Edible bird's nest(EBN),abundant in sialic acid(SA)has been recognized as a natural substance beneficial to brain development and cognitive ability.In order to investigate active component of EBN,sialylated glycop...Edible bird's nest(EBN),abundant in sialic acid(SA)has been recognized as a natural substance beneficial to brain development and cognitive ability.In order to investigate active component of EBN,sialylated glycopeptides(SCP)were extracted from EBN by 60%ethanol after trypsin hydrolysis and its effects on central nervous system was evaluated in lipopolysaccharide(LPS