Adapting Grice's maxims in the teaching of writing

Grice's maxims,which define the conditions for efficient spoken communication,can be adapted to the teaching of writing by providing both teachers and writers with a way of understanding successful and unsuccessful written correspondence in mono-and cross-cultural settings.A survey of lay readers' responses to a sample letter which show that,while there are individual differences in the way these maxims are interpreted,readers expect clarity,brevity,and sincerity,and writing which fails to meet these expectations will be unfavorably received.Also discussed are the issues of contrastive rhetoric,and ways of helping writers to position themselves in relation to their real or imagined reader.

Understanding of English Contracts though Relation Maxims

Contract is the legal evidence of the concerning parties of business. And this lead to its unique characteristics: technical terms, archaism, borrowed words, juxtaposition, and abbreviation. The understanding of contracts is of vital importance for each party, because it concerns the share of interests. In order to avoid ambiguity that some words or sentence in English contracts may lead to, and achieve"best relevance and least effort"of communication, this paper, by applying relation maxim, deeply analyze how to understand English contracts though selection of words, modification, the complexity and simplicity of sentence.

花椒病虫害绿色防控技术研究进展

花椒(Zanthoxylum bungeanum Maxim.)经济价值较高,在中国广泛种植,但其生长过程中易遭受病虫危害,科学的防治技术措施对花椒的绿色发展至关重要。从生态调控技术、生物防治技术、理化诱控技术、科学用药技术4个方面对花椒病虫害绿色防控技术进行综述,以期为生产上花椒病虫害绿色防控提供参考。

A Bitcoin Address Multi-Classification Mechanism Based on Bipartite Graph-Based Maximization Consensus

Bitcoin is widely used as the most classic electronic currency for various electronic services such as exchanges,gambling,marketplaces,and also scams such as high-yield investment projects.Identifying the services operated by a Bitcoin address can help determine the risk level of that address and build an alert model accordingly.Feature engineering can also be used to flesh out labeled addresses and to analyze the current state of Bitcoin in a small way.In this paper,we address the problem of identifying multiple classes of Bitcoin services,and for the poor classification of individual addresses that do not have significant features,we propose a Bitcoin address identification scheme based on joint multi-model prediction using the mapping relationship between addresses and entities.The innovation of the method is to(1)Extract as many valuable features as possible when an address is given to facilitate the multi-class service identification task.(2)Unlike the general supervised model approach,this paper proposes a joint prediction scheme for multiple learners based on address-entity mapping relationships.Specifically,after obtaining the overall features,the address classification and entity clustering tasks are performed separately,and the results are subjected to graph-basedmaximization consensus.The final result ismade to baseline the individual address classification results while satisfying the constraint of having similarly behaving entities as far as possible.By testing and evaluating over 26,000 Bitcoin addresses,our feature extraction method captures more useful features.In addition,the combined multi-learner model obtained results that exceeded the baseline classifier reaching an accuracy of 77.4%.

Policy Network-Based Dual-Agent Deep Reinforcement Learning for Multi-Resource Task Offloading in Multi-Access Edge Cloud Networks

The Multi-access Edge Cloud(MEC) networks extend cloud computing services and capabilities to the edge of the networks. By bringing computation and storage capabilities closer to end-users and connected devices, MEC networks can support a wide range of applications. MEC networks can also leverage various types of resources, including computation resources, network resources, radio resources,and location-based resources, to provide multidimensional resources for intelligent applications in 5/6G.However, tasks generated by users often consist of multiple subtasks that require different types of resources. It is a challenging problem to offload multiresource task requests to the edge cloud aiming at maximizing benefits due to the heterogeneity of resources provided by devices. To address this issue,we mathematically model the task requests with multiple subtasks. Then, the problem of task offloading of multi-resource task requests is proved to be NP-hard. Furthermore, we propose a novel Dual-Agent Deep Reinforcement Learning algorithm with Node First and Link features(NF_L_DA_DRL) based on the policy network, to optimize the benefits generated by offloading multi-resource task requests in MEC networks. Finally, simulation results show that the proposed algorithm can effectively improve the benefit of task offloading with higher resource utilization compared with baseline algorithms.

