PTCE1.5 can be fully degraded into thiol-modified intermediate products.Overall,this material not only enriches the application range of CE resin,but also provides a reliable approach to addressing environmental issue.展开更多
Objective:To predict the nephrotoxicity mechanism of Lianqiao-4 through network pharmacology and molecular docking methods.Methods:The main chemical components of Lianqiao(Forsythia suspensa),Bistortae rhizoma,Ophiopo...Objective:To predict the nephrotoxicity mechanism of Lianqiao-4 through network pharmacology and molecular docking methods.Methods:The main chemical components of Lianqiao(Forsythia suspensa),Bistortae rhizoma,Ophiopogonis radix,and Clematidis radix et rhizoma,as well as nephrotoxicity-related targets,were screened through databases such as TCMSP,Swiss Target Prediction,GeneCards,and ETCM.Venny 2.1.0 was used to identify the main components of Lianqiao-4 and nephrotoxicity targets.The STRING platform and David database were utilized to construct a protein-protein interaction(PPI)network diagram,while gene function(GO)enrichment analysis and KEGG pathway analysis were conducted.The“Lianqiao-4 active ingredients-nephrotoxicity targets-signaling pathways”network model was constructed using Cytoscape 3.9.1 software.Results:Network pharmacology and molecular docking analysis revealed that the core active ingredients responsible for the nephrotoxicity mechanism of Mongolian medicine Lianqiao-4 include steroidal saponins such as ophiopogonin A,flavonoids like kaempferol and quercetin,steroidal compounds such asβ-sitosterol and sitosterol,and other key regulatory targets including STAT3,ABCG2,HSP90AA1,MMP9,PTGS2,and EGFR.Major pathways involved include lipid and atherosclerosis,chemical carcinogenesis-DNA adducts,and arachidonic acid metabolism.Conclusion:Mongolian medicine Lianqiao-4 exerts its therapeutic effect on nephrotoxicity through multiple components,targets,and pathways,pending experimental verification.展开更多
(±)-Penicithrones A–D(1a/1b–4a/4b),four novel pairs of anthrone–cyclopentenone heterodimers characterized by a distinctive bridged 6/6/6−5 tetracyclic core skeleton,together with three previously identified co...(±)-Penicithrones A–D(1a/1b–4a/4b),four novel pairs of anthrone–cyclopentenone heterodimers characterized by a distinctive bridged 6/6/6−5 tetracyclic core skeleton,together with three previously identified compounds(5–7),were isolated from the crude extract of the mangrove-derived fungus Penicillium sp.,guided by heteronuclear single quantum correlation(HSQC)-based small molecule accurate recognition technology(SMART 2.0)and liquid chromatography-tandem mass spectrometry(LC-MS/MS)-based molecular networking.The structural elucidation of new compounds was accomplished through comprehensive spectroscopic analysis,and their absolute configurations were determined using DP4+^(13)C nuclear magnetic resonance(NMR)calculations and electronic circular dichroism(ECD)calculations.Compounds 1a/1b–4a/4b demonstrated moderate cytotoxicity against three human cancer cell lines HeLa,HCT116 and MCF-7 with half maximal inhibitory concentration(IC50)values ranging from 15.95±1.64 to 28.56±2.59μmol·L–1.展开更多
We collected the data on the Sendeng-4 chemical composition corresponding targets through the literature and from Drug Bank, SuperT arget, TTD(Therapeutic Targets Database) and other databases and the relevant signali...We collected the data on the Sendeng-4 chemical composition corresponding targets through the literature and from Drug Bank, SuperT arget, TTD(Therapeutic Targets Database) and other databases and the relevant signaling pathways from the KEGG(Kyoto Encyclopedia of Genes and Genomes) database and established models of the chemical composition-target network and chemical composition-target- disease network using Cytoscape software, the analysis indicated that the chemical composition had at least nine different types of targets that acted together to exert effects on the diseases, suggesting a "multi-component, multi-target" feature of the traditional Mongolian medicine. We also employed the rat model of rheumatoid arthritis induced by Collgen Type II to validate the key targets of the chemical components of Sendeng-4, and three of the key targets were validated through laboratory experiments, further confirming the anti-inflammatory effects of Sendeng-4. In all, this study predicted the active ingredients and targets of Sendeng-4, and explored its mechanism of action, which provided new strategies and methods for further research and development of Sendeng-4 and other traditional Mongolian medicines as well.展开更多
Accident causation analysis is of great importance for accident prevention.In order to improve the aviation safety,a new analysis method of aviation accident causation based on complex network theory is proposed in th...Accident causation analysis is of great importance for accident prevention.In order to improve the aviation safety,a new analysis method of aviation accident causation based on complex network theory is proposed in this paper.Through selecting 257 accident investigation reports,45 causative factors and nine accident types are obtained by the three-level coding process of the grounded theory,and the interaction of these factors is analyzed based on the“2-4”model.Accordingly,the aviation accident causation network is constructed based on complex network theory which has scale-free characteristics and small-world properties,the characteristics of causative factors are analyzed by the topology of the network,and the key causative factors of the accidents are identified by the technique for order of preference by similarity to ideal solution(TOPSIS)method.The comparison results show that the method proposed in this paper has the advantages of independent of expert experience,quantitative analysis of accident causative factors and statistical analysis of a lot of accident data,and it has better applicability and advancement.展开更多
