Background:The heartwood(HW)proportion in the trunk of mature trees is an important characteristic not only for wood quality but also for assessing the role of forests in carbon sequestration.We have for the first tim...Background:The heartwood(HW)proportion in the trunk of mature trees is an important characteristic not only for wood quality but also for assessing the role of forests in carbon sequestration.We have for the first time studied the proportion of HW in the trunk and the distribution of carbon and extractives in sapwood(SW)and HW of 70–80 year old Pinus sylvestris L.trees under different growing conditions in the pine forests of North-West Russia.Method:We have examined the influence of conditions and tree position in stand(dominant,intermediate and suppressed trees)in the ecological series:blueberry pine forest(Blu)–lingonberry pine forest(Lin)–lichen pine forest(Lic).We have analyzed the influence of climate conditions in the biogeographical series of Lin:the middle taiga subzone–the northern taiga subzone–the transition area of the northern taiga subzone and tundra.Results:We found that the carbon concentration in HW was 1.6%–3.4%higher than in SW,and the difference depended on growing conditions.Carbon concentration in HW increased with a decrease in stand productivity(Blu-Lin-Lic).In medium-productive stands,the carbon concentration in SW was higher in intermediate and supressed trees compared to dominant trees.In the series from south to north,carbon concentration in HW increased by up to 2%,while in SW,it rose by 2.7%–3.8%.Conclusions:Our results once again emphasized the need for an empirical assessment of the accurate carbon content in aboveground wood biomass,including various forest growing conditions,to better understand the role of boreal forests in carbon storage.展开更多
This paper investigates the reliability of internal marine combustion engines using an integrated approach that combines Fault Tree Analysis(FTA)and Bayesian Networks(BN).FTA provides a structured,top-down method for ...This paper investigates the reliability of internal marine combustion engines using an integrated approach that combines Fault Tree Analysis(FTA)and Bayesian Networks(BN).FTA provides a structured,top-down method for identifying critical failure modes and their root causes,while BN introduces flexibility in probabilistic reasoning,enabling dynamic updates based on new evidence.This dual methodology overcomes the limitations of static FTA models,offering a comprehensive framework for system reliability analysis.Critical failures,including External Leakage(ELU),Failure to Start(FTS),and Overheating(OHE),were identified as key risks.By incorporating redundancy into high-risk components such as pumps and batteries,the likelihood of these failures was significantly reduced.For instance,redundant pumps reduced the probability of ELU by 31.88%,while additional batteries decreased the occurrence of FTS by 36.45%.The results underscore the practical benefits of combining FTA and BN for enhancing system reliability,particularly in maritime applications where operational safety and efficiency are critical.This research provides valuable insights for maintenance planning and highlights the importance of redundancy in critical systems,especially as the industry transitions toward more autonomous vessels.展开更多
In the context of modern software development characterized by increasing complexity and compressed development cycles,traditional static vulnerability detection methods face prominent challenges including high false ...In the context of modern software development characterized by increasing complexity and compressed development cycles,traditional static vulnerability detection methods face prominent challenges including high false positive rates and missed detections of complex logic due to their over-reliance on rule templates.This paper proposes a Syntax-Aware Hierarchical Attention Network(SAHAN)model,which achieves high-precision vulnerability detection through grammar-rule-driven multi-granularity code slicing and hierarchical semantic fusion mechanisms.The SAHAN model first generates Syntax Independent Units(SIUs),which slices the code based on Abstract Syntax Tree(AST)and predefined grammar rules,retaining vulnerability-sensitive contexts.Following this,through a hierarchical attention mechanism,the local syntax-aware layer encodes fine-grained patterns within SIUs,while the global semantic correlation layer captures vulnerability chains across SIUs,achieving synergistic modeling of syntax and semantics.Experiments show that on benchmark datasets like QEMU,SAHAN significantly improves detection performance by 4.8%to 13.1%on average compared to baseline models such as Devign and VulDeePecker.展开更多
L（ s, t）-labeling is a variation of graph coloring which is motivated by a special kind of the channel assignment problem. Let s and t be any two nonnegative integers. An L （s, t）-labeling of a graph G is an assig...L（ s, t）-labeling is a variation of graph coloring which is motivated by a special kind of the channel assignment problem. Let s and t be any two nonnegative integers. An L （s, t）-labeling of a graph G is an assignment of integers to the vertices of G such that adjacent vertices receive integers which differ by at least s, and vertices that are at distance of two receive integers which differ by at least t. Given an L（s, t） -labeling f of a graph G, the L（s, t） edge span of f, βst （ G, f） = max { ｜f（u） -f（v）｜： （ u, v） ∈ E（G） } is defined. The L（ s, t） edge span of G, βst（G）, is minβst（G,f）, where the minimum runs over all L（s, t）-labelings f of G. Let T be any tree with a maximum degree of △≥2. It is proved that if 2s≥t≥0, then βst（T） =（ [△/2 ] - 1）t ＋s; if 0≤2s 〈 t and △ is even, then βst（T） = [ （△ - 1） t/2 ] ; and if 0 ≤2s 〈 t and △ is odd, then βst（T） = （△ - 1） t/2 ＋ s. Thus, the L（s, t） edge spans of the Cartesian product of two paths and of the square lattice are completely determined.展开更多
