Guided by molecular networking,nine novel curvularin derivatives(1-9)and 16 known analogs(10-25)were isolated from the hydrothermal vent sediment fungus Penicillium sp.HL-50.Notably,compounds 5-7 represented a hybrid ...Guided by molecular networking,nine novel curvularin derivatives(1-9)and 16 known analogs(10-25)were isolated from the hydrothermal vent sediment fungus Penicillium sp.HL-50.Notably,compounds 5-7 represented a hybrid of curvularin and purine.The structures and absolute configurations of compounds 1-9 were elucidated via nuclear magnetic resonance(NMR)spectroscopy,X-ray diffraction,electronic circular dichroism(ECD)calculations,^(13)C NMR calculation,modified Mosher's method,and chemical derivatization.Investigation of anti-inflammatory activities revealed that compounds 7-9,11,12,14,15,and 18 exhibited significant suppressive effects against lipopolysaccharide(LPS)-induced nitric oxide(NO)production in murine macrophage RAW264.7 cells,with IC_(50)values ranging from 0.44 to 4.40μmol·L^(-1).Furthermore,these bioactive compounds were found to suppress the expression of inflammation-related proteins,including inducible NO synthase(i NOS),cyclooxygenase-2(COX-2),NLR family pyrin domain-containing protein 3(NLRP3),and nuclear factor kappa-B(NF-κB).Additional studies demonstrated that the novel compound 7 possessed potent antiinflammatory activity by inhibiting the transcription of inflammation-related genes,downregulating the expression of inflammation-related proteins,and inhibiting the release of inflammatory cytokines,indicating its potential application in the treatment of inflammatory diseases.展开更多
Chemical graph theory is a branch of mathematics which combines graph theory and chemistry.Chemical reaction network theory is a territory of applied mathematics that endeavors to display the conduct of genuine compou...Chemical graph theory is a branch of mathematics which combines graph theory and chemistry.Chemical reaction network theory is a territory of applied mathematics that endeavors to display the conduct of genuine compound frameworks.It pulled the research community due to its applications in theoretical and organic chemistry since 1960.Additionally,it also increases the interest the mathematicians due to the interesting mathematical structures and problems are involved.The structure of an interconnection network can be represented by a graph.In the network,vertices represent the processor nodes and edges represent the links between the processor nodes.Graph invariants play a vital feature in graph theory and distinguish the structural properties of graphs and networks.In this paper,we determined the newly introduced topological indices namely,first ve-degree Zagreb?index,first ve-degree Zagreb?index,second ve-degree Zagreb index,ve-degree Randic index,ve-degree atom-bond connectivity index,ve-degree geometric-arithmetic index,ve-degree harmonic index and ve-degree sum-connectivity index for honey comb derived network.In the analysis of the quantitative structure property relationships(QSPRs)and the quantitative structure-activity relationships(QSARs),graph invariants are important tools to approximate and predicate the properties of the biological and chemical compounds.Also,we give the numerical and graphical representation of our outcomes.展开更多
Given a protein sequence, how can we identify whether it is a metalloprotein or not? If it is, which main functional class and subclasses it belongs to? This is an important biological question because they are closel...Given a protein sequence, how can we identify whether it is a metalloprotein or not? If it is, which main functional class and subclasses it belongs to? This is an important biological question because they are closely related to the biological function of an uncharacterized protein. Particularly, with the avalanche of protein sequences generated in the post genomic era and since conventional techniques are time consuming and expensive, it is highly desirable to develop an automated method by which one can get a fast and accurate answer to these questions. Here, a top-down predictor, called MetalloPred, is developed which consists of 3 level of hierarchical classification using cascade of neural networks from sequence derived features. The 1st layer of the prediction engine is for identifying a query protein as metalloprotein or not;the 2nd layer for the main functional class;and the 3rd layer for the sub-functional class. The overall success rates for all the three layers are higher than 60% that were obtained through rigorous cross-validation tests on the very stringent benchmark datasets in which none of the proteins has 30% sequence identity with any other in the same class or subclass. MetalloPred achieved good prediction accuracies and could nicely complement experimental approaches for identification of metal binding proteins. MetalloPred is freely available to be used in-house as a standalone and is accessible at http://www.juit.ac.in/assets/Metallopred/.展开更多