A self-organization formation configuration based assignment probability and collision detection

The formation control of multiple unmanned aerial vehicles(multi-UAVs)has always been a research hotspot.Based on the straight line trajectory,a multi-UAVs target point assignment algorithm based on the assignment probability is proposed to achieve the shortest overall formation path of multi-UAVs with low complexity and reduce the energy consumption.In order to avoid the collision between UAVs in the formation process,the concept of safety ball is introduced,and the collision detection based on continuous motion of two time slots and the lane occupation detection after motion is proposed to avoid collision between UAVs.Based on the idea of game theory,a method of UAV motion form setting based on the maximization of interests is proposed,including the maximization of self-interest and the maximization of formation interest is proposed,so that multi-UAVs can complete the formation task quickly and reasonably with the linear trajectory assigned in advance.Finally,through simulation verification,the multi-UAVs target assignment algorithm based on the assignment probability proposed in this paper can effectively reduce the total path length,and the UAV motion selection method based on the maximization interests can effectively complete the task formation.

Identifying influential spreaders in social networks: A two-stage quantum-behaved particle swarm optimization with Lévy flight

The influence maximization problem aims to select a small set of influential nodes, termed a seed set, to maximize their influence coverage in social networks. Although the methods that are based on a greedy strategy can obtain good accuracy, they come at the cost of enormous computational time, and are therefore not applicable to practical scenarios in large-scale networks. In addition, the centrality heuristic algorithms that are based on network topology can be completed in relatively less time. However, they tend to fail to achieve satisfactory results because of drawbacks such as overlapped influence spread. In this work, we propose a discrete two-stage metaheuristic optimization combining quantum-behaved particle swarm optimization with Lévy flight to identify a set of the most influential spreaders. According to the framework,first, the particles in the population are tasked to conduct an exploration in the global solution space to eventually converge to an acceptable solution through the crossover and replacement operations. Second, the Lévy flight mechanism is used to perform a wandering walk on the optimal candidate solution in the population to exploit the potentially unidentified influential nodes in the network. Experiments on six real-world social networks show that the proposed algorithm achieves more satisfactory results when compared to other well-known algorithms.

Sum-Rate Maximization in Active RIS-Assisted Multi-Antenna WPCN

In this paper,we propose an active reconfigurable intelligent surface(RIS)enabled hybrid relaying scheme for a multi-antenna wireless powered communication network(WPCN),where the active RIS is employed to assist both wireless energy transfer(WET)from the power station(PS)to energyconstrained users and wireless information transmission(WIT)from users to the receiving station(RS).For further performance enhancement,we propose to employ both transmit beamforming at the PS and receive beamforming at the RS.We formulate a sumrate maximization problem by jointly optimizing the RIS phase shifts and amplitude reflection coefficients for both the WET and the WIT,transmit and receive beamforming vectors,and network resource allocation.To solve this non-convex problem,we propose an efficient alternating optimization algorithm with the linear minimum mean squared error criterion,semidefinite relaxation(SDR)and successive convex approximation techniques.Specifically,the tightness of applying the SDR is proved.Simulation results demonstrate that our proposed scheme with 10 reflecting elements(REs)and 4 antennas can achieve 17.78%and 415.48%performance gains compared to the single-antenna scheme with 10 REs and passive RIS scheme with 100 REs,respectively.

A STABILITY RESULT FOR TRANSLATINGSPACELIKE GRAPHS IN LORENTZ MANIFOLDS

In this paper,we investigate spacelike graphs defined over a domain Ω⊂M^(n) in the Lorentz manifold M^(n)×ℝ with the metric−ds^(2)+σ,where M^(n) is a complete Riemannian n-manifold with the metricσ,Ωhas piecewise smooth boundary,and ℝ denotes the Euclidean 1-space.We prove an interesting stability result for translating spacelike graphs in M^(n)×ℝ under a conformal transformation.

Maximal operators of pseudo-differential operators with rough symbols

Consider a pseudo-differential operator T_(a)f(x)=∫_(R^(n))e^(ix,ζ)a(x,ζ)f(ζ)dζwhere the symbol a is in the rough Hormander class L^(∞)S_(ρ)^(m)with m∈R andρ∈[0,1].In this note,when 1≤p≤2,if n(ρ-1)/p and a∈L^(∞)S_(ρ)^(m),then for any f∈S(R^(n))and x∈R^(n),we prove that M(T_(a)f)(x)≤C(M(|f|^(p))(x))^(1/p) where M is the Hardy-Littlewood maximal operator.Our theorem improves the known results and the bound on m is sharp,in the sense that n(ρ-1)/p can not be replaced by a larger constant.