Electrical pollution is a worldwide concern,because it is potentially harmful to human health.Trees not only play a significant role in moderating the climate,but also can be used as shields against electrical polluti...Electrical pollution is a worldwide concern,because it is potentially harmful to human health.Trees not only play a significant role in moderating the climate,but also can be used as shields against electrical pollution.Shielding effects on the electric field strength under transmission lines by two tree species,Populus alba and Larix gmelinii,were examined in this study.The electrical resistivity at different heights of trees was measured using a PiCUS sonic tomograph,which can image the electrical impedance for trees.The electric field strength around the trees was measured with an elf field strength measurement system,HI-3604,and combined with tree resistivity to develop a model for calculating the electric field intensity around trees using the finite element method.In addition,the feasibility of the finite element method was confirmed by comparing the calculated results and experimental data.The results showed that the trees did reduce the electric field strength.The electric field intensity was reduced by 95.6%,and P.alba was better than L.gmelinii at shielding.展开更多
The learning Bayesian network （BN） structure from data is an NP-hard problem and still one of the most exciting chal- lenges in the machine learning. In this work, a novel algorithm is presented which combines ideas...The learning Bayesian network （BN） structure from data is an NP-hard problem and still one of the most exciting chal- lenges in the machine learning. In this work, a novel algorithm is presented which combines ideas from local learning, constraint- based, and search-and-score techniques in a principled and ef- fective way. It first reconstructs the junction tree of a BN and then performs a K2-scoring greedy search to orientate the local edges in the cliques of junction tree. Theoretical and experimental results show the proposed algorithm is capable of handling networks with a large number of variables. Its comparison with the well-known K2 algorithm is also presented.展开更多
In this paper a new modeling framework for the dependability analysis of complex systems is presented and related to dynamic fault trees (DFTs). The methodology is based on a modular approach: two separate models are ...In this paper a new modeling framework for the dependability analysis of complex systems is presented and related to dynamic fault trees (DFTs). The methodology is based on a modular approach: two separate models are used to handle, the fault logic and the stochastic dependencies of the system. Thus, the fault schema, free of any dependency logic, can be easily evaluated, while the dependency schema allows the modeler to design new kind of non-trivial dependencies not easily caught by the traditional holistic methodologies. Moreover, the use of a dependency schema allows building a pure behavioral model that can be used for various kinds of dependability studies. In the paper is shown how to build and integrate the two modular models and convert them in a Stochastic Activity Network. Furthermore, based on the construction of the schema that embeds the stochastic dependencies, the procedure to convert DFTs into static fault trees is shown, allowing the resolution of DFTs in a very efficient way.展开更多
Several data mining techniques such as Hidden Markov Model (HMM), artificial neural network, statistical techniques and expert systems are used to model network packets in the field of intrusion detection. In this pap...Several data mining techniques such as Hidden Markov Model (HMM), artificial neural network, statistical techniques and expert systems are used to model network packets in the field of intrusion detection. In this paper a novel intrusion detection mode based on understandable Neural Network Tree (NNTree) is pre-sented. NNTree is a modular neural network with the overall structure being a Decision Tree (DT), and each non-terminal node being an Expert Neural Network (ENN). One crucial advantage of using NNTrees is that they keep the non-symbolic model ENN’s capability of learning in changing environments. Another potential advantage of using NNTrees is that they are actually “gray boxes” as they can be interpreted easily if the num-ber of inputs for each ENN is limited. We showed through experiments that the trained NNTree achieved a simple ENN at each non-terminal node as well as a satisfying recognition rate of the network packets dataset. We also compared the performance with that of a three-layer backpropagation neural network. Experimental results indicated that the NNTree based intrusion detection model achieved better performance than the neural network based intrusion detection model.展开更多
Based on a fuzzy neural network, the letter presents an approach for the induction of decision trees. The approach makes use of the weights of fuzzy mappings in the fuzzy neural network which has been trained. It can ...Based on a fuzzy neural network, the letter presents an approach for the induction of decision trees. The approach makes use of the weights of fuzzy mappings in the fuzzy neural network which has been trained. It can realize the optimization of fuzzy decision trees by branch cutting, and improve the ratio of correctness and efficiency of the induction of decision trees.展开更多
Agriculture and farming are mainly dependent on weather especially in Malaysia as it received heavy rainfall throughout the years. An efficient crop or tree management system with a weather forecast needed for suitabl...Agriculture and farming are mainly dependent on weather especially in Malaysia as it received heavy rainfall throughout the years. An efficient crop or tree management system with a weather forecast needed for suitable planning of farming operation. Radial Basis Function Neural Network (RBFNN) algorithm was used in this study to predict rainfall and the main focus of this study is to analyze the factor that affect</span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">s</span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;"> the performance of neural model. This study found that the model works better the more hidden nodes and the optimum learning rate is 0.01 with the RMSE 49% and the percentage accuracy is 57%. Besides that, it is found that the meteorology data also affect the model performance. Future research can be conducted to improve the rainfall forecast of this study and improv</span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">e</span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;"> the tree management system.展开更多
