A Versatile Method for Uniform Dispersion of Nanocarbons in Metal Matrix Based on Electrostatic Interactions

Realizing the uniform dispersion of nanocarbons such as carbon nanotube and graphene in metals, is an essential prerequisite to fully exhibit their enhancement effect in mechanical, thermal, and electrical properties of metal matrix composites(MMCs). In this work, we propose an effective method to achieve uniform distribution of nanocarbons in various metal flakes through a slurry-based method. It relies on the electrostatic interactions between the negatively charged nanocarbons and the positively charged metal flakes when mixed in slurry. For case study, flake metal powders(Al, Mg, Ti,Fe, and Cu) were positively charged in aqueous suspension by spontaneous ionization or cationic surface modification. While nanocarbons, given examples as carboxylic multi-walled carbon nanotubes, pristine single-walled carbon nanotube, and carbon nanotube–graphene oxide hybrid were negatively charged by the ionization of oxygen-containing functional groups or anionic surfactant. It was found that through the electrostatic interaction mechanism, all kinds of nanocarbons can be spontaneously and efficiently adsorbed onto the surface of various metal flakes. The development of such a versatile method would provide us great opportunities to fabricate advanced MMCs with appealing properties.

FLOCKING OF A THERMODYNAMIC CUCKER-SMALE MODEL WITH LOCAL VELOCITY INTERACTIONS

In this paper, we study the flocking behavior of a thermodynamic Cucker–Smale model with local velocity interactions. Using the spectral gap of a connected stochastic matrix, together with an elaborate estimate on perturbations of a linearized system, we provide a sufficient framework in terms of initial data and model parameters to guarantee flocking. Moreover, it is shown that the system achieves a consensus at an exponential rate.

Vibration analysis of fluid- structure interaction in water hammer based on transfer matrix method

In consideration of the problem that the effect of conduit structure on water hammer has been ignored in the classical theory,the Poisson coupling between the fluid and the pipeline was studied and a fourteen-equation mathematical model of fluid-structure interaction(FSI)was developed.Then,the transfer matrix method(TMM)was used to calculate the modal frequency,modal shape and frequency response.The results were compared with that in experiment to verify the correctness of the TMM and the results show that the fluid-structure coupling has a greater impact on the modal frequencies than the modal shape.Finally,the influence on the response spectrum of different damping ratios was studied and the results show that the natural frequency under different damping ratios has changed little but there is a big difference for the pressure spectrum.With the decreasing of damping ratio,the damping of the system on frequency spectrum is more and more significant and the dispersion and dissipation is more and more apparent.Therefore the appropriate damping ratio should be selected to minimize the effects of the vibration of the FSI.The results provide references for the theory research of FSI in the transient process.

INTERACTION OF PARTICLES WITH A SOLIDIFIED INTERFACE DURING SOLIDIFICATION OF METAL MATRIX COMPOSITE REINFORCED WITH PARTICLES

The interaction of particles with a solid-liquid interface during solidification of metal matrix composites has been investigated theoretically in this paper.Owing to the presence of particles in the melt,the shape of the solidification front and solute concentration field in front of solidification interface have been disturbed The thermodynamic method was employed,and a mathematical expression of the shape of the solidification interface and solute concentration field were deduced.Meanwhile,a theory is developed for evaluation of critical velocities of particles pushed by the solidification interface.A numerical simulation is done in which the critical velocity is evaluated as a function of particle size,thermal conductivity,diffusion coefficient,temperature gradient at the solidification front,the solid-liquid interfacial energy and the melt viscosity.The critical velocity is shown to be closely linked to the shape of the solidification interface and solute concentration field, and hence all the parameters also affect the shape of the solidification interface and solute concentration field of the front.

Effects of electrical resistance on the spontaneous combustion tendency of coal and the interaction matrix concept

There have been several developments in determining the spontaneous combustion liability of coal. Most of the methods of concern have purely been based on the internal properties of the coal itself. The relation between the crossing-point method and the electrical resistance of coal was examined here to outline the spontaneous combustion tendency of coal, The electrical resistance property of coal was looked into as a decision-making parameter of the interaction matrix concept for the final decision on the spontaneous combustion tendency.