A new three-dimensional supramolecular [Ce2（2,5-pydc）3（H2O）2]（1） has been hydrothermally synthesized at 180 ℃ and characterized by single-crystal X-ray diffraction.X-ray crystal analyses reveal that the compoun...A new three-dimensional supramolecular [Ce2（2,5-pydc）3（H2O）2]（1） has been hydrothermally synthesized at 180 ℃ and characterized by single-crystal X-ray diffraction.X-ray crystal analyses reveal that the compound belongs to the monoclinic system,space group P21/c,C21H13Ce2N3O14,a = 6.561（1）,b = 17.986（5）,c = 9.411（3） ,β = 95.558（5）° and Z = 2.In the structure of 1,each Ce（1） center is surrounded by 2,5-pydc ligands,forming the 6-connected node,and the 2,5-pydc ligand coordinates to the Ce（Ⅲ） in two different coordination modes.In mode 1,the four oxygen atoms of two carboxyl groups connect neighboring Ce（Ⅲ） ions,giving 4-connected（4-c） second building unit（SBU-1）.Furthermore,the structure is extended into a 2-D layer from SBU-1 by sharing Ce（1） atoms.In mode 2,the ligand coordinates to the Ce（Ⅲ） ion from the adjacent chain with the 4-connected（4-c） second building unit（SBU-2）,generating a 1-D ladder from SBU-2 by sharing Ce（1） atoms.Finally,the structure is extended into a 6,4,4-c network.Its photoluminescence property was also investigated.展开更多
Titanium dioxide （TiO2） nanoparticles were prepared by sol gel route. The preparation parameters were optimized in the removal of 4-nitropbenol （4-NP）. All catalysts were analyzed by X-ray diffraction （XRD） and ...Titanium dioxide （TiO2） nanoparticles were prepared by sol gel route. The preparation parameters were optimized in the removal of 4-nitropbenol （4-NP）. All catalysts were analyzed by X-ray diffraction （XRD） and scanning electron microscopy （SEM）. An artificial neural network model （ANN） was developed to predict the photocatalytic removal of 4-NP in the presence of TiOz nanoparticles prepared under desired conditions. The comparison between the predicted results by designed ANN model and the experimental data proved that modeling of the removal process of 4-NP using artificial neural network was a precise method to predict the extent of 4-NP removal under different conditions.展开更多
In the study of complex networks almost all theoretical models have the property of infinite growth, but the size of actual networks is finite. According to statistics from the China Internet IPv4 （Internet Protocol ...In the study of complex networks almost all theoretical models have the property of infinite growth, but the size of actual networks is finite. According to statistics from the China Internet IPv4 （Internet Protocol version 4） addresses, this paper proposes a forecasting model by using S curve （logistic curve）. The growing trend of IPv4 addresses in China is forecasted. There are some reference values for optimizing the distribution of IPv4 address resource and the development of IPv6. Based on the laws of IPv4 growth, that is, the bulk growth and the finitely growing limit, it proposes a finite network model with a bulk growth. The model is said to be an S-curve network. Analysis demonstrates that the analytic method based on uniform distributions （i.e., Barabasi-Albert method） is not suitable for the network. It develops an approximate method to predict the growth dynamics of the individual nodes, and uses this to calculate analytically the degree distribution and the scaling exponents. The analytical result agrees with the simulation well, obeying an approximately power-law form. This method can overcome a shortcoming of Barabasi-Albert method commonly used in current network research.展开更多
A fuzzy neural network (FNN) model is developed to predict the 4-CBA concentration of the oxidation unit in purified terephthalic acid process. Several technologies are used to deal with the process data before modeli...A fuzzy neural network (FNN) model is developed to predict the 4-CBA concentration of the oxidation unit in purified terephthalic acid process. Several technologies are used to deal with the process data before modeling.First,a set of preliminary input variables is selected according to prior knowledge and experience. Secondly,a method based on the maximum correlation coefficient is proposed to detect the dead time between the process variables and response variables. Finally, the fuzzy curve method is used to reduce the unimportant input variables.The simulation results based on industrial data show that the relative error range of the FNN model is narrower than that of the American Oil Company (AMOCO) model. Furthermore, the FNN model can predict the trend of the 4-CBA concentration more accurately.展开更多
With rising capacity demand in mobile networks, the infrastructure is also becoming increasingly denser and complex. This results in collection of larger amount of raw data(big data) that is generated at different lev...With rising capacity demand in mobile networks, the infrastructure is also becoming increasingly denser and complex. This results in collection of larger amount of raw data(big data) that is generated at different levels of network architecture and is typically underutilized. To unleash its full value, innovative machine learning algorithms need to be utilized in order to extract valuable insights which can be used for improving the overall network's performance. Additionally, a major challenge for network operators is to cope up with increasing number of complete(or partial) cell outages and to simultaneously reduce operational expenditure. This paper contributes towards the aforementioned problems by exploiting big data generated from the core network of 4 G LTE-A to detect network's anomalous behavior. We present a semi-supervised statistical-based anomaly detection technique to identify in time: first, unusually low user activity region depicting sleeping cell, which is a special case of cell outage; and second, unusually high user traffic area corresponding to a situation where special action such as additional resource allocation, fault avoidance solution etc. may be needed. Achieved results demonstrate that the proposed method can be used for timely and reliable anomaly detection in current and future cellular networks.展开更多