Understanding an underlying structure for phylogenetic trees is very important as it informs on the methods that should be employed during phylogenetic inference. The methods used under a structured population differ ...Understanding an underlying structure for phylogenetic trees is very important as it informs on the methods that should be employed during phylogenetic inference. The methods used under a structured population differ from those needed when a population is not structured. In this paper, we compared two supervised machine learning techniques, that is artificial neural network (ANN) and logistic regression models for prediction of an underlying structure for phylogenetic trees. We carried out parameter tuning for the models to identify optimal models. We then performed 10-fold cross-validation on the optimal models for both logistic regression?and ANN. We also performed a non-supervised technique called clustering to identify the number of clusters that could be identified from simulated phylogenetic trees. The trees were from?both structured?and non-structured populations. Clustering and prediction using classification techniques were?done using tree statistics such as Colless, Sackin and cophenetic indices, among others. Results from 10-fold cross-validation revealed that both logistic regression and ANN models had comparable results, with both models having average accuracy rates of over 0.75. Most of the clustering indices used resulted in 2 or 3 as the optimal number of clusters.展开更多
A finite random graph generated by continuous time birth and death processes with exponentially distributed waiting times was investigated, which is similar to a communication network in daily life. The vertices are t...A finite random graph generated by continuous time birth and death processes with exponentially distributed waiting times was investigated, which is similar to a communication network in daily life. The vertices are the living particles, and directed edges go from mothers to daughters. The size of the communication network was studied. Furthermore, the probability of successfully connecting senders with receivers and the transmitting speed of information were obtained.展开更多
This paper presents a new method for obtaining network properties from incomplete data sets. Problems associated with missing data represent well-known stumbling blocks in Social Network Analysis. The method of “esti...This paper presents a new method for obtaining network properties from incomplete data sets. Problems associated with missing data represent well-known stumbling blocks in Social Network Analysis. The method of “estimating connectivity from spanning tree completions” (ECSTC) is specifically designed to address situations where only spanning tree(s) of a network are known, such as those obtained through respondent driven sampling (RDS). Using repeated random completions derived from degree information, this method forgoes the usual step of trying to obtain final edge or vertex rosters, and instead aims to estimate network-centric properties of vertices probabilistically from the spanning trees themselves. In this paper, we discuss the problem of missing data and describe the protocols of our completion method, and finally the results of an experiment where ECSTC was used to estimate graph dependent vertex properties from spanning trees sampled from a graph whose characteristics were known ahead of time. The results show that ECSTC methods hold more promise for obtaining network-centric properties of individuals from a limited set of data than researchers may have previously assumed. Such an approach represents a break with past strategies of working with missing data which have mainly sought means to complete the graph, rather than ECSTC’s approach, which is to estimate network properties themselves without deciding on the final edge set.展开更多
Perfect state transfer(PST)has great significance due to its applications in quantum information processing and quantum computation.The main problem we study in this paper is to determine whether the two-fold Cayley t...Perfect state transfer(PST)has great significance due to its applications in quantum information processing and quantum computation.The main problem we study in this paper is to determine whether the two-fold Cayley tree,an extension of the Cayley tree,admits perfect state transfer between two roots using quantum walks.We show that PST can be achieved by means of the so-called nonrepeating quantum walk[Phys.Rev.A 89042332(2014)]within time steps that are the distance between the two roots;while both the continuous-time quantum walk and the typical discrete-time quantum walk with Grover coin approaches fail.Our results suggest that in some cases the dynamics of a discrete-time quantum walk may be much richer than that of the continuous-time quantum walk.展开更多