In this study,artificial neural networks(ANNs)were implemented to determine design parameters for an impressed current cathodic protection(ICCP)prototype.An ASTM A36 steel plate was tested in 3.5%NaCl solution,seawate...In this study,artificial neural networks(ANNs)were implemented to determine design parameters for an impressed current cathodic protection(ICCP)prototype.An ASTM A36 steel plate was tested in 3.5%NaCl solution,seawater,and NS4 using electrochemical impedance spectroscopy(EIS)to monitor the evolution of the substrate surface,which affects the current required to reach the protection potential(Eprot).Experimental data were collected as training datasets and analyzed using statistical methods,including box plots and correlation matrices.Subsequently,ANNs were applied to predict the current demand at different exposure times,enabling the estimation of electrochemical parameters(limiting voltage values)that can be used to optimize a self-regulating ICCP system.The obtained electrochemical parameters were then used,through Particle Swarm Optimization(PSO),to fine-tune an ANN-based proportional-integral-derivative(PID)controller for the ICCP system.展开更多
Based on the nonlinear error equation of deformation network monitoring, the mathematical model of nonlinear dynamic optimal design of class two was put forward for the deformation network monitoring, in which the tar...Based on the nonlinear error equation of deformation network monitoring, the mathematical model of nonlinear dynamic optimal design of class two was put forward for the deformation network monitoring, in which the target function is the accuracy criterion and the constraint conditions are the network’s sensitivity, reliability and observing cost. Meanwhile a new non derivative solution to the nonlinear dynamic optimal design of class two was also put forward. The solving model uses the difference to stand for the first derivative of functions and solves the revised feasible direction to get the optimal solution to unknown parameters. It can not only make the solution to converge on the minimum point of the constraint problem, but decrease the calculating load.展开更多
With the dense deployment of femtocells in enterprise femtocell network and the small coverage of femtocells, handover in enterprise femtocell network will be frequent. The general handover key derivation method which...With the dense deployment of femtocells in enterprise femtocell network and the small coverage of femtocells, handover in enterprise femtocell network will be frequent. The general handover key derivation method which is used in handover procedures in LTE is not suitable for handover in this scenario because of its long time cost and the weak security. To solve this problem, this paper has proposed a new local gateway assisted handover key derivation schema in enterprise femtocell network. It can meet the fast derivation and good forward/backward key secrecy requirement of handover key derivation in enterprise femtocell network. The simulation result has verified that the proposed handover key derivation schema works better than the existing method.展开更多
This article aims to address the global exponential synchronization problem for fractional-order complex dynamical networks(FCDNs)with derivative couplings and impulse effects via designing an appropriate feedback con...This article aims to address the global exponential synchronization problem for fractional-order complex dynamical networks(FCDNs)with derivative couplings and impulse effects via designing an appropriate feedback control based on discrete time state observations.In contrast to the existing works on integer-order derivative couplings,fractional derivative couplings are introduced into FCDNs.First,a useful lemma with respect to the relationship between the discrete time observations term and a continuous term is developed.Second,by utilizing an inequality technique and auxiliary functions,the rigorous global exponential synchronization analysis is given and synchronization criterions are achieved in terms of linear matrix inequalities(LMIs).Finally,two examples are provided to illustrate the correctness of the obtained results.展开更多
One of the evolving hand biometric features considered so far is finger knuckle printing,because of its ability towards unique identification of individuals.Despite many attempts have been made in this area of researc...One of the evolving hand biometric features considered so far is finger knuckle printing,because of its ability towards unique identification of individuals.Despite many attempts have been made in this area of research,the accuracy of the recognition model remains a major issue.To overcome this problem,a novel biometric-based method,named fingerknuckle-print(FKP),has been developed for individual verification.The proposed system carries key steps such as preprocessing,segmentation,feature extraction and classification.Initially input FKP image is fed into the preprocessing stage where colour images are converted to gray scale image for augmenting the system performance.Afterwards,segmentation process is carried out with the help of CROI(Circular Region of Interest)and Morphological operation.Then,feature extraction stage is carried out using Gabor-Derivative line approach for extracting intrinsic features.Finally,DCNN(Deep Convolutional Neural Network)is trained for the processed knuckle images to recognize imposter and genuine individuals.Extensive experiments on standard FKP database demonstrates that the proposed method attains considerable improvement compared with state-of-the-art methods.The overall accuracy attained for the proposed methodology is 95.6%which is achieved better than the existing techniques.展开更多
