Micro-and nano-to millimeter-scale magnetic matrix materials have gained widespread application due to their exceptional magnetic properties and favorable cost-effectiveness.With the rapid progress in condensed matter...Micro-and nano-to millimeter-scale magnetic matrix materials have gained widespread application due to their exceptional magnetic properties and favorable cost-effectiveness.With the rapid progress in condensed matter physics,materials science,and mineral separation technologies,these materials are now poised for new opportunities in theoretical research and development.This review provides a comprehensive analysis of these matrices,encompassing their structure,size,shape,composition,properties,and multifaceted applications.These materials,primarily composed of alloys of transition state metasl such as iron(Fe),cobalt(Co),titanium(Ti),and nickel(Ni),exhibit unique attributes like high magnetization rates,low eleastic modulus,and high saturation magnetic field strengths.Furthermore,the studies also delve into the complex mechanical interactions involved in the separation of magnetic particles using magnetic separator matrices,including magnetic,gravitational,centrifugal,and van der Waals forces.The review outlines how size and shape effects influence the magnetic behavior of matrices,offering new perspectives for innovative applications of magnetic matrices in various domains of materials science and magnetic separation.展开更多
This study introduces a comprehensive theoretical framework for accurately calculating the electronic band-structure of strained long-wavelength InAs/GaSb type-Ⅱsuperlattices.Utilizing an eight-band k·p Hamilto⁃...This study introduces a comprehensive theoretical framework for accurately calculating the electronic band-structure of strained long-wavelength InAs/GaSb type-Ⅱsuperlattices.Utilizing an eight-band k·p Hamilto⁃nian in conjunction with a scattering matrix method,the model effectively incorporates quantum confinement,strain effects,and interface states.This robust and numerically stable approach achieves exceptional agreement with experimental data,offering a reliable tool for analyzing and engineering the band structure of complex multi⁃layer systems.展开更多
Basalt fibers/7075 aluminum matrix composites were studied to meet the demand of aluminum alloy drill pipes for material wear resistance.The composites with different basalt fiber additions were prepared by hot presse...Basalt fibers/7075 aluminum matrix composites were studied to meet the demand of aluminum alloy drill pipes for material wear resistance.The composites with different basalt fiber additions were prepared by hot pressed sintering and hot extrusion.The mechanical properties as well as friction and wear properties of the composites were studied by microstructure analysis,tensile experiments,friction and wear experiments.The results showed that basalt fibers were oriented and uniformly distributed and led to local grain refinement in the alloy matrix.The hardness and elongation of the composites were improved.The friction coefficient of the composites increased and then decreased,and the maximum wear depth and wear amount decreased,then increased,then decreased again with the growth of basalt fiber addition.Meanwhile,the inclusion of basalt fibers mitigated the uneven wear of the extruded 7075 aluminum alloy.The value of wear depth difference of 7075-0.2BF was the smallest,and that of 7075-2.0BF was close to it.The maximum wear depth and wear volume the 7075-0.2BF and 7075-2.0BF were also the smallest.The inhibition of uneven wear by basalt fibers enhanced of wear resistance for 7075 aluminum alloy,which has reference significance for improving the performance of aluminum alloy drill pipes.展开更多
With respect to the multiple attribute decision making problems with linguistic preference relations on alternatives in the form of incomplete linguistic judgment matrix, a method is proposed to analyze the decision p...With respect to the multiple attribute decision making problems with linguistic preference relations on alternatives in the form of incomplete linguistic judgment matrix, a method is proposed to analyze the decision problem. The incomplete linguistic judgment matrix is transformed into incomplete fuzzy judgment matrix and an optimization model is developed on the basis of incomplete fuzzy judgment matrix provided by the decision maker and the decision matrix to determine attribute weights by Lagrange multiplier method. Then the overall values of all alternatives are calculated to rank them. A numerical example is given to illustrate the feasibility and practicality of the proposed method.展开更多
To reduce the computational complexity of matrix inversion, which is the majority of processing in many practical applications, two numerically efficient recursive algorithms （called algorithms I and II, respectively...To reduce the computational complexity of matrix inversion, which is the majority of processing in many practical applications, two numerically efficient recursive algorithms （called algorithms I and II, respectively） are presented. Algorithm I is used to calculate the inverse of such a matrix, whose leading principal minors are all nonzero. Algorithm II, whereby, the inverse of an arbitrary nonsingular matrix can be evaluated is derived via improving the algorithm I. The implementation, for algorithm II or I, involves matrix-vector multiplications and vector outer products. These operations are computationally fast and highly parallelizable. MATLAB simulations show that both recursive algorithms are valid.展开更多
Most existing network representation learning algorithms focus on network structures for learning.However,network structure is only one kind of view and feature for various networks,and it cannot fully reflect all cha...Most existing network representation learning algorithms focus on network structures for learning.However,network structure is only one kind of view and feature for various networks,and it cannot fully reflect all characteristics of networks.In fact,network vertices usually contain rich text information,which can be well utilized to learn text-enhanced network representations.Meanwhile,Matrix-Forest Index(MFI)has shown its high effectiveness and stability in link prediction tasks compared with other algorithms of link prediction.Both MFI and Inductive Matrix Completion(IMC)are not well applied with algorithmic frameworks of typical representation learning methods.Therefore,we proposed a novel semi-supervised algorithm,tri-party deep network representation learning using inductive matrix completion(TDNR).Based on inductive matrix completion algorithm,TDNR incorporates text features,the link certainty degrees of existing edges and the future link probabilities of non-existing edges into network representations.The experimental results demonstrated that TFNR outperforms other baselines on three real-world datasets.The visualizations of TDNR show that proposed algorithm is more discriminative than other unsupervised approaches.展开更多
基金Project(52174245)supported by the National Natural Science Foundation of ChinaProject(2021J01640)supported by the Natural Science Foundation of Fujian Province,ChinaProject(BGRIMM-KJSKL2022-03)supported by Open Foundation of the State Key Laboratory of Mineral Processing,China。
文摘Micro-and nano-to millimeter-scale magnetic matrix materials have gained widespread application due to their exceptional magnetic properties and favorable cost-effectiveness.With the rapid progress in condensed matter physics,materials science,and mineral separation technologies,these materials are now poised for new opportunities in theoretical research and development.This review provides a comprehensive analysis of these matrices,encompassing their structure,size,shape,composition,properties,and multifaceted applications.These materials,primarily composed of alloys of transition state metasl such as iron(Fe),cobalt(Co),titanium(Ti),and nickel(Ni),exhibit unique attributes like high magnetization rates,low eleastic modulus,and high saturation magnetic field strengths.Furthermore,the studies also delve into the complex mechanical interactions involved in the separation of magnetic particles using magnetic separator matrices,including magnetic,gravitational,centrifugal,and van der Waals forces.The review outlines how size and shape effects influence the magnetic behavior of matrices,offering new perspectives for innovative applications of magnetic matrices in various domains of materials science and magnetic separation.