To assess road traffic safety risk in civil aviation airports and develop effective accident prevention measures,this study proposed a risk assessment method based on accident tree and Bayesian network for airport air...To assess road traffic safety risk in civil aviation airports and develop effective accident prevention measures,this study proposed a risk assessment method based on accident tree and Bayesian network for airport aircraft activity areas.It identified influencing factors in the aircraft activity area from the perspectives of person-vehicle-road-environment-management and analyzed their relationships.The Bayesian network was utilized to determine initial probabilities for each influencing factor.Findings indicated a relatively high overall safety level in the airport's road traffic system.Accident trees were employed to qualitatively and quantitatively analyze common human-vehicle accident patterns.The initial probabilities obtained from the Bayesian network served as basic event probabilities in the accident tree to determine the occurrence probability of the top event.Taking a 4F airport in China as an example,accident cause analysis identified five important risk sources in human-vehicle accidents,including blind spots for special vehicles,illegal driving by drivers,pedestrians violating regulations,passengers entering restricted areas,and blind spots at intersections.Corresponding safety management measures were formulated.The study concluded that the integration of Bayesian networks and accident trees effectively determines accident probabilities and offers specific solutions,thus playing a crucial role in enhancing road traffic safety management within aviation airports.展开更多
Prunus africana is a species of great economic, medicinal and ecological importance. Due to its multiple uses, unsustainable exploitation methods and low regeneration capacity in tropical rainforests, this species is ...Prunus africana is a species of great economic, medicinal and ecological importance. Due to its multiple uses, unsustainable exploitation methods and low regeneration capacity in tropical rainforests, this species is threatened with extinction. Present and exploited in the eastern part of DR Congo, knowledge of the dynamics of post-bark regeneration of Prunus africana remains fragmentary and poorly known. In North Kivu province, this species thrives in both afromontane forest and lowland tropical rainforest habitats. In order to contribute to the rational and sustainable exploitation of Prunus africana in this province, this paper was carried out with the objective of contributing to the knowledge of the dynamics of the regeneration of post-harvest bark of Prunus africana in two exploitation sites (low and high altitude). To achieve this objective, the inventory was conducted on 16 plots of 25 hectares each, with 8 plots per site. Dendrometric parameters (diameter at breast height (DBH), total tree height) and tree growth and regeneration parameters, i.e., stem bark thickness of the unharvested and harvested portions of the trees (bark reconstitution) were measured. A total of 716 barked stems of Prunus africana in 2016 in 25 hectares constituted the study sample. Results show that sites do not influence diameter at breast height of P. africana trees (p > 0.05) or total tree height. The bark diameter of harvested trees and the bark diameter of unharvested trees varied significantly by site (p 0.05). In contrast, the annual growth rate of bark differed with altitude;the highest rate was observed in trees growing at high altitude (2.97 ± 0.9 mm/yr) compared to 2.23 ± 0.74 mm/yr at low altitude. In view of these results, this study indicates that a half-rotation of 7 years could allow an effective reconstitution of the bark of Prunus africana at the second passage on the remaining side of the same stem.展开更多
Spanning tree(τ)has an enormous application in computer science and chemistry to determine the geometric and dynamics analysis of compact polymers.In the field of medicines,it is helpful to recognize the epidemiology...Spanning tree(τ)has an enormous application in computer science and chemistry to determine the geometric and dynamics analysis of compact polymers.In the field of medicines,it is helpful to recognize the epidemiology of hepatitis C virus(HCV)infection.On the other hand,Kemeny’s constant(Ω)is a beneficial quantifier characterizing the universal average activities of a Markov chain.This network invariant infers the expressions of the expected number of time-steps required to trace a randomly selected terminus state since a fixed beginning state si.Levene and Loizou determined that the Kemeny’s constant can also be obtained through eigenvalues.Motivated by Levene and Loizou,we deduced the Kemeny’s constant and the number of spanning trees of hexagonal ring network by their normalized Laplacian eigenvalues and the coefficients of the characteristic polynomial.Based on the achieved results,entirely results are obtained for the M鯾ius hexagonal ring network.展开更多
Agrobacterium tumefaciens-mediated transformation has been widely adopted for plant genetic engineering and the study of gene function(Krenek et al.,2015).This method is prevalent in the genetic transformation of herb...Agrobacterium tumefaciens-mediated transformation has been widely adopted for plant genetic engineering and the study of gene function(Krenek et al.,2015).This method is prevalent in the genetic transformation of herbaceous plants,with notable applications in species such as Arabidopsis(Yin et al.,2024),soybean(Zhang et al.,2024),rice(Zhang et al.,2020),and Chinese cabbage(Li et al.,2021).However,its application in fruit trees is limited.This is primarily due to their long growth cycles and lack of rapid,efficient,and stable transgenic systems,which severely hinders foundational research involving plant genetic transformation(Mei et al.,2024).Furthermore,for subtropical fruit trees,the presence of recalcitrant seeds adds an extra layer of difficulty to genetic transformation(Umarani et al.,2015),as most methods rely on seed germination as a basis for transformation.展开更多