To improve the generalization performance and prediction accuracy of the stochastic configuration network(SCN)model,a novel SCN modeling method is proposed.First,the first-and second-order directional derivatives of t...To improve the generalization performance and prediction accuracy of the stochastic configuration network(SCN)model,a novel SCN modeling method is proposed.First,the first-and second-order directional derivatives of the hidden layer output matrix are calculated.The key factors extracted from the directional derivatives are linearly added to the original hidden layer output matrix to formulate a new hidden layer output matrix.Second,a spatial angle adaptive supervisory mechanism is established to improve the quality of the parameter configuration of the hidden layer nodes.The experimental results show that the proposed method improves the generalization performance and prediction accuracy.This work is a beneficial exploration of the standard SCN algorithm.展开更多
Dear Editor,This letter studies the stabilization control issue of cyber-physical systems with time-varying delays and aperiodic denial-of-service(DoS)attacks.To address the calculation overload issue caused by networ...Dear Editor,This letter studies the stabilization control issue of cyber-physical systems with time-varying delays and aperiodic denial-of-service(DoS)attacks.To address the calculation overload issue caused by networked predictive control(NPC)approach,an event-based NPC method is proposed.Within the proposed method,the negative effects of time-varying delays and DoS attacks on system performance are compensated.Then,sufficient and necessary conditions are derived to ensure the stability of the closed-loop system.In the end,simulation results are provided to demonstrate the validity of presented method.展开更多
Endochondral ossification is a physiological process involving a sequential formation of cartilage and bone tissues.Classically,cartilage and bone formation have been considered independent processes at cellular level...Endochondral ossification is a physiological process involving a sequential formation of cartilage and bone tissues.Classically,cartilage and bone formation have been considered independent processes at cellular level.However,the recently described multiple cell differentiation dynamics suggest that some bone cells are indeed the progeny of cartilage cells,or chondrocyte-derived osteoblasts.We hypothesized that the cartilage-to-bone phenotype transition is triggered by specific molecular events.First,the process was assessed in mouse bone tissue,and then,it was mimicked using in vivo cell implantation and in vitro serial differentiation protocols.Data indicates that cartilage cells transition to bone cell phenotype during postnatal physiological bone formation.This process can be reproduced using cartilage precursor cells coupled to specific implantation procedures or differentiation protocols.Gene expression profiling reveals that NOTCH,BMP and MAPK signaling pathways are relevant at the phenotype-switch,while the transcription factors Mesp1,Alx1,Grhl3 and Hmx3 are the feasible driver genes for chondrocyte-derived osteoblasts formation.Altogether,this report shows that endochondral ossification can be modeled using primary cell cultures and data indicate that this process is regulated by specific molecular events,previously described at skeleton morphogenesis during embryo development,and from now on also linkable to postnatal bone development and regeneration processes.展开更多
In order to make the static state feedback nonlinear decoupling control law for a kind of missile to be easy for implementation in practice, an improvement is discussed. The improvement method is to introduce a BP neu...In order to make the static state feedback nonlinear decoupling control law for a kind of missile to be easy for implementation in practice, an improvement is discussed. The improvement method is to introduce a BP neural network to approximate the decoupling control laws which are designed for different aerodynamic characteristic points, so a new decoupling control law based on BP neural network is produced after the network training. The simulation results on an example illustrate the approach obtained feasible and effective.展开更多
The (integer order) Halanay inequality with distributed delays is extended to the fractional order case. It is proved that solutions decay to zero as a Mittag-Leffler function as time goes to infinity provided that th...The (integer order) Halanay inequality with distributed delays is extended to the fractional order case. It is proved that solutions decay to zero as a Mittag-Leffler function as time goes to infinity provided that the delay feedback are bounded by similar functions.An application to a problem arising in neural network theory is provided showing that the equilibrium is Mittag-Leffler stable.展开更多