Carbon fiber(C_(f))reinforced pyrolytic carbon(PyC)composites simultaneously possessing robust mechanical strength,excellent friction performances and outstanding anti-ablation properties are demanded for advanced aer...Carbon fiber(C_(f))reinforced pyrolytic carbon(PyC)composites simultaneously possessing robust mechanical strength,excellent friction performances and outstanding anti-ablation properties are demanded for advanced aerospace applications.Efficient architecture design and optimization of composites are promi-nent yet remain high challenging for realizing the above requirements.Herein,binary reinforcements of networked silicon nitride nanowires(Si_(3)N_(4) nws)and interconnected graphene(GE)have been successfully constructed into C f/PyC by precursor impregnation-pyrolysis and chemical vapor deposition.Notably,net-worked Si_(3)N_(4) nws are uniformly distributed among the carbon fibers,while interconnected GE is firmly rooted on the surface of both networked Si_(3)N_(4) nws and carbon fibers.In the networked Si_(3)N_(4) nws and interconnected GE reinforced C_(f)/PyC,networked Si_(3)N_(4) nws significantly boost the cohesion strength of PyC,while GE markedly improves the interface bonding of both Si_(3)N_(4) nws/PyC and fiber/PyC.Benefiting from the synergistic reinforcement effect of networked Si_(3)N_(4) nws and interconnected GE,the C_(f)/PyC have a prominent enhancement in mechanical(shear and compressive strengths increased by 119.9% and 52.84%,respectively)and friction(friction coefficient and wear rate reduced by 25.40% and 60.10%,respectively)as well as anti-ablation(mass ablation rate and linear ablation rate decreased by 71.25% and 63.01%,respectively).This present strategy for networked Si_(3)N_(4) nws and interconnected GE reinforced C_(f)/PyC provides a dominant route to produce mechanically robust,frictionally resisting and ablatively resistant materials for use in advanced aerospace applications.展开更多
The air cooler is an important equipment in the petroleum refining industry.Ammonium chloride(NH4 Cl)deposition-induced corrosion is one of its main failure forms.In this study,the ammonium salt crystallization temper...The air cooler is an important equipment in the petroleum refining industry.Ammonium chloride(NH4 Cl)deposition-induced corrosion is one of its main failure forms.In this study,the ammonium salt crystallization temperature is chosen as the key decision variable of NH4 Cl deposition-induced corrosion through in-depth mechanism research and experimental analysis.The functional link neural network(FLNN)is adopted as the basic algorithm for modeling because of its advantages in dealing with non-linear problems and its fast-computational ability.A hybrid FLNN attached to a small norm is built to improve the generalization performance of the model.Then,the trained model is used to predict the NH4 Cl salt crystallization temperature in the air cooler of a sour water stripper plant.Experimental results show the proposed improved FLNN algorithm can achieve better generalization performance than the PLS,the back propagation neural network,and the conventional FLNN models.展开更多
Soft sensor is attractive in dealing with online product quality measurement by virtue of other easily measured variables. In AMOCO PTA (purified terephthalic acid) production process, the unavailability of real-time ...Soft sensor is attractive in dealing with online product quality measurement by virtue of other easily measured variables. In AMOCO PTA (purified terephthalic acid) production process, the unavailability of real-time measurement of 4-CBA makes it impossible for timely adjustment and thereby influences the product quality and the plant economy benefit. In this paper, a kind of FCMAC (fuzzy cerebellar model articulation controller) method is presented to solve the online measurement problem. Different from the conventional CMAC (cerebellar model articulation controller) networks, which has inferior smoothing ability because of its table look-up based technology. Integrating fuzzy model into CMAC networks, it becomes more accurate in functional mapping without weakening its generalization ability. Numerical example and industrial application results show the method proposed here is satisfactory and feasible.展开更多
This paper relates to an advanced open mobile communication system and method of integrating the mobile communications, wireless access systems and wired communications into one common platform architecture for China&...This paper relates to an advanced open mobile communication system and method of integrating the mobile communications, wireless access systems and wired communications into one common platform architecture for China's 4th generation mobile communications, supporting costeffective broadband voice, data and video services in wireless, mobile and wired environment with one single integrated mobile terminal device. The paper includes new architecture in the integrated mobile device and converged network access, and minimum modifi cation in the existing mobile telecommunication infrastructures. This paper introduces the long-term evolution strategy for China's TDD system platform towards China's future 4G mobile communications.展开更多