Tree endophytic fungi play an important role in reducing insect herbivory,either by repelling them or kill-ing them directly.Identifying which fungi show such activ-ity could lead to new environmentally friendly pesti...Tree endophytic fungi play an important role in reducing insect herbivory,either by repelling them or kill-ing them directly.Identifying which fungi show such activ-ity could lead to new environmentally friendly pesticides.In this study,the Mediterranean basin climate conditions are projected to harshen in the next decades,will increase vulnerability of tree species to pest invasions.Endophytic fungi were isolated from wood and leaves of Quercus pyr-enaica,Q.ilex and Q.suber and tested for virulence against adults of the mealworm beetle,Tenebrio molitor L.using a direct contact method.Only 3 of 111 sporulating isolates had entomopathogenic activity,all identified as Lecanicillium lecanii.The pathogenicity of L.lecanii on T.molitor resulted in a median lethal time(TL50)of 14-16 d.Compared with commercial products,L.lecanii caused faster insect death than the nematode Steinernema carpocapsae and nuclear polyhedrosis virus(no effect on T.molitor survival),and slower than Beauveria bassiana(TL50=5),Beauveria pseu-dobassiana(TL50=8d)and Bacillus thuriengensis(80%mortality first day after inoculation).Mortality was also accelerated under water stress,reducing TL50 by an addi-tional 33%.Remarkably,water stress alone had a comparable effect on mortality to that of L.lecanii isolates.This study confirms T.molitor as a good model insect for pathogenicity testing and agrees with management policies proposed in the EU Green Deal.展开更多
基金carried out within the framework of the most important innovative project of state importance“Development of a system of ground-based and remote monitoring of carbon pools and greenhouse gas fluxes on the territory of the Russian Federation,…”(No.123030300031-6)in the northern taiga subzone and on the border of tundra and taiga under the state assignment of the Forest Institute of the Karelian Research Center of the Russian Academy of Sciences(FMEN-2021-0018)with the partial financial support from RSF(grant no.21-14-00204)。
文摘Background:The heartwood(HW)proportion in the trunk of mature trees is an important characteristic not only for wood quality but also for assessing the role of forests in carbon sequestration.We have for the first time studied the proportion of HW in the trunk and the distribution of carbon and extractives in sapwood(SW)and HW of 70–80 year old Pinus sylvestris L.trees under different growing conditions in the pine forests of North-West Russia.Method:We have examined the influence of conditions and tree position in stand(dominant,intermediate and suppressed trees)in the ecological series:blueberry pine forest(Blu)–lingonberry pine forest(Lin)–lichen pine forest(Lic).We have analyzed the influence of climate conditions in the biogeographical series of Lin:the middle taiga subzone–the northern taiga subzone–the transition area of the northern taiga subzone and tundra.Results:We found that the carbon concentration in HW was 1.6%–3.4%higher than in SW,and the difference depended on growing conditions.Carbon concentration in HW increased with a decrease in stand productivity(Blu-Lin-Lic).In medium-productive stands,the carbon concentration in SW was higher in intermediate and supressed trees compared to dominant trees.In the series from south to north,carbon concentration in HW increased by up to 2%,while in SW,it rose by 2.7%–3.8%.Conclusions:Our results once again emphasized the need for an empirical assessment of the accurate carbon content in aboveground wood biomass,including various forest growing conditions,to better understand the role of boreal forests in carbon storage.
基金supported by Istanbul Technical University(Project No.45698)supported through the“Young Researchers’Career Development Project-training of doctoral students”of the Croatian Science Foundation.
文摘This paper investigates the reliability of internal marine combustion engines using an integrated approach that combines Fault Tree Analysis(FTA)and Bayesian Networks(BN).FTA provides a structured,top-down method for identifying critical failure modes and their root causes,while BN introduces flexibility in probabilistic reasoning,enabling dynamic updates based on new evidence.This dual methodology overcomes the limitations of static FTA models,offering a comprehensive framework for system reliability analysis.Critical failures,including External Leakage(ELU),Failure to Start(FTS),and Overheating(OHE),were identified as key risks.By incorporating redundancy into high-risk components such as pumps and batteries,the likelihood of these failures was significantly reduced.For instance,redundant pumps reduced the probability of ELU by 31.88%,while additional batteries decreased the occurrence of FTS by 36.45%.The results underscore the practical benefits of combining FTA and BN for enhancing system reliability,particularly in maritime applications where operational safety and efficiency are critical.This research provides valuable insights for maintenance planning and highlights the importance of redundancy in critical systems,especially as the industry transitions toward more autonomous vessels.
基金supported by the research start-up funds for invited doctor of Lanzhou University of Technology under Grant 14/062402。
文摘In the context of modern software development characterized by increasing complexity and compressed development cycles,traditional static vulnerability detection methods face prominent challenges including high false positive rates and missed detections of complex logic due to their over-reliance on rule templates.This paper proposes a Syntax-Aware Hierarchical Attention Network(SAHAN)model,which achieves high-precision vulnerability detection through grammar-rule-driven multi-granularity code slicing and hierarchical semantic fusion mechanisms.The SAHAN model first generates Syntax Independent Units(SIUs),which slices the code based on Abstract Syntax Tree(AST)and predefined grammar rules,retaining vulnerability-sensitive contexts.Following this,through a hierarchical attention mechanism,the local syntax-aware layer encodes fine-grained patterns within SIUs,while the global semantic correlation layer captures vulnerability chains across SIUs,achieving synergistic modeling of syntax and semantics.Experiments show that on benchmark datasets like QEMU,SAHAN significantly improves detection performance by 4.8%to 13.1%on average compared to baseline models such as Devign and VulDeePecker.