Three-dimensional aspects of formulation excipients in drug discovery:a critical assessment on orphan excipients,matrix effects and drug interactions

Formulation/pharmaceutical excipients play a major role in formulating drug candidates,with the objectives of ease of administration,targeted delivery and complete availability.Many excipients used in pharmaceutical formulations are orphanized in preclinical drug discovery.These orphan excipients could enhance formulatability of highly lipophilic compounds.Additionally,they are safe in preclinical species when used below the LD50 values.However,when the excipients are used in formulating compounds with diverse physico-chemical properties,they pose challenges by modulating study results through their bioanalytical matrix effects.Excipients invariably present in study samples and not in the calibration curve standards cause over-/under-estimation of exposures.Thus,the mechanism by which excipients cause matrix effects and strategies to nullify these effects needs to be revisited.Furthermore,formulation excipients cause drug interactions by moderating the pathways of drug metabolizing enzymes and drug transport proteins.Although it is not possible to get rid of excipient driven interactions,it is always advised to be aware of these interactions and apply the knowledge to draw meaningful conclusions from study results.In this review,we will comprehensively discuss a)orphan excipients that have wider applications in preclinical formulations,b)bioanalytical matrix effects and possible approaches to mitigating these effects,and c)excipient driven drug interactions and strategies to alleviate the impacts of drug interactions.

The interaction of versican with its binding partners

Versican belongs to the family of the large aggregating chondroitin sulfate proteoglycans located primarily within the extracellular matrix （ECM）. Versican, like other members of its family, has unique N- and C-terminal globular regions, each with multiple motifs. A large glycosaminoglycan-binding region lies between them. This review will begin by outlining these structures, in the context of ECM proteoglycans. The diverse binding partners afforded to versican by virtue of its modular design will then be examined. These include ECM components, such as hyaluronan, type Ⅰ collagen, tenascin-R, fibulin-1, and -2, fibrillin-1, fibronectin, P- and L-selectins, and chemokines. Versican also binds to the cell surface proteins CD44, integrin β1, epidermal growth factor receptor, and P-selectin glycoprotein ligand-1. These multiple interactors play important roles in cell behaviour, and the roles of versican in modulating such processes are discussed.

A SEMI-ANALYTICAL AND SEMI-NUMERICAL METHOD FOR SOLVING 2-D SOUND-STRUCTURE INTERACTION PROBLEMS

Based on the transfer matrix method and the virtual source simulation technique, this paper proposes a novel semi-analytical and semi-numerical method for solving 2-D sound- structure interaction problems under a harmonic excitation.Within any integration segment, as long as its length is small enough,along the circumferential curvilinear coordinate,the non- homogeneous matrix differential equation of an elastic ring of complex geometrical shape can be rewritten in terms of the homogeneous one by the method of extended homogeneous capacity proposed in this paper.For the exterior fluid domain,the multi-circular virtual source simulation technique is adopted.The source density distributed on each virtual circular curve may be ex- panded as the Fourier's series.Combining with the inverse fast Fourier transformation,a higher accuracy and efficiency method for solving 2-D exterior Helmholtz's problems is presented in this paper.In the aspect of solution to the coupling equations,the state vectors of elastic ring induced by the given harmonic excitation and generalized forces of coefficients of the Fourier series can be obtained respectively by using a high precision integration scheme combined with the method of extended homogeneous capacity put forward in this paper.According to the superposition princi- ple and compatibility conditions at the interface between the elastic ring and fluid,the algebraic equation of system can be directly constructed by using the least square approximation.Examples of acoustic radiation from two typical fluid-loaded elastic rings under a harmonic concentrated force are presented.Numerical results show that the method proposed is more efficient than the mixed FE-BE method in common use.

Lattice Green's Function for Infinite Square Lattice in the Second Nearest-Neighbour Interaction Approximation

In dealing with the square lattice model,we replace the traditionally needed Born-Von Karmann periodic boundary condition with additional Hamiltonian terms to make up a ring lattice.In doing so,the lattice Green's function of an infinite square lattice in the second nearest-neighbour interaction approximation can be derived by means of the matrix Green's function method.It is shown that the density of states may change when the second nearest-neighbour interaction is turned on.

Modeling One Dimensional Two-Cell Model with Tumor Interaction Using Krylov Subspace Methods

A brain tumor occurs when abnormal cells grow, sometimes very rapidly, into an abnormal mass of tissue. The tumor can infect normal tissue, so there is an interaction between healthy and infected cell. The aim of this paper is to propose some efficient and accurate numerical methods for the computational solution of one-dimensional continuous basic models for the growth and control of brain tumors. After computing the analytical solution, we construct approximations of the solution to the problem using a standard second order finite difference method for space discretization and the Crank-Nicolson method for time discretization. Then, we investigate the convergence behavior of Conjugate gradient and generalized minimum residual as Krylov subspace methods to solve the tridiagonal toeplitz matrix system derived.