NCW(network centric warfare) is an information warfare concentrating on network. A global network-centric warfare architecture with OGSA grid technology is put forward,which is a four levels system including the user ...NCW(network centric warfare) is an information warfare concentrating on network. A global network-centric warfare architecture with OGSA grid technology is put forward,which is a four levels system including the user level, the application level, the grid middleware layer and the resource level. In grid middleware layer,based on virtual hosting environment, a BEPL4WS grid service composition method is introduced. In addition, the NCW grid service model is built with the help of Eclipse-SDK-3.0.1 and Bpws4j.展开更多
Warm rotary draw bending provides a feasible method to form the large-diameter thin-walled（LDTW）TC4 bent tubes, which are widely used in the pneumatic system of aircrafts. An accurate prediction of flow behavior of ...Warm rotary draw bending provides a feasible method to form the large-diameter thin-walled（LDTW）TC4 bent tubes, which are widely used in the pneumatic system of aircrafts. An accurate prediction of flow behavior of TC4 tubes considering the couple effects of temperature,strain rate and strain is critical for understanding the deformation behavior of metals and optimizing the processing parameters in warm rotary draw bending of TC4 tubes. In this study, isothermal compression tests of TC4 tube alloy were performed from 573 to 873 K with an interval of 100 K and strain rates of 0.001, 0.010 and0.100 s^（-1）. The prediction of flow behavior was done using two constitutive models, namely modified Arrhenius model and artificial neural network（ANN） model. The predictions of these constitutive models were compared using statistical measures like correlation coefficient（R）, average absolute relative error（AARE） and its variation with the deformation parameters（temperature, strain rate and strain）. Analysis of statistical measures reveals that the two models show high predicted accuracy in terms of R and AARE. Comparatively speaking, the ANN model presents higher predicted accuracy than the modified Arrhenius model. In addition, the predicted accuracy of ANN model presents high stability at the whole deformation parameter ranges, whereas the predictability of the modified Arrhenius model has some fluctuation at different deformation conditions. It presents higher predicted accuracy at temperatures of 573-773 K, strain rates of 0.010-0.100 s^（-1）and strain of 0.04-0.32, while low accuracy at temperature of 873 K, strain rates of 0.001 s^（-1）and strain of 0.36-0.48.Thus, the application of modified Arrhenius model is limited by its relatively low predicted accuracy at some deformation conditions, while the ANN model presents very high predicted accuracy at all deformation conditions,which can be used to study the compression behavior of TC4 tube at the temperature range of 573-873 K and the strain rate of 0.001-0.100 s^（-1）. It can provide guideline for the design of processing parameters in warm rotary draw bending of LDTW TC4 tubes.展开更多
Multi-bond network(MBN) hydrogels contain hierarchical dynamic bonds with different bond association energy as energy dissipation units,enabling super-tough mechanical properties.In this work,we copolymerize a protona...Multi-bond network(MBN) hydrogels contain hierarchical dynamic bonds with different bond association energy as energy dissipation units,enabling super-tough mechanical properties.In this work,we copolymerize a protonated 2-ureido-4[1 H]-pyrimidone(UPy)-contained monomer with acrylic acid in HCl solution.After removing excess HCl,UPy motifs are deprotonated and from dimers,thus generating an UPy-contained MBN hydrogel.The obtained MBN hydrogels(75 wt% watercontent) exhibit super-tough mechanical properties(0.39 MPa to 2.51 MPa tensile strength),with tremendous amount of energy(1.68 MJ/m^(3) to 11.1 MJ/m^(3)) dissipated by the dissociation of UPy dimers.The introduction of ionic bonds can further improve the mechanical properties.Moreover,owing to their dynamic nature,both UPy dimers and ionic bonds can re-associate after being dissociated,resulting in excellent self-recovery ability(around 90% recovery efficiency within only 1 h).The excellent self-recovery ability mainly originates from the re-association of UPy dimers based on the high dimerization constant of UPy motifs.展开更多
基金supported by the National Key Research and Development Program of China under Grant 2022YFB2901501in part by the Science and Technology Innovation leading Talents Subsidy Project of Central Plains under Grant 244200510038.
文摘The rapid growth of distributed data-centric applications and AI workloads increases demand for low-latency,high-throughput communication,necessitating frequent and flexible updates to network routing configurations.However,maintaining consistent forwarding states during these updates is challenging,particularly when rerouting multiple flows simultaneously.Existing approaches pay little attention to multi-flow update,where improper update sequences across data plane nodes may construct deadlock dependencies.Moreover,these methods typically involve excessive control-data plane interactions,incurring significant resource overhead and performance degradation.This paper presents P4LoF,an efficient loop-free update approach that enables the controller to reroute multiple flows through minimal interactions.P4LoF first utilizes a greedy-based algorithm to generate the shortest update dependency chain for the single-flow update.These chains are then dynamically merged into a dependency graph and resolved as a Shortest Common Super-sequence(SCS)problem to produce the update sequence of multi-flow update.To address deadlock dependencies in multi-flow updates,P4LoF builds a deadlock-fix forwarding model that leverages the flexible packet processing capabilities of the programmable data plane.Experimental results show that P4LoF reduces control-data plane interactions by at least 32.6%with modest overhead,while effectively guaranteeing loop-free consistency.