基金The National Natural Science Foundation of China(No10671033)Southeast University Science Foundation ( NoXJ0607230)
文摘L（ s, t）-labeling is a variation of graph coloring which is motivated by a special kind of the channel assignment problem. Let s and t be any two nonnegative integers. An L （s, t）-labeling of a graph G is an assignment of integers to the vertices of G such that adjacent vertices receive integers which differ by at least s, and vertices that are at distance of two receive integers which differ by at least t. Given an L（s, t） -labeling f of a graph G, the L（s, t） edge span of f, βst （ G, f） = max { ｜f（u） -f（v）｜： （ u, v） ∈ E（G） } is defined. The L（ s, t） edge span of G, βst（G）, is minβst（G,f）, where the minimum runs over all L（s, t）-labelings f of G. Let T be any tree with a maximum degree of △≥2. It is proved that if 2s≥t≥0, then βst（T） =（ [△/2 ] - 1）t ＋s; if 0≤2s 〈 t and △ is even, then βst（T） = [ （△ - 1） t/2 ] ; and if 0 ≤2s 〈 t and △ is odd, then βst（T） = （△ - 1） t/2 ＋ s. Thus, the L（s, t） edge spans of the Cartesian product of two paths and of the square lattice are completely determined.
基金financially supported by the National Key Research and Development Program(2017YFD0600101)the Central University Basic Research and Operating Expenses of Special Funding(2572016CB04)the Harbin Application Technology Research and Development Projects(2016RQQXJ134)
文摘Electrical pollution is a worldwide concern,because it is potentially harmful to human health.Trees not only play a significant role in moderating the climate,but also can be used as shields against electrical pollution.Shielding effects on the electric field strength under transmission lines by two tree species,Populus alba and Larix gmelinii,were examined in this study.The electrical resistivity at different heights of trees was measured using a PiCUS sonic tomograph,which can image the electrical impedance for trees.The electric field strength around the trees was measured with an elf field strength measurement system,HI-3604,and combined with tree resistivity to develop a model for calculating the electric field intensity around trees using the finite element method.In addition,the feasibility of the finite element method was confirmed by comparing the calculated results and experimental data.The results showed that the trees did reduce the electric field strength.The electric field intensity was reduced by 95.6%,and P.alba was better than L.gmelinii at shielding.
基金supported by the National Natural Science Fundation of China (6097408261075055)the Fundamental Research Funds for the Central Universities (K50510700004)
文摘The learning Bayesian network （BN） structure from data is an NP-hard problem and still one of the most exciting chal- lenges in the machine learning. In this work, a novel algorithm is presented which combines ideas from local learning, constraint- based, and search-and-score techniques in a principled and ef- fective way. It first reconstructs the junction tree of a BN and then performs a K2-scoring greedy search to orientate the local edges in the cliques of junction tree. Theoretical and experimental results show the proposed algorithm is capable of handling networks with a large number of variables. Its comparison with the well-known K2 algorithm is also presented.
文摘In this paper a new modeling framework for the dependability analysis of complex systems is presented and related to dynamic fault trees (DFTs). The methodology is based on a modular approach: two separate models are used to handle, the fault logic and the stochastic dependencies of the system. Thus, the fault schema, free of any dependency logic, can be easily evaluated, while the dependency schema allows the modeler to design new kind of non-trivial dependencies not easily caught by the traditional holistic methodologies. Moreover, the use of a dependency schema allows building a pure behavioral model that can be used for various kinds of dependability studies. In the paper is shown how to build and integrate the two modular models and convert them in a Stochastic Activity Network. Furthermore, based on the construction of the schema that embeds the stochastic dependencies, the procedure to convert DFTs into static fault trees is shown, allowing the resolution of DFTs in a very efficient way.
基金Supported in part by the National Natural Science Foundation of China (No.60272046, No.60102011), Na-tional High Technology Project of China (No.2002AA143010), Natural Science Foundation of Jiangsu Province (No.BK2001042), and the Foundation for Excellent Doctoral Dissertation of Southeast Univer-sity (No.YBJJ0412).
文摘Several data mining techniques such as Hidden Markov Model (HMM), artificial neural network, statistical techniques and expert systems are used to model network packets in the field of intrusion detection. In this paper a novel intrusion detection mode based on understandable Neural Network Tree (NNTree) is pre-sented. NNTree is a modular neural network with the overall structure being a Decision Tree (DT), and each non-terminal node being an Expert Neural Network (ENN). One crucial advantage of using NNTrees is that they keep the non-symbolic model ENN’s capability of learning in changing environments. Another potential advantage of using NNTrees is that they are actually “gray boxes” as they can be interpreted easily if the num-ber of inputs for each ENN is limited. We showed through experiments that the trained NNTree achieved a simple ENN at each non-terminal node as well as a satisfying recognition rate of the network packets dataset. We also compared the performance with that of a three-layer backpropagation neural network. Experimental results indicated that the NNTree based intrusion detection model achieved better performance than the neural network based intrusion detection model.
文摘Based on a fuzzy neural network, the letter presents an approach for the induction of decision trees. The approach makes use of the weights of fuzzy mappings in the fuzzy neural network which has been trained. It can realize the optimization of fuzzy decision trees by branch cutting, and improve the ratio of correctness and efficiency of the induction of decision trees.
