As a fundamental parameter of the optical crystals,birefringence plays a vital role in many optical applications,such as phase modulation,light splitting,and polarization,especially the phase matching process of the n...As a fundamental parameter of the optical crystals,birefringence plays a vital role in many optical applications,such as phase modulation,light splitting,and polarization,especially the phase matching process of the nonlinear optical crystals.The big birefringence not only benefits to the miniaturization of related devices,but also broadens the phase-matching wavelength range of nonlinear optical crystals.The design and synthesis of crystals with large birefringence becomes a hot research topic due to its more and more important applications in the optical modulation and laser technology fields.Herein,crystals with birefringence greater than 0.05 in the borate system are reviewed and classified according to different birefringent active groups,and the relationship between structure and properties is thoroughly explored.It is hoped that this review will provide a clear understanding of what kinds of building units and arrangements would have more opportunity to get adequate birefringence in borate systems and provide the statistical references to encourage the emergence of better crystal materials with large birefringence.展开更多
Discovering regularities between entities in temporal graphs is vital for many real-world applications(e.g.,social recommendation,emergency event detection,and cyberattack event detection).This paper proposes temporal...Discovering regularities between entities in temporal graphs is vital for many real-world applications(e.g.,social recommendation,emergency event detection,and cyberattack event detection).This paper proposes temporal graph association rules(TGARs)that extend traditional graph-pattern association rules in a static graph by incorporating the unique temporal information and constraints.We introduce quality measures(e.g.,support,confidence,and diversification)to characterize meaningful TGARs that are useful and diversified.In addition,the proposed support metric is an upper bound for alternative metrics,allowing us to guarantee a superset of patterns.We extend conventional confidence measures in terms of maximal occurrences of TGARs.The diversification score strikes a balance between interestingness and diversity.Although the problem is NP-hard,we develop an effective discovery algorithm for TGARs that integrates TGARs generation and TGARs selection and shows that mining TGARs is feasible over a temporal graph.We propose pruning strategies to filter TGARs that have low support or cannot make top-k as early as possible.Moreover,we design an auxiliary data structure to prune the TGARs that do not meet the constraints during the TGARs generation process to avoid conducting repeated subgraph matching for each extension in the search space.We experimentally verify the effectiveness,efficiency,and scalability of our algorithms in discovering diversified top-k TGARs from temporal graphs in real-life applications.展开更多
基金supported by Shanghai Cooperation Organization Science and Technology Partnership Program(2020E01039)the Scientific Instrument Developing Project,CAS(YJKYYQ20210033)+3 种基金CAS Youth Interdisciplinary Team(JCTD-2021–18)the West Light Foundation of CAS(2021-XBQNXZ-004)the Outstanding Youth Science Fund Project of Natural Science Foundation of Xinjiang(2022D01E90)Key Training Object of Talent Project of Urumqi。
文摘As a fundamental parameter of the optical crystals,birefringence plays a vital role in many optical applications,such as phase modulation,light splitting,and polarization,especially the phase matching process of the nonlinear optical crystals.The big birefringence not only benefits to the miniaturization of related devices,but also broadens the phase-matching wavelength range of nonlinear optical crystals.The design and synthesis of crystals with large birefringence becomes a hot research topic due to its more and more important applications in the optical modulation and laser technology fields.Herein,crystals with birefringence greater than 0.05 in the borate system are reviewed and classified according to different birefringent active groups,and the relationship between structure and properties is thoroughly explored.It is hoped that this review will provide a clear understanding of what kinds of building units and arrangements would have more opportunity to get adequate birefringence in borate systems and provide the statistical references to encourage the emergence of better crystal materials with large birefringence.
基金This work was partially supported by the National Key Research and Development Program(No.2018YFB1800203)National Natural Science Foundation of China(No.U19B2024)Postgraduate Scientific Research Innovation Project of Hunan Province(No.CX20210038).
文摘Discovering regularities between entities in temporal graphs is vital for many real-world applications(e.g.,social recommendation,emergency event detection,and cyberattack event detection).This paper proposes temporal graph association rules(TGARs)that extend traditional graph-pattern association rules in a static graph by incorporating the unique temporal information and constraints.We introduce quality measures(e.g.,support,confidence,and diversification)to characterize meaningful TGARs that are useful and diversified.In addition,the proposed support metric is an upper bound for alternative metrics,allowing us to guarantee a superset of patterns.We extend conventional confidence measures in terms of maximal occurrences of TGARs.The diversification score strikes a balance between interestingness and diversity.Although the problem is NP-hard,we develop an effective discovery algorithm for TGARs that integrates TGARs generation and TGARs selection and shows that mining TGARs is feasible over a temporal graph.We propose pruning strategies to filter TGARs that have low support or cannot make top-k as early as possible.Moreover,we design an auxiliary data structure to prune the TGARs that do not meet the constraints during the TGARs generation process to avoid conducting repeated subgraph matching for each extension in the search space.We experimentally verify the effectiveness,efficiency,and scalability of our algorithms in discovering diversified top-k TGARs from temporal graphs in real-life applications.