The rapid growth of 3G/4G enabled devices such as smartphones and tablets in large numbers has created increased demand for mobile data services. Wi-Fi offloading helps satisfy the requirements of data-rich applicatio...The rapid growth of 3G/4G enabled devices such as smartphones and tablets in large numbers has created increased demand for mobile data services. Wi-Fi offloading helps satisfy the requirements of data-rich applications and terminals with improved multi- media. Wi-Fi is an essential approach to alleviating mobile data traffic load on a cellular network because it provides extra capacity and improves overall performance. In this paper, we propose an integrated LTE/Wi-Fi architecture with software-defined networking （SDN） abstraction in mobile baekhaul and enhanced components that facilitate the move towards next-generation 5G mo- bile networks. Our proposed architecture enables programmable offloading policies that take into account real-time network conditions as well as the status of devices and applications. This mechanism improves overall network performance by deriving real- time policies and steering traffic between cellular and Wi-Fi networks more efficiently.展开更多
Rosa roxburghii fruit is rich in flavonoids, but little is known about their biosynthetic pathways. In this study, we employed transcriptomics and metabolomics to study changes related to the flavonoids at five differ...Rosa roxburghii fruit is rich in flavonoids, but little is known about their biosynthetic pathways. In this study, we employed transcriptomics and metabolomics to study changes related to the flavonoids at five different stages of R. roxburghii fruit development. Flavonoids and the genes related to their biosynthesis were found to undergo significant changes in abundance across different developmental stages, and numerous quercetin derivatives were identified. We found three gene expression modules that were significantly associated with the abundances of the different flavonoids in R. roxburghii and identified three structural UDP-glycosyltransferase genes directly involved in the synthesis of quercetin derivatives within these modules. In addition, we found that RrBEH4, RrLBD1 and RrPIF8could significantly increase the expression of downstream quercetin derivative biosynthesis genes. Taken together,these results provide new insights into the metabolism of flavonoids and the accumulation of quercetin derivatives in R. roxburghii.展开更多
To evaluate the performance of real time kinematic (RTK) network algorithms without applying actual measurements, a new method called geometric precision evaluation methodology (GPEM) based on covariance analysis was ...To evaluate the performance of real time kinematic (RTK) network algorithms without applying actual measurements, a new method called geometric precision evaluation methodology (GPEM) based on covariance analysis was presented. Three types of multiple reference station interpolation algorithms, including partial derivation algorithm (PDA), linear interpolation algorithms (LIA) and least squares condition (LSC) were discussed and analyzed. The geometric dilution of precision (GDOP) was defined to describe the influence of the network geometry on the interpolation precision, and the different GDOP expressions of above-mentioned algorithms were deduced. In order to compare geometric precision characteristics among different multiple reference station network algorithms, a simulation was conducted, and the GDOP contours of these algorithms were enumerated. Finally, to confirm the validation of GPEM, an experiment was conducted using data from Unite State Continuously Operating Reference Stations (US-CORS), and the precision performances were calculated according to the real test data and GPEM, respectively. The results show that GPEM generates very accurate estimation of the performance compared to the real data test.展开更多
基金funded by the National Key Research and Development Program of China(No.2022YFC2804101)the Guangdong Provincial Key R&D Program(No.2023B1111050011)+2 种基金the Guangdong Basic and Applied Basic Research Foundation(No.2023A1515010432)the Guangzhou Basic and Applied Basic Research Foundation(No.202201010305)the High-Level Talents Special Program of Zhejiang(No.2022R52036)。
文摘Guided by molecular networking,nine novel curvularin derivatives(1-9)and 16 known analogs(10-25)were isolated from the hydrothermal vent sediment fungus Penicillium sp.HL-50.Notably,compounds 5-7 represented a hybrid of curvularin and purine.The structures and absolute configurations of compounds 1-9 were elucidated via nuclear magnetic resonance(NMR)spectroscopy,X-ray diffraction,electronic circular dichroism(ECD)calculations,^(13)C NMR calculation,modified Mosher's method,and chemical derivatization.Investigation of anti-inflammatory activities revealed that compounds 7-9,11,12,14,15,and 18 exhibited significant suppressive effects against lipopolysaccharide(LPS)-induced nitric oxide(NO)production in murine macrophage RAW264.7 cells,with IC_(50)values ranging from 0.44 to 4.40μmol·L^(-1).Furthermore,these bioactive compounds were found to suppress the expression of inflammation-related proteins,including inducible NO synthase(i NOS),cyclooxygenase-2(COX-2),NLR family pyrin domain-containing protein 3(NLRP3),and nuclear factor kappa-B(NF-κB).Additional studies demonstrated that the novel compound 7 possessed potent antiinflammatory activity by inhibiting the transcription of inflammation-related genes,downregulating the expression of inflammation-related proteins,and inhibiting the release of inflammatory cytokines,indicating its potential application in the treatment of inflammatory diseases.