文摘This study introduces a comprehensive theoretical framework for accurately calculating the electronic band-structure of strained long-wavelength InAs/GaSb type-Ⅱsuperlattices.Utilizing an eight-band k·p Hamilto⁃nian in conjunction with a scattering matrix method,the model effectively incorporates quantum confinement,strain effects,and interface states.This robust and numerically stable approach achieves exceptional agreement with experimental data,offering a reliable tool for analyzing and engineering the band structure of complex multi⁃layer systems.
基金Project(2021YFC2900200)supported by the National Key Research and Development Project of ChinaProject(20230203114SF)supported by the Key Research and Development Project of Jilin Province,China。
文摘Basalt fibers/7075 aluminum matrix composites were studied to meet the demand of aluminum alloy drill pipes for material wear resistance.The composites with different basalt fiber additions were prepared by hot pressed sintering and hot extrusion.The mechanical properties as well as friction and wear properties of the composites were studied by microstructure analysis,tensile experiments,friction and wear experiments.The results showed that basalt fibers were oriented and uniformly distributed and led to local grain refinement in the alloy matrix.The hardness and elongation of the composites were improved.The friction coefficient of the composites increased and then decreased,and the maximum wear depth and wear amount decreased,then increased,then decreased again with the growth of basalt fiber addition.Meanwhile,the inclusion of basalt fibers mitigated the uneven wear of the extruded 7075 aluminum alloy.The value of wear depth difference of 7075-0.2BF was the smallest,and that of 7075-2.0BF was close to it.The maximum wear depth and wear volume the 7075-0.2BF and 7075-2.0BF were also the smallest.The inhibition of uneven wear by basalt fibers enhanced of wear resistance for 7075 aluminum alloy,which has reference significance for improving the performance of aluminum alloy drill pipes.
基金the National Natural Science Foundation of China (70701008)National Science Foundationfor Distinguished Young Scholars of China (70525002)
文摘With respect to the multiple attribute decision making problems with linguistic preference relations on alternatives in the form of incomplete linguistic judgment matrix, a method is proposed to analyze the decision problem. The incomplete linguistic judgment matrix is transformed into incomplete fuzzy judgment matrix and an optimization model is developed on the basis of incomplete fuzzy judgment matrix provided by the decision maker and the decision matrix to determine attribute weights by Lagrange multiplier method. Then the overall values of all alternatives are calculated to rank them. A numerical example is given to illustrate the feasibility and practicality of the proposed method.
文摘To reduce the computational complexity of matrix inversion, which is the majority of processing in many practical applications, two numerically efficient recursive algorithms （called algorithms I and II, respectively） are presented. Algorithm I is used to calculate the inverse of such a matrix, whose leading principal minors are all nonzero. Algorithm II, whereby, the inverse of an arbitrary nonsingular matrix can be evaluated is derived via improving the algorithm I. The implementation, for algorithm II or I, involves matrix-vector multiplications and vector outer products. These operations are computationally fast and highly parallelizable. MATLAB simulations show that both recursive algorithms are valid.
基金Projects(11661069,61763041) supported by the National Natural Science Foundation of ChinaProject(IRT_15R40) supported by Changjiang Scholars and Innovative Research Team in University,ChinaProject(2017TS045) supported by the Fundamental Research Funds for the Central Universities,China
文摘Most existing network representation learning algorithms focus on network structures for learning.However,network structure is only one kind of view and feature for various networks,and it cannot fully reflect all characteristics of networks.In fact,network vertices usually contain rich text information,which can be well utilized to learn text-enhanced network representations.Meanwhile,Matrix-Forest Index(MFI)has shown its high effectiveness and stability in link prediction tasks compared with other algorithms of link prediction.Both MFI and Inductive Matrix Completion(IMC)are not well applied with algorithmic frameworks of typical representation learning methods.Therefore,we proposed a novel semi-supervised algorithm,tri-party deep network representation learning using inductive matrix completion(TDNR).Based on inductive matrix completion algorithm,TDNR incorporates text features,the link certainty degrees of existing edges and the future link probabilities of non-existing edges into network representations.The experimental results demonstrated that TFNR outperforms other baselines on three real-world datasets.The visualizations of TDNR show that proposed algorithm is more discriminative than other unsupervised approaches.