Accurate machine learning models based on small dataset of energetic materials through spatial matrix featurization methods

A large database is desired for machine learning(ML) technology to make accurate predictions of materials physicochemical properties based on their molecular structure.When a large database is not available,the development of proper featurization method based on physicochemical nature of target proprieties can improve the predictive power of ML models with a smaller database.In this work,we show that two new featurization methods,volume occupation spatial matrix and heat contribution spatial matrix,can improve the accuracy in predicting energetic materials' crystal density(ρ_(crystal)) and solid phase enthalpy of formation(H_(f,solid)) using a database containing 451 energetic molecules.Their mean absolute errors are reduced from 0.048 g/cm~3 and 24.67 kcal/mol to 0.035 g/cm~3 and 9.66 kcal/mol,respectively.By leave-one-out-cross-validation,the newly developed ML models can be used to determine the performance of most kinds of energetic materials except cubanes.Our ML models are applied to predict ρ_(crystal) and H_(f,solid) of CHON-based molecules of the 150 million sized PubChem database,and screened out 56 candidates with competitive detonation performance and reasonable chemical structures.With further improvement in future,spatial matrices have the potential of becoming multifunctional ML simulation tools that could provide even better predictions in wider fields of materials science.

An Ensemble Learning Recommender System for Interactive Platforms

In interactive platforms, we often want to predict which items could be more relevant for users, either based on their previous interactions with the system or their preferences. Such systems are called Recommender Systems. They are divided into three main groups, including content-based, collaborative and hybrid recommenders. In this paper, we focus on collaborative filtering and the improvement of the accuracy of its techniques. Then, we suggest an Ensemble Learning Recommender System model made of a probabilistic model and an efficient matrix factorization method. The interactions between users and the platform are scored by explicit and implicit scores. At each user session, implicit scores are used to train a probabilistic model to compute the maximum likelihood estimator for the probability that an item will be recommended in the next session. The explicit scores are used to know the impact of the user’s vote on an item at the time of the recommendation.

一种基于模型概率单调性变化的自适应IMM-UKF改进算法

针对现有交互式多模型(IMM)算法模型间切换迟滞和转换速率慢的缺点,提出一种基于模型概率单调性变化的自适应交互式多模型无迹卡尔曼滤波改进算法(mIMM-UKF)。该算法利用后验信息模型概率的单调性,对马尔可夫转移概率矩阵及模型估计概率进行二次修正,加快了匹配模型的切换速度及转换速率。仿真结果表明,与现有算法相比,该算法通过快速切换匹配模型,有效提高了水下目标跟踪精度。

用于夹层梁静动力及屈曲分析的新型组合结构单元

推导出新型组合结构单元,用于考虑界面滑移的3层部分作用夹层组合梁的静动力及屈曲特性分析.基于铁木辛柯梁理论,建立考虑夹层梁部分作用效应的能量原理.针对其受力特性,在节点位移、横截面转角和界面滑移插值时均采用含内部自由度的高阶插值函数,以解决含界面有限元数值分析中常遇到的“滑移锁定”现象.通过变分原理得到夹层梁的刚度矩阵、质量矩阵以及几何刚度矩阵的显示表达式.基于MATLAB编译相应夹层结构的有限元程序并验证其准确性.对不同截面3层夹层组合梁进行不同荷载条件和边界条件下的静动力及屈曲特性分析,并探讨不同夹层组合梁跨高比和不同界面抗剪连接刚度下的计算结果及其误差的变化规律.所推导的显示表达式新型组合结构单元计算效率高,并便于推广应用于其他有限元程序或商业软件子程序中.

卫生健康标准中关系型数据共现矩阵计算及SAS程序实现

目的设计卫生健康标准中关系型数据共现矩阵的求解路径及其SAS实现方法。方法文章以计算一组标准的起草单位共现矩阵为例,将“标准-起草单位”二维表格导入SAS(版本号:9.4),按照“两两相乘”的计算思路自行设计宏程序计算起草单位之间的共现矩阵。结果以计算一组标准的起草单位共现矩阵为例,采用自行构建的模拟数据进行演示。首先,导入宏循环起始的数据集,并计算共现频次C_(j,k);然后,导出为out数据集,进一步合并数据集,形成最终的共现矩阵。结论SAS宏程序计算标准中关系型数据共现矩阵具有灵活高效的优势,可用于社会网络分析和互动演进规律总结。