文摘Chemical graph theory is a branch of mathematics which combines graph theory and chemistry.Chemical reaction network theory is a territory of applied mathematics that endeavors to display the conduct of genuine compound frameworks.It pulled the research community due to its applications in theoretical and organic chemistry since 1960.Additionally,it also increases the interest the mathematicians due to the interesting mathematical structures and problems are involved.The structure of an interconnection network can be represented by a graph.In the network,vertices represent the processor nodes and edges represent the links between the processor nodes.Graph invariants play a vital feature in graph theory and distinguish the structural properties of graphs and networks.In this paper,we determined the newly introduced topological indices namely,first ve-degree Zagreb?index,first ve-degree Zagreb?index,second ve-degree Zagreb index,ve-degree Randic index,ve-degree atom-bond connectivity index,ve-degree geometric-arithmetic index,ve-degree harmonic index and ve-degree sum-connectivity index for honey comb derived network.In the analysis of the quantitative structure property relationships(QSPRs)and the quantitative structure-activity relationships(QSARs),graph invariants are important tools to approximate and predicate the properties of the biological and chemical compounds.Also,we give the numerical and graphical representation of our outcomes.
文摘Given a protein sequence, how can we identify whether it is a metalloprotein or not? If it is, which main functional class and subclasses it belongs to? This is an important biological question because they are closely related to the biological function of an uncharacterized protein. Particularly, with the avalanche of protein sequences generated in the post genomic era and since conventional techniques are time consuming and expensive, it is highly desirable to develop an automated method by which one can get a fast and accurate answer to these questions. Here, a top-down predictor, called MetalloPred, is developed which consists of 3 level of hierarchical classification using cascade of neural networks from sequence derived features. The 1st layer of the prediction engine is for identifying a query protein as metalloprotein or not;the 2nd layer for the main functional class;and the 3rd layer for the sub-functional class. The overall success rates for all the three layers are higher than 60% that were obtained through rigorous cross-validation tests on the very stringent benchmark datasets in which none of the proteins has 30% sequence identity with any other in the same class or subclass. MetalloPred achieved good prediction accuracies and could nicely complement experimental approaches for identification of metal binding proteins. MetalloPred is freely available to be used in-house as a standalone and is accessible at http://www.juit.ac.in/assets/Metallopred/.
文摘In this study,artificial neural networks(ANNs)were implemented to determine design parameters for an impressed current cathodic protection(ICCP)prototype.An ASTM A36 steel plate was tested in 3.5%NaCl solution,seawater,and NS4 using electrochemical impedance spectroscopy(EIS)to monitor the evolution of the substrate surface,which affects the current required to reach the protection potential(Eprot).Experimental data were collected as training datasets and analyzed using statistical methods,including box plots and correlation matrices.Subsequently,ANNs were applied to predict the current demand at different exposure times,enabling the estimation of electrochemical parameters(limiting voltage values)that can be used to optimize a self-regulating ICCP system.The obtained electrochemical parameters were then used,through Particle Swarm Optimization(PSO),to fine-tune an ANN-based proportional-integral-derivative(PID)controller for the ICCP system.
文摘Based on the nonlinear error equation of deformation network monitoring, the mathematical model of nonlinear dynamic optimal design of class two was put forward for the deformation network monitoring, in which the target function is the accuracy criterion and the constraint conditions are the network’s sensitivity, reliability and observing cost. Meanwhile a new non derivative solution to the nonlinear dynamic optimal design of class two was also put forward. The solving model uses the difference to stand for the first derivative of functions and solves the revised feasible direction to get the optimal solution to unknown parameters. It can not only make the solution to converge on the minimum point of the constraint problem, but decrease the calculating load.
文摘With the dense deployment of femtocells in enterprise femtocell network and the small coverage of femtocells, handover in enterprise femtocell network will be frequent. The general handover key derivation method which is used in handover procedures in LTE is not suitable for handover in this scenario because of its long time cost and the weak security. To solve this problem, this paper has proposed a new local gateway assisted handover key derivation schema in enterprise femtocell network. It can meet the fast derivation and good forward/backward key secrecy requirement of handover key derivation in enterprise femtocell network. The simulation result has verified that the proposed handover key derivation schema works better than the existing method.