基金supported by the National Natural Science Foundation of China(Nos.52473080,52403167 and 52173079)the Fundamental Research Funds for the Central Universities(Nos.xtr052023001 and xzy012023037)+1 种基金the Postdoctoral Research Project of Shaanxi Province(No.2024BSHSDZZ054)the Shaanxi Laboratory of Advanced Materials(No.2024ZY-JCYJ-04-12).
文摘Shape memory polymers used in 4D printing only had one permanent shape after molding,which limited their applications in requiring multiple reconstructions and multifunctional shapes.Furthermore,the inherent stability of the triazine ring structure within cyanate ester(CE)crosslinked networks after molding posed significant challenges for both recycling,repairing,and degradation of resin.To address these obstacles,dynamic thiocyanate ester(TCE)bonds and photocurable group were incorporated into CE,obtaining the recyclable and 3D printable CE covalent adaptable networks(CANs),denoted as PTCE1.5.This material exhibits a Young's modulus of 810 MPa and a tensile strength of 50.8 MPa.Notably,damaged printed PTCE1.5 objects can be readily repaired through reprinting and interface rejoining by thermal treatment.Leveraging the solid-state plasticity,PTCE1.5 also demonstrated attractive shape memory ability and permanent shape reconfigurability,enabling its reconfigurable 4D printing.The printed PTCE1.5 hinges and a main body were assembled into a deployable and retractable satellite model,validating its potential application as a controllable component in the aerospace field.Moreover,printed PTCE1.5 can be fully degraded into thiol-modified intermediate products.Overall,this material not only enriches the application range of CE resin,but also provides a reliable approach to addressing environmental issue.
文摘Objective:To predict the nephrotoxicity mechanism of Lianqiao-4 through network pharmacology and molecular docking methods.Methods:The main chemical components of Lianqiao(Forsythia suspensa),Bistortae rhizoma,Ophiopogonis radix,and Clematidis radix et rhizoma,as well as nephrotoxicity-related targets,were screened through databases such as TCMSP,Swiss Target Prediction,GeneCards,and ETCM.Venny 2.1.0 was used to identify the main components of Lianqiao-4 and nephrotoxicity targets.The STRING platform and David database were utilized to construct a protein-protein interaction(PPI)network diagram,while gene function(GO)enrichment analysis and KEGG pathway analysis were conducted.The“Lianqiao-4 active ingredients-nephrotoxicity targets-signaling pathways”network model was constructed using Cytoscape 3.9.1 software.Results:Network pharmacology and molecular docking analysis revealed that the core active ingredients responsible for the nephrotoxicity mechanism of Mongolian medicine Lianqiao-4 include steroidal saponins such as ophiopogonin A,flavonoids like kaempferol and quercetin,steroidal compounds such asβ-sitosterol and sitosterol,and other key regulatory targets including STAT3,ABCG2,HSP90AA1,MMP9,PTGS2,and EGFR.Major pathways involved include lipid and atherosclerosis,chemical carcinogenesis-DNA adducts,and arachidonic acid metabolism.Conclusion:Mongolian medicine Lianqiao-4 exerts its therapeutic effect on nephrotoxicity through multiple components,targets,and pathways,pending experimental verification.
基金supported by the National Key Research and Development Program of China(No.2022YFC2303100)the National Natural Science Foundation of China(Nos.32022002 and 21977113).
文摘(±)-Penicithrones A–D(1a/1b–4a/4b),four novel pairs of anthrone–cyclopentenone heterodimers characterized by a distinctive bridged 6/6/6−5 tetracyclic core skeleton,together with three previously identified compounds(5–7),were isolated from the crude extract of the mangrove-derived fungus Penicillium sp.,guided by heteronuclear single quantum correlation(HSQC)-based small molecule accurate recognition technology(SMART 2.0)and liquid chromatography-tandem mass spectrometry(LC-MS/MS)-based molecular networking.The structural elucidation of new compounds was accomplished through comprehensive spectroscopic analysis,and their absolute configurations were determined using DP4+^(13)C nuclear magnetic resonance(NMR)calculations and electronic circular dichroism(ECD)calculations.Compounds 1a/1b–4a/4b demonstrated moderate cytotoxicity against three human cancer cell lines HeLa,HCT116 and MCF-7 with half maximal inhibitory concentration(IC50)values ranging from 15.95±1.64 to 28.56±2.59μmol·L–1.