文摘Agriculture and farming are mainly dependent on weather especially in Malaysia as it received heavy rainfall throughout the years. An efficient crop or tree management system with a weather forecast needed for suitable planning of farming operation. Radial Basis Function Neural Network (RBFNN) algorithm was used in this study to predict rainfall and the main focus of this study is to analyze the factor that affect</span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">s</span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;"> the performance of neural model. This study found that the model works better the more hidden nodes and the optimum learning rate is 0.01 with the RMSE 49% and the percentage accuracy is 57%. Besides that, it is found that the meteorology data also affect the model performance. Future research can be conducted to improve the rainfall forecast of this study and improv</span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">e</span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;"> the tree management system.
文摘Understanding an underlying structure for phylogenetic trees is very important as it informs on the methods that should be employed during phylogenetic inference. The methods used under a structured population differ from those needed when a population is not structured. In this paper, we compared two supervised machine learning techniques, that is artificial neural network (ANN) and logistic regression models for prediction of an underlying structure for phylogenetic trees. We carried out parameter tuning for the models to identify optimal models. We then performed 10-fold cross-validation on the optimal models for both logistic regression?and ANN. We also performed a non-supervised technique called clustering to identify the number of clusters that could be identified from simulated phylogenetic trees. The trees were from?both structured?and non-structured populations. Clustering and prediction using classification techniques were?done using tree statistics such as Colless, Sackin and cophenetic indices, among others. Results from 10-fold cross-validation revealed that both logistic regression and ANN models had comparable results, with both models having average accuracy rates of over 0.75. Most of the clustering indices used resulted in 2 or 3 as the optimal number of clusters.
基金Project supported by the National Natural Science Foundation of China （Grant Nos.10471088, 60572126）
文摘A finite random graph generated by continuous time birth and death processes with exponentially distributed waiting times was investigated, which is similar to a communication network in daily life. The vertices are the living particles, and directed edges go from mothers to daughters. The size of the communication network was studied. Furthermore, the probability of successfully connecting senders with receivers and the transmitting speed of information were obtained.
文摘This paper presents a new method for obtaining network properties from incomplete data sets. Problems associated with missing data represent well-known stumbling blocks in Social Network Analysis. The method of “estimating connectivity from spanning tree completions” (ECSTC) is specifically designed to address situations where only spanning tree(s) of a network are known, such as those obtained through respondent driven sampling (RDS). Using repeated random completions derived from degree information, this method forgoes the usual step of trying to obtain final edge or vertex rosters, and instead aims to estimate network-centric properties of vertices probabilistically from the spanning trees themselves. In this paper, we discuss the problem of missing data and describe the protocols of our completion method, and finally the results of an experiment where ECSTC was used to estimate graph dependent vertex properties from spanning trees sampled from a graph whose characteristics were known ahead of time. The results show that ECSTC methods hold more promise for obtaining network-centric properties of individuals from a limited set of data than researchers may have previously assumed. Such an approach represents a break with past strategies of working with missing data which have mainly sought means to complete the graph, rather than ECSTC’s approach, which is to estimate network properties themselves without deciding on the final edge set.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.61802002 and 61701004)the Natural Science Foundation of Anhui Province,China(Grant No.1708085MF162)the Natural Science Foundation of Jiangsu Province,China(Grant No.BK20171458)。
文摘Perfect state transfer(PST)has great significance due to its applications in quantum information processing and quantum computation.The main problem we study in this paper is to determine whether the two-fold Cayley tree,an extension of the Cayley tree,admits perfect state transfer between two roots using quantum walks.We show that PST can be achieved by means of the so-called nonrepeating quantum walk[Phys.Rev.A 89042332(2014)]within time steps that are the distance between the two roots;while both the continuous-time quantum walk and the typical discrete-time quantum walk with Grover coin approaches fail.Our results suggest that in some cases the dynamics of a discrete-time quantum walk may be much richer than that of the continuous-time quantum walk.
文摘To assess road traffic safety risk in civil aviation airports and develop effective accident prevention measures,this study proposed a risk assessment method based on accident tree and Bayesian network for airport aircraft activity areas.It identified influencing factors in the aircraft activity area from the perspectives of person-vehicle-road-environment-management and analyzed their relationships.The Bayesian network was utilized to determine initial probabilities for each influencing factor.Findings indicated a relatively high overall safety level in the airport's road traffic system.Accident trees were employed to qualitatively and quantitatively analyze common human-vehicle accident patterns.The initial probabilities obtained from the Bayesian network served as basic event probabilities in the accident tree to determine the occurrence probability of the top event.Taking a 4F airport in China as an example,accident cause analysis identified five important risk sources in human-vehicle accidents,including blind spots for special vehicles,illegal driving by drivers,pedestrians violating regulations,passengers entering restricted areas,and blind spots at intersections.Corresponding safety management measures were formulated.The study concluded that the integration of Bayesian networks and accident trees effectively determines accident probabilities and offers specific solutions,thus playing a crucial role in enhancing road traffic safety management within aviation airports.