基金supported by Key Projectof Natural Science Foundation of China(61833005)the Natural Science Foundation of Hebei Province of China(A2018203288)。
文摘This article aims to address the global exponential synchronization problem for fractional-order complex dynamical networks(FCDNs)with derivative couplings and impulse effects via designing an appropriate feedback control based on discrete time state observations.In contrast to the existing works on integer-order derivative couplings,fractional derivative couplings are introduced into FCDNs.First,a useful lemma with respect to the relationship between the discrete time observations term and a continuous term is developed.Second,by utilizing an inequality technique and auxiliary functions,the rigorous global exponential synchronization analysis is given and synchronization criterions are achieved in terms of linear matrix inequalities(LMIs).Finally,two examples are provided to illustrate the correctness of the obtained results.
基金RUSA PHASE 2.0, University of Alagappa, Karaikudi has supported this research projectThe UGC-NFSC fellowship has helped support this research
文摘One of the evolving hand biometric features considered so far is finger knuckle printing,because of its ability towards unique identification of individuals.Despite many attempts have been made in this area of research,the accuracy of the recognition model remains a major issue.To overcome this problem,a novel biometric-based method,named fingerknuckle-print(FKP),has been developed for individual verification.The proposed system carries key steps such as preprocessing,segmentation,feature extraction and classification.Initially input FKP image is fed into the preprocessing stage where colour images are converted to gray scale image for augmenting the system performance.Afterwards,segmentation process is carried out with the help of CROI(Circular Region of Interest)and Morphological operation.Then,feature extraction stage is carried out using Gabor-Derivative line approach for extracting intrinsic features.Finally,DCNN(Deep Convolutional Neural Network)is trained for the processed knuckle images to recognize imposter and genuine individuals.Extensive experiments on standard FKP database demonstrates that the proposed method attains considerable improvement compared with state-of-the-art methods.The overall accuracy attained for the proposed methodology is 95.6%which is achieved better than the existing techniques.
基金supported by the National Natural Science Foundation of China(62373017).
文摘To improve the generalization performance and prediction accuracy of the stochastic configuration network(SCN)model,a novel SCN modeling method is proposed.First,the first-and second-order directional derivatives of the hidden layer output matrix are calculated.The key factors extracted from the directional derivatives are linearly added to the original hidden layer output matrix to formulate a new hidden layer output matrix.Second,a spatial angle adaptive supervisory mechanism is established to improve the quality of the parameter configuration of the hidden layer nodes.The experimental results show that the proposed method improves the generalization performance and prediction accuracy.This work is a beneficial exploration of the standard SCN algorithm.
基金supported by the National Natural Science Foundation of China(61433003,60904003,11602019).
文摘Dear Editor,This letter studies the stabilization control issue of cyber-physical systems with time-varying delays and aperiodic denial-of-service(DoS)attacks.To address the calculation overload issue caused by networked predictive control(NPC)approach,an event-based NPC method is proposed.Within the proposed method,the negative effects of time-varying delays and DoS attacks on system performance are compensated.Then,sufficient and necessary conditions are derived to ensure the stability of the closed-loop system.In the end,simulation results are provided to demonstrate the validity of presented method.
基金funded by Grants PID2021-127191OB-I00,RTI2018-101708-A-I00,PRE2018-084542 and PRE2022-102680 funded by MCIN/AEI/10.13039/501100011033 and by“ERDF A way of making Europe”Grant RYC2018-025502-I is funded by MCIN/AEI/10.13039/501100011033 and by“ESF Investing in your future”+1 种基金Grant MDM-20170720 Maria de Maeztu Units of Excellence Program funded by the Spanish State Research Agencysupported by Instituto de Salud CarlosⅢ,Infrastructure of Precision Medicine associated with Science and Technology(IMPaCT)of the Strategic Action in Health(iDATA-MP)。
文摘Endochondral ossification is a physiological process involving a sequential formation of cartilage and bone tissues.Classically,cartilage and bone formation have been considered independent processes at cellular level.However,the recently described multiple cell differentiation dynamics suggest that some bone cells are indeed the progeny of cartilage cells,or chondrocyte-derived osteoblasts.We hypothesized that the cartilage-to-bone phenotype transition is triggered by specific molecular events.First,the process was assessed in mouse bone tissue,and then,it was mimicked using in vivo cell implantation and in vitro serial differentiation protocols.Data indicates that cartilage cells transition to bone cell phenotype during postnatal physiological bone formation.This process can be reproduced using cartilage precursor cells coupled to specific implantation procedures or differentiation protocols.Gene expression profiling reveals that NOTCH,BMP and MAPK signaling pathways are relevant at the phenotype-switch,while the transcription factors Mesp1,Alx1,Grhl3 and Hmx3 are the feasible driver genes for chondrocyte-derived osteoblasts formation.Altogether,this report shows that endochondral ossification can be modeled using primary cell cultures and data indicate that this process is regulated by specific molecular events,previously described at skeleton morphogenesis during embryo development,and from now on also linkable to postnatal bone development and regeneration processes.