MAXIMAL FUNCTION CHARACTERIZATIONS OF HARDY SPACES ASSOCIATED WITH BOTH NON-NEGATIVE SELF-ADJOINT OPERATORS SATISFYING GAUSSIAN ESTIMATES AND BALL QUASI-BANACH FUNCTION SPACES

Assume that L is a non-negative self-adjoint operator on L^(2)(ℝ^(n))with its heat kernels satisfying the so-called Gaussian upper bound estimate and that X is a ball quasi-Banach function space onℝ^(n) satisfying some mild assumptions.Let HX,L(ℝ^(n))be the Hardy space associated with both X and L,which is defined by the Lusin area function related to the semigroup generated by L.In this article,the authors establish various maximal function characterizations of the Hardy space HX,L(ℝ^(n))and then apply these characterizations to obtain the solvability of the related Cauchy problem.These results have a wide range of generality and,in particular,the specific spaces X to which these results can be applied include the weighted space,the variable space,the mixed-norm space,the Orlicz space,the Orlicz-slice space,and the Morrey space.Moreover,the obtained maximal function characterizations of the mixed-norm Hardy space,the Orlicz-slice Hardy space,and the Morrey-Hardy space associated with L are completely new.

Growth of RB Population in the Conversion Phase of Chlamydia Life Cycle

Upon infecting a host cell,the reticulate body(RB)form of the Chlamydia bacteria simply proliferates by binary fission for an extended period.Available data show only RB units in the infected cells 20 hours post infection(hpi),spanning nearly half way through the development cycle.With data collected every 4 hpi,conversion to the elementary body(EB)form begins abruptly at a rapid rate sometime around 24 hpi.By modeling proliferation and conversion as simple birth and death processes,it has been shown that the optimal strategy for maximizing the total(mean)EB population at host cell lysis time is a bang-bang control qualitatively replicating the observed conversion activities.However,the simple birth and death model for the RB proliferation and conversion to EB deviates in a significant way from the available data on the evolution of the RB population after the onset of RB-to-EB conversion.By working with a more refined model that takes into account a small size threshold eligibility requirement for conversion noted in the available data,we succeed in removing the deficiency of the previous models on the evolution of the RB population without affecting the optimal bang-bang conversion strategy.

Optimal Shape Factor and Fictitious Radius in the MQ-RBF:Solving Ill-Posed Laplacian Problems

To solve the Laplacian problems,we adopt a meshless method with the multiquadric radial basis function(MQRBF)as a basis whose center is distributed inside a circle with a fictitious radius.A maximal projection technique is developed to identify the optimal shape factor and fictitious radius by minimizing a merit function.A sample function is interpolated by theMQ-RBF to provide a trial coefficient vector to compute the merit function.We can quickly determine the optimal values of the parameters within a preferred rage using the golden section search algorithm.The novel method provides the optimal values of parameters and,hence,an optimal MQ-RBF;the performance of the method is validated in numerical examples.Moreover,nonharmonic problems are transformed to the Poisson equation endowed with a homogeneous boundary condition;this can overcome the problem of these problems being ill-posed.The optimal MQ-RBF is extremely accurate.We further propose a novel optimal polynomial method to solve the nonharmonic problems,which achieves high precision up to an order of 10^(−11).

{(3,4),4}-富勒烯图的极大共振性

A {(3,4), 4}-fullerene graph S is a 4-regular map on the sphere whose faces are of length 3 or 4.It follows from Euler s formula that the number of triangular faces is eight.A set H of disjoint quadrangular faces of S is called resonant pattern if S has a perfect matching M such that every quadrangular face in H is M-alternating.Let k be a positive integer,S is k-resonant if any i≤k disjoint quadrangular faces of S form a resonant pattern.Moreover,if graph S is k-resonant for any integer k,then S is called maximally resonant.In this paper,we show that the maximally resonant{(3,4),4}-fullerene graphs are S_6,S_8,S_(10)~2,S_(12)~2,S_(12)~4,S_(12)~5,S_(14)~3,S_(14)~5,S_(16)~3,S_(18)~5,S_(24) as shown in Fig.1.As a corollary,it is shown that if a {(3,4),4}-fullerene graph is 4-resonant,then it is also maximally resonant.

Screening for Anti-tumor Activity of Fractions from Buddleja officinalis Maxim

[Objectives]The anti-tumor activity of fractions from Buddleja officinalis Maxim.by petroleum ether,ethyl acetate,n-butanol and water solvent was studied.[Methods]The ethanol extract from B.officinalis Maxim.was extracted and then concentrated with petroleum ether,ethyl acetate,n-butanol and water,respectively,and the extracts were obtained.The inhibitory effects of the four different fractions on the growth of three tumor cell lines in vitro were detected by CCK-8 method,and the median inhibitory concentration(IC 50 value)was calculated.[Results]The four fractions inhibited the growth of the three tumor cell lines in vitro,among which the n-butanol fraction had the best anti-tumor activity.The IC 50 values of the n-butanol fraction on human gastric cancer(SGC-7901),human breast cancer(MCF-7)and human liver cancer(BEL-7404)cell lines were 0.08,1.58 and 0.12 mg/mL,respectively.[Conclusions]Petroleum ether,ethyl acetate,n-butanol and water fractions from the ethanol extract of B.officinalis Maxim.had certain anti-tumor effects,and the n-butanol fraction had the best anti-tumor activity.