文摘Prunus africana is a species of great economic, medicinal and ecological importance. Due to its multiple uses, unsustainable exploitation methods and low regeneration capacity in tropical rainforests, this species is threatened with extinction. Present and exploited in the eastern part of DR Congo, knowledge of the dynamics of post-bark regeneration of Prunus africana remains fragmentary and poorly known. In North Kivu province, this species thrives in both afromontane forest and lowland tropical rainforest habitats. In order to contribute to the rational and sustainable exploitation of Prunus africana in this province, this paper was carried out with the objective of contributing to the knowledge of the dynamics of the regeneration of post-harvest bark of Prunus africana in two exploitation sites (low and high altitude). To achieve this objective, the inventory was conducted on 16 plots of 25 hectares each, with 8 plots per site. Dendrometric parameters (diameter at breast height (DBH), total tree height) and tree growth and regeneration parameters, i.e., stem bark thickness of the unharvested and harvested portions of the trees (bark reconstitution) were measured. A total of 716 barked stems of Prunus africana in 2016 in 25 hectares constituted the study sample. Results show that sites do not influence diameter at breast height of P. africana trees (p > 0.05) or total tree height. The bark diameter of harvested trees and the bark diameter of unharvested trees varied significantly by site (p 0.05). In contrast, the annual growth rate of bark differed with altitude;the highest rate was observed in trees growing at high altitude (2.97 ± 0.9 mm/yr) compared to 2.23 ± 0.74 mm/yr at low altitude. In view of these results, this study indicates that a half-rotation of 7 years could allow an effective reconstitution of the bark of Prunus africana at the second passage on the remaining side of the same stem.
文摘Spanning tree(τ)has an enormous application in computer science and chemistry to determine the geometric and dynamics analysis of compact polymers.In the field of medicines,it is helpful to recognize the epidemiology of hepatitis C virus(HCV)infection.On the other hand,Kemeny’s constant(Ω)is a beneficial quantifier characterizing the universal average activities of a Markov chain.This network invariant infers the expressions of the expected number of time-steps required to trace a randomly selected terminus state since a fixed beginning state si.Levene and Loizou determined that the Kemeny’s constant can also be obtained through eigenvalues.Motivated by Levene and Loizou,we deduced the Kemeny’s constant and the number of spanning trees of hexagonal ring network by their normalized Laplacian eigenvalues and the coefficients of the characteristic polynomial.Based on the achieved results,entirely results are obtained for the M鯾ius hexagonal ring network.
基金funded by the Key-Area Research and Development Program of Guangdong Province(Grant No.2022B0202070002)the Guangxi Science and Technology Major Program(Grant No.GuikeAA23023007-2)+1 种基金the Guangdong Province Modern Agricultural Industry Technology System Innovation Team Construction Project(2024CXTD19)Guangdong Basic and Applied Basic Research Foundation(Grant No.2023A1515010303)。
文摘Agrobacterium tumefaciens-mediated transformation has been widely adopted for plant genetic engineering and the study of gene function(Krenek et al.,2015).This method is prevalent in the genetic transformation of herbaceous plants,with notable applications in species such as Arabidopsis(Yin et al.,2024),soybean(Zhang et al.,2024),rice(Zhang et al.,2020),and Chinese cabbage(Li et al.,2021).However,its application in fruit trees is limited.This is primarily due to their long growth cycles and lack of rapid,efficient,and stable transgenic systems,which severely hinders foundational research involving plant genetic transformation(Mei et al.,2024).Furthermore,for subtropical fruit trees,the presence of recalcitrant seeds adds an extra layer of difficulty to genetic transformation(Umarani et al.,2015),as most methods rely on seed germination as a basis for transformation.
基金supported by LIFE project MYCORESTORE“Innovative use of mycological resources for resilient and productive Mediterranean forests threatened by climate change,LIFE18 CCA/ES/001110”projects VA178P23 and VA208P20 funded by JCYL(Spain),both co-financed by FEDER(UE)budget.
文摘Tree endophytic fungi play an important role in reducing insect herbivory,either by repelling them or kill-ing them directly.Identifying which fungi show such activ-ity could lead to new environmentally friendly pesticides.In this study,the Mediterranean basin climate conditions are projected to harshen in the next decades,will increase vulnerability of tree species to pest invasions.Endophytic fungi were isolated from wood and leaves of Quercus pyr-enaica,Q.ilex and Q.suber and tested for virulence against adults of the mealworm beetle,Tenebrio molitor L.using a direct contact method.Only 3 of 111 sporulating isolates had entomopathogenic activity,all identified as Lecanicillium lecanii.The pathogenicity of L.lecanii on T.molitor resulted in a median lethal time(TL50)of 14-16 d.Compared with commercial products,L.lecanii caused faster insect death than the nematode Steinernema carpocapsae and nuclear polyhedrosis virus(no effect on T.molitor survival),and slower than Beauveria bassiana(TL50=5),Beauveria pseu-dobassiana(TL50=8d)and Bacillus thuriengensis(80%mortality first day after inoculation).Mortality was also accelerated under water stress,reducing TL50 by an addi-tional 33%.Remarkably,water stress alone had a comparable effect on mortality to that of L.lecanii isolates.This study confirms T.molitor as a good model insect for pathogenicity testing and agrees with management policies proposed in the EU Green Deal.