文摘In order to make the static state feedback nonlinear decoupling control law for a kind of missile to be easy for implementation in practice, an improvement is discussed. The improvement method is to introduce a BP neural network to approximate the decoupling control laws which are designed for different aerodynamic characteristic points, so a new decoupling control law based on BP neural network is produced after the network training. The simulation results on an example illustrate the approach obtained feasible and effective.
基金Supported by King Abdulaziz City of King Abdulaziz City of Science and Technology (KACST) under the National Science,Technology and Innovation Plan(NSTIP),Project No.15-OIL4884-0124
文摘The (integer order) Halanay inequality with distributed delays is extended to the fractional order case. It is proved that solutions decay to zero as a Mittag-Leffler function as time goes to infinity provided that the delay feedback are bounded by similar functions.An application to a problem arising in neural network theory is provided showing that the equilibrium is Mittag-Leffler stable.
文摘The rapid growth of 3G/4G enabled devices such as smartphones and tablets in large numbers has created increased demand for mobile data services. Wi-Fi offloading helps satisfy the requirements of data-rich applications and terminals with improved multi- media. Wi-Fi is an essential approach to alleviating mobile data traffic load on a cellular network because it provides extra capacity and improves overall performance. In this paper, we propose an integrated LTE/Wi-Fi architecture with software-defined networking （SDN） abstraction in mobile baekhaul and enhanced components that facilitate the move towards next-generation 5G mo- bile networks. Our proposed architecture enables programmable offloading policies that take into account real-time network conditions as well as the status of devices and applications. This mechanism improves overall network performance by deriving real- time policies and steering traffic between cellular and Wi-Fi networks more efficiently.
基金supported in part by the Priority Academic Program Development of Jiangsu Higher Education Institutions and the State Key Laboratory of Crop Genetics and Germplasm Enhancement,China(ZW201813)。
文摘Rosa roxburghii fruit is rich in flavonoids, but little is known about their biosynthetic pathways. In this study, we employed transcriptomics and metabolomics to study changes related to the flavonoids at five different stages of R. roxburghii fruit development. Flavonoids and the genes related to their biosynthesis were found to undergo significant changes in abundance across different developmental stages, and numerous quercetin derivatives were identified. We found three gene expression modules that were significantly associated with the abundances of the different flavonoids in R. roxburghii and identified three structural UDP-glycosyltransferase genes directly involved in the synthesis of quercetin derivatives within these modules. In addition, we found that RrBEH4, RrLBD1 and RrPIF8could significantly increase the expression of downstream quercetin derivative biosynthesis genes. Taken together,these results provide new insights into the metabolism of flavonoids and the accumulation of quercetin derivatives in R. roxburghii.
基金Project(61273055) supported by the National Natural Science Foundation of ChinaProject(CX2010B012) supported by Hunan Provincial Innovation Foundation for Postgraduate Students, ChinaProject(B100302) supported by Innovation Foundation for Postgraduate Students of National University of Defense Technology, China
文摘To evaluate the performance of real time kinematic (RTK) network algorithms without applying actual measurements, a new method called geometric precision evaluation methodology (GPEM) based on covariance analysis was presented. Three types of multiple reference station interpolation algorithms, including partial derivation algorithm (PDA), linear interpolation algorithms (LIA) and least squares condition (LSC) were discussed and analyzed. The geometric dilution of precision (GDOP) was defined to describe the influence of the network geometry on the interpolation precision, and the different GDOP expressions of above-mentioned algorithms were deduced. In order to compare geometric precision characteristics among different multiple reference station network algorithms, a simulation was conducted, and the GDOP contours of these algorithms were enumerated. Finally, to confirm the validation of GPEM, an experiment was conducted using data from Unite State Continuously Operating Reference Stations (US-CORS), and the precision performances were calculated according to the real test data and GPEM, respectively. The results show that GPEM generates very accurate estimation of the performance compared to the real data test.