Determination of Total Flavonoids in Acanthopanax senticosus(Rupr. et Maxim.) Harms by Enzymolysis and Its Technological Optimization

In order to optimize the ultrasonic extraction technique for the total flavonoid of leaf yellows plus, the contents of 21 leaf yellows plus total flavonoid from four regions in Heilongjiang Province were comparatively analyzed. The ultrasonic extraction technology was optimized by Box-Behnken response surface method, and the total flavonoid content of 21 kinds of Acanthopanax senticosus(Rupr. et Maxim.) Harms from different producing areas were analyzed by cluster analysis. The optimal process conditions were determined as ultrasonic time 30 min, solid-liquid ratio 1 : 12 and ultrasonic power 250 W, and the average yield of the total flavonoid was 1.453 mg·g^ (-1). By optimizing the ultrasonic-assisted extraction method, the total flavonoid content from different producing areas was compared in the experiment, which provided certain data support for the optimization of the extraction process in the future and laid a certain theoretical foundation for the quality analysis of Chinese medicinal materials.

红花除虫菊和甘野菊的花粉采集与贮藏

花粉贮藏可有效解决远缘杂交亲本的花期不遇障碍,但是不同植物花粉合适的采集时机和适宜的贮藏技术差异较大。通过不同处理条件的花粉萌发率的检测,确定红花除虫菊[Pyrethrum coccineum(Willd.)Worosch.]和甘野菊[Dendranthema lavandulifolium var.seticuspe(Maxim.)Shih]的花粉最适合在其花粉期的第三天至第五天,于晴天10:00—13:00采集;花粉经干燥后,短期可贮于硫酸纸袋4℃冷藏,长期需置于-20℃、离心管内密封保存,90 d后仍能满足授粉的需要,该结果为远缘杂交奠定了基础。

山桐子性别分子标记的通用性验证

采用已知性别的120份山桐子(Idesia polycarpa Maxim.)样品,检验了2个已报道UBC841和STZ分子标记在山桐子性别鉴定中的通用性。同时,分析了大量简单重复序列间区扩增多态性(ISSR)和相关序列扩增多态性(SRAP)标记在山桐子雌雄株中的多态性。结果表明,UBC841标记在24份山桐子样品中可检测到多态性条带,但未检测到雌雄性别特异性条带;STZ标记可在部分样本中扩增出目的条带,但未表现出雌雄株性别特异性;说明这2组标记均未表现出良好的通用性,雌雄性别鉴别准确率较低。此外,筛选了26条ISSR引物和780对SRAP引物组,也未能获得雌雄性别特异标记,说明采用通用型分子标记ISSR和SRAP在山桐子中较难筛选到稳定、可靠的性别特异的标记。

An Influence Maximization Algorithm Based on Improved K-Shell in Temporal Social Networks

Influence maximization of temporal social networks(IMT)is a problem that aims to find the most influential set of nodes in the temporal network so that their information can be the most widely spread.To solve the IMT problem,we propose an influence maximization algorithm based on an improved K-shell method,namely improved K-shell in temporal social networks(KT).The algorithm takes into account the global and local structures of temporal social networks.First,to obtain the kernel value Ks of each node,in the global scope,it layers the network according to the temporal characteristic of nodes by improving the K-shell method.Then,in the local scope,the calculation method of comprehensive degree is proposed to weigh the influence of nodes.Finally,the node with the highest comprehensive degree in each core layer is selected as the seed.However,the seed selection strategy of KT can easily lose some influential nodes.Thus,by optimizing the seed selection strategy,this paper proposes an efficient heuristic algorithm called improved K-shell in temporal social networks for influence maximization(KTIM).According to the hierarchical distribution of cores,the algorithm adds nodes near the central core to the candidate seed set.It then searches for seeds in the candidate seed set according to the comprehensive degree.Experiments showthatKTIMis close to the best performing improved method for influence maximization of temporal graph(IMIT)algorithm in terms of effectiveness,but runs at least an order of magnitude faster than it.Therefore,considering the effectiveness and efficiency simultaneously in temporal social networks,the KTIM algorithm works better than other baseline algorithms.