基金supported by the National Natural Science Foundation of China(No.81160550)Inner Mongolia Natural Science Foundation(No.2013JQ03)2010 Science and Technology Project of social development in Inner Mongolia
文摘We collected the data on the Sendeng-4 chemical composition corresponding targets through the literature and from Drug Bank, SuperT arget, TTD(Therapeutic Targets Database) and other databases and the relevant signaling pathways from the KEGG(Kyoto Encyclopedia of Genes and Genomes) database and established models of the chemical composition-target network and chemical composition-target- disease network using Cytoscape software, the analysis indicated that the chemical composition had at least nine different types of targets that acted together to exert effects on the diseases, suggesting a "multi-component, multi-target" feature of the traditional Mongolian medicine. We also employed the rat model of rheumatoid arthritis induced by Collgen Type II to validate the key targets of the chemical components of Sendeng-4, and three of the key targets were validated through laboratory experiments, further confirming the anti-inflammatory effects of Sendeng-4. In all, this study predicted the active ingredients and targets of Sendeng-4, and explored its mechanism of action, which provided new strategies and methods for further research and development of Sendeng-4 and other traditional Mongolian medicines as well.
基金supported by the Civil Aviation Joint Fund of National Natural Science Foundation of China(No.U1533112)。
文摘Accident causation analysis is of great importance for accident prevention.In order to improve the aviation safety,a new analysis method of aviation accident causation based on complex network theory is proposed in this paper.Through selecting 257 accident investigation reports,45 causative factors and nine accident types are obtained by the three-level coding process of the grounded theory,and the interaction of these factors is analyzed based on the“2-4”model.Accordingly,the aviation accident causation network is constructed based on complex network theory which has scale-free characteristics and small-world properties,the characteristics of causative factors are analyzed by the topology of the network,and the key causative factors of the accidents are identified by the technique for order of preference by similarity to ideal solution(TOPSIS)method.The comparison results show that the method proposed in this paper has the advantages of independent of expert experience,quantitative analysis of accident causative factors and statistical analysis of a lot of accident data,and it has better applicability and advancement.
文摘A new three-dimensional supramolecular [Ce2（2,5-pydc）3（H2O）2]（1） has been hydrothermally synthesized at 180 ℃ and characterized by single-crystal X-ray diffraction.X-ray crystal analyses reveal that the compound belongs to the monoclinic system,space group P21/c,C21H13Ce2N3O14,a = 6.561（1）,b = 17.986（5）,c = 9.411（3） ,β = 95.558（5）° and Z = 2.In the structure of 1,each Ce（1） center is surrounded by 2,5-pydc ligands,forming the 6-connected node,and the 2,5-pydc ligand coordinates to the Ce（Ⅲ） in two different coordination modes.In mode 1,the four oxygen atoms of two carboxyl groups connect neighboring Ce（Ⅲ） ions,giving 4-connected（4-c） second building unit（SBU-1）.Furthermore,the structure is extended into a 2-D layer from SBU-1 by sharing Ce（1） atoms.In mode 2,the ligand coordinates to the Ce（Ⅲ） ion from the adjacent chain with the 4-connected（4-c） second building unit（SBU-2）,generating a 1-D ladder from SBU-2 by sharing Ce（1） atoms.Finally,the structure is extended into a 6,4,4-c network.Its photoluminescence property was also investigated.
文摘Titanium dioxide （TiO2） nanoparticles were prepared by sol gel route. The preparation parameters were optimized in the removal of 4-nitropbenol （4-NP）. All catalysts were analyzed by X-ray diffraction （XRD） and scanning electron microscopy （SEM）. An artificial neural network model （ANN） was developed to predict the photocatalytic removal of 4-NP in the presence of TiOz nanoparticles prepared under desired conditions. The comparison between the predicted results by designed ANN model and the experimental data proved that modeling of the removal process of 4-NP using artificial neural network was a precise method to predict the extent of 4-NP removal under different conditions.
基金Project supported by the National Natural Science Foundation of China (Grant No. 70871082)the Shanghai Leading Academic Discipline Project (Grant No. S30504)
文摘In the study of complex networks almost all theoretical models have the property of infinite growth, but the size of actual networks is finite. According to statistics from the China Internet IPv4 （Internet Protocol version 4） addresses, this paper proposes a forecasting model by using S curve （logistic curve）. The growing trend of IPv4 addresses in China is forecasted. There are some reference values for optimizing the distribution of IPv4 address resource and the development of IPv6. Based on the laws of IPv4 growth, that is, the bulk growth and the finitely growing limit, it proposes a finite network model with a bulk growth. The model is said to be an S-curve network. Analysis demonstrates that the analytic method based on uniform distributions （i.e., Barabasi-Albert method） is not suitable for the network. It develops an approximate method to predict the growth dynamics of the individual nodes, and uses this to calculate analytically the degree distribution and the scaling exponents. The analytical result agrees with the simulation well, obeying an approximately power-law form. This method can overcome a shortcoming of Barabasi-Albert method commonly used in current network research.
基金Supported by the National Outstanding Youth Science Foundation of China (No. 60025308).
文摘A fuzzy neural network (FNN) model is developed to predict the 4-CBA concentration of the oxidation unit in purified terephthalic acid process. Several technologies are used to deal with the process data before modeling.First,a set of preliminary input variables is selected according to prior knowledge and experience. Secondly,a method based on the maximum correlation coefficient is proposed to detect the dead time between the process variables and response variables. Finally, the fuzzy curve method is used to reduce the unimportant input variables.The simulation results based on industrial data show that the relative error range of the FNN model is narrower than that of the American Oil Company (AMOCO) model. Furthermore, the FNN model can predict the trend of the 4-CBA concentration more accurately.