基于改进自适应IMM算法的高速列车组合定位

针对列车高精度定位问题,该文提出基于改进自适应交互多模型(IMM)的高速列车高精度组合定位方法。首先,根据列车定位需求和各传感器特点,设计了卫星接收器、轮轴测速传感器、测速雷达以及单轴陀螺仪4种传感器的组合定位方案。然后,针对IMM融合滤波算法因先验信息不准导致固定参数设置不当的问题,引入Sage-Husa自适应滤波和转移概率矩阵(TPM)自适应更新集成为自适应IMM算法。针对多模型切换的滞后问题,利用子模型似然函数值能快速反映模型变化趋势的特点,将似然函数值设为判定标志,并引入判定窗对TPM矩阵元素进行修正,有效提升了模型的切换速度。最后,基于改进自适应IMM算法对4种传感器定位信息进行融合滤波,实现高速列车的高精度组合定位。仿真结果表明:改进后的算法相比其他自适应IMM算法提升定位精度1.6%~14.7%,并且能通过提高模型间切换速度来有效降低位置误差峰值,同时具备较好的抗噪性能。

基于WSR-IM的装配式预制构件吊装施工安全评价

装配式建筑预制构件吊装施工相较于传统建筑吊装作业的施工安全风险更加具有多样性和复杂性,为准确有效的评估装配式建筑预制构件吊装施工的安全风险状态,识别出关键风险因素,在多因素耦合视角下构建预制构件吊装施工安全事故致因模型。基于施工单位责任视角,首先采用WSR方法论从“物理-事理-人理”三个层面识别并筛选出预制构件吊装施工安全风险影响因素20个,其次利用可以削弱主观因素影响的C-OWA算子构建改进相互作用矩阵进行风险耦合分析,最后用实例验证该方法实用性。结果表明:该项目整体风险等级偏强,项目管理者应该重视预制构件吊装风险的预防和管控,通过采取有效的防御措施,对施工过程中的高权重风险因素进行控制,降低发生重大安全事故的概率。

基于会话的独立邻域矩阵偏好交互推荐

通过合并输入和输出邻域矩阵可以使一些工作生成全局和局部偏好,并直接对这2个偏好建模来构建会话表示,从而实现改进。然而,一个会话的输入矩阵和输出矩阵并没有很强的相关性,它们的连接可能会为构建2个偏好引入噪声。其次,全局偏好和局部偏好可以相互促进,且邻域会话的协同信息可能有助于提高推荐性能。因此,一种基于会话的偏好交互推荐被提出,它来自独立的输入邻域矩阵和输出邻域矩阵框架,包括2个并行模块:输入会话表示编码器(ISE)和输出会话表示编码器(OSE)。ISE通过GNN和并行协同注意力机制对具有输入信息的会话表示进行建模。OSE通过GNN和并行协同注意力机制对具有输出信息的会话表示进行建模。最后,引入一种融合门控机制来平衡ISE和OSE产生的会话表示的重要性。结果表明,在Yoochoose和Diginetica数据集上,提出的模型明显优于其他先进的方法。

多因素耦合作用下的地铁施工渗漏水风险评价

针对多因素耦合作用下地铁盾构施工渗漏水灾害分析评价的模糊性和动态解释能力不足的问题,基于人、物、法、环4个维度构建地铁施工渗漏水风险评价指标体系;运用组合数有序加权算子(Combination Ordered Weighted Averaging,C-OWA)削弱主观因素影响建立相互作用矩阵,通过相互作用矩阵与模糊认知图的融合模型识别关键风险、预测演化趋势;在此基础上,基于可拓云物元理论构建了地铁盾构隧道渗漏水风险评价模型,并以某地铁隧道工程为例进行实证分析,结果表明,该盾构隧道施工渗漏水风险状态为安全,与实际情况相符,验证了该方法的可行性与适用性。该模型可为地铁盾构施工渗漏水风险评估与防范提供一种操作性强的方法。

基于域矩阵因子分解机的点击通过率预估增强网络

有效的特征交互,对于工业推荐系统中点击通过率(click-through-rate,CTR)预估的准确性起着至关重要的作用。以往并行结构的CTR预估模型通过将独立的浅层模型和深层模型并行连接,以此来学习特征的低阶交互和高阶交互。但是,这些模型存在浅层模型准确性低、未考虑特征交互时的多语义问题、参数过多、深层模型过度泛化等问题。基于上述问题,提出了一种基于域矩阵因子分解机的点击通过率预估增强网络,通过引入域矩阵优化浅层模型中的交互,提高运算效率,并在深层模型的DNN层与层之间增加了桥接模块,在每层高阶交互后增强对原始特征的记忆能力,将浅层模型和深层模型的结果相加并归一化得到预测值。该模型在Criteo、KKBox、Frappe和MovieLens数据集上进行了大量实验,展现了优秀的预测能力。