基金supported in part by the National Natural Science Foundation of China under the Grants No.61431011 and 61671371the National Science and Technology Major Project under Grant no.2016ZX03001016-005+1 种基金the Key Research and Development Program of Shaanxi Province under Grant No.2017ZDXM-G-Y-012the Fundamental Research Funds for the Central Universities
文摘With rising capacity demand in mobile networks, the infrastructure is also becoming increasingly denser and complex. This results in collection of larger amount of raw data(big data) that is generated at different levels of network architecture and is typically underutilized. To unleash its full value, innovative machine learning algorithms need to be utilized in order to extract valuable insights which can be used for improving the overall network's performance. Additionally, a major challenge for network operators is to cope up with increasing number of complete(or partial) cell outages and to simultaneously reduce operational expenditure. This paper contributes towards the aforementioned problems by exploiting big data generated from the core network of 4 G LTE-A to detect network's anomalous behavior. We present a semi-supervised statistical-based anomaly detection technique to identify in time: first, unusually low user activity region depicting sleeping cell, which is a special case of cell outage; and second, unusually high user traffic area corresponding to a situation where special action such as additional resource allocation, fault avoidance solution etc. may be needed. Achieved results demonstrate that the proposed method can be used for timely and reliable anomaly detection in current and future cellular networks.
基金financially supported by the National Natural Science Foundation of China(No.51872232)the Research Fund of the State Key Laboratory of Solidification Processing(NWPU),China(No.136-QP-2015)+4 种基金the“111”project of China(No.B08040)the National Training Program of Innovation and Entrepreneurship for Undergraduates(No.S202010699336)the Joint Funds of the National Natural Science Foundation of China(No.U21B2067)the Key Scientific and Technological Innovation Research Team of Shaanxi Province(No.2022TD-31)the Key R&D Program of Shaanxi Province(No.2021ZDLGY14-04).
文摘Carbon fiber(C_(f))reinforced pyrolytic carbon(PyC)composites simultaneously possessing robust mechanical strength,excellent friction performances and outstanding anti-ablation properties are demanded for advanced aerospace applications.Efficient architecture design and optimization of composites are promi-nent yet remain high challenging for realizing the above requirements.Herein,binary reinforcements of networked silicon nitride nanowires(Si_(3)N_(4) nws)and interconnected graphene(GE)have been successfully constructed into C f/PyC by precursor impregnation-pyrolysis and chemical vapor deposition.Notably,net-worked Si_(3)N_(4) nws are uniformly distributed among the carbon fibers,while interconnected GE is firmly rooted on the surface of both networked Si_(3)N_(4) nws and carbon fibers.In the networked Si_(3)N_(4) nws and interconnected GE reinforced C_(f)/PyC,networked Si_(3)N_(4) nws significantly boost the cohesion strength of PyC,while GE markedly improves the interface bonding of both Si_(3)N_(4) nws/PyC and fiber/PyC.Benefiting from the synergistic reinforcement effect of networked Si_(3)N_(4) nws and interconnected GE,the C_(f)/PyC have a prominent enhancement in mechanical(shear and compressive strengths increased by 119.9% and 52.84%,respectively)and friction(friction coefficient and wear rate reduced by 25.40% and 60.10%,respectively)as well as anti-ablation(mass ablation rate and linear ablation rate decreased by 71.25% and 63.01%,respectively).This present strategy for networked Si_(3)N_(4) nws and interconnected GE reinforced C_(f)/PyC provides a dominant route to produce mechanically robust,frictionally resisting and ablatively resistant materials for use in advanced aerospace applications.
基金supported by the National Natural Science Foundation of China(Grant No.51876194,U1909216)the China Petrochemical Corporation Research Project(318023-2)the Zhejiang Public Welfare Technology Research Project(LGG20F030007)。
文摘The air cooler is an important equipment in the petroleum refining industry.Ammonium chloride(NH4 Cl)deposition-induced corrosion is one of its main failure forms.In this study,the ammonium salt crystallization temperature is chosen as the key decision variable of NH4 Cl deposition-induced corrosion through in-depth mechanism research and experimental analysis.The functional link neural network(FLNN)is adopted as the basic algorithm for modeling because of its advantages in dealing with non-linear problems and its fast-computational ability.A hybrid FLNN attached to a small norm is built to improve the generalization performance of the model.Then,the trained model is used to predict the NH4 Cl salt crystallization temperature in the air cooler of a sour water stripper plant.Experimental results show the proposed improved FLNN algorithm can achieve better generalization performance than the PLS,the back propagation neural network,and the conventional FLNN models.
基金Supported by the special Funds for Major State Basic Research Program of China (973 Program) (No. 2002CB312200) the 863 Hi-Tech. Research and Development Program of China (No. 2001AA413130, No.2002AA412110)the Key Technologies R&D Programme of China (No. 2001BA201A04).
文摘Soft sensor is attractive in dealing with online product quality measurement by virtue of other easily measured variables. In AMOCO PTA (purified terephthalic acid) production process, the unavailability of real-time measurement of 4-CBA makes it impossible for timely adjustment and thereby influences the product quality and the plant economy benefit. In this paper, a kind of FCMAC (fuzzy cerebellar model articulation controller) method is presented to solve the online measurement problem. Different from the conventional CMAC (cerebellar model articulation controller) networks, which has inferior smoothing ability because of its table look-up based technology. Integrating fuzzy model into CMAC networks, it becomes more accurate in functional mapping without weakening its generalization ability. Numerical example and industrial application results show the method proposed here is satisfactory and feasible.
文摘This paper relates to an advanced open mobile communication system and method of integrating the mobile communications, wireless access systems and wired communications into one common platform architecture for China's 4th generation mobile communications, supporting costeffective broadband voice, data and video services in wireless, mobile and wired environment with one single integrated mobile terminal device. The paper includes new architecture in the integrated mobile device and converged network access, and minimum modifi cation in the existing mobile telecommunication infrastructures. This paper introduces the long-term evolution strategy for China's TDD system platform towards China's future 4G mobile communications.
文摘NCW(network centric warfare) is an information warfare concentrating on network. A global network-centric warfare architecture with OGSA grid technology is put forward,which is a four levels system including the user level, the application level, the grid middleware layer and the resource level. In grid middleware layer,based on virtual hosting environment, a BEPL4WS grid service composition method is introduced. In addition, the NCW grid service model is built with the help of Eclipse-SDK-3.0.1 and Bpws4j.
基金financially supported by the National Natural Science Foundation of China(Nos.51275415 and50905144)the Natural Science Basic Research Plan in Shanxi Province(No.2011JQ6004)the Program of the Ministry of Education of China for Introducing Talents of Discipline to Universities(No.B08040)
文摘Warm rotary draw bending provides a feasible method to form the large-diameter thin-walled（LDTW）TC4 bent tubes, which are widely used in the pneumatic system of aircrafts. An accurate prediction of flow behavior of TC4 tubes considering the couple effects of temperature,strain rate and strain is critical for understanding the deformation behavior of metals and optimizing the processing parameters in warm rotary draw bending of TC4 tubes. In this study, isothermal compression tests of TC4 tube alloy were performed from 573 to 873 K with an interval of 100 K and strain rates of 0.001, 0.010 and0.100 s^（-1）. The prediction of flow behavior was done using two constitutive models, namely modified Arrhenius model and artificial neural network（ANN） model. The predictions of these constitutive models were compared using statistical measures like correlation coefficient（R）, average absolute relative error（AARE） and its variation with the deformation parameters（temperature, strain rate and strain）. Analysis of statistical measures reveals that the two models show high predicted accuracy in terms of R and AARE. Comparatively speaking, the ANN model presents higher predicted accuracy than the modified Arrhenius model. In addition, the predicted accuracy of ANN model presents high stability at the whole deformation parameter ranges, whereas the predictability of the modified Arrhenius model has some fluctuation at different deformation conditions. It presents higher predicted accuracy at temperatures of 573-773 K, strain rates of 0.010-0.100 s^（-1）and strain of 0.04-0.32, while low accuracy at temperature of 873 K, strain rates of 0.001 s^（-1）and strain of 0.36-0.48.Thus, the application of modified Arrhenius model is limited by its relatively low predicted accuracy at some deformation conditions, while the ANN model presents very high predicted accuracy at all deformation conditions,which can be used to study the compression behavior of TC4 tube at the temperature range of 573-873 K and the strain rate of 0.001-0.100 s^（-1）. It can provide guideline for the design of processing parameters in warm rotary draw bending of LDTW TC4 tubes.
基金the National Natural Science Foundation of China(Nos.21774069,51633003 and 21474058)for financial support。
文摘Multi-bond network(MBN) hydrogels contain hierarchical dynamic bonds with different bond association energy as energy dissipation units,enabling super-tough mechanical properties.In this work,we copolymerize a protonated 2-ureido-4[1 H]-pyrimidone(UPy)-contained monomer with acrylic acid in HCl solution.After removing excess HCl,UPy motifs are deprotonated and from dimers,thus generating an UPy-contained MBN hydrogel.The obtained MBN hydrogels(75 wt% watercontent) exhibit super-tough mechanical properties(0.39 MPa to 2.51 MPa tensile strength),with tremendous amount of energy(1.68 MJ/m^(3) to 11.1 MJ/m^(3)) dissipated by the dissociation of UPy dimers.The introduction of ionic bonds can further improve the mechanical properties.Moreover,owing to their dynamic nature,both UPy dimers and ionic bonds can re-associate after being dissociated,resulting in excellent self-recovery ability(around 90% recovery efficiency within only 1 h).The excellent self-recovery ability mainly originates from the re-association of UPy dimers based on the high dimerization constant of UPy motifs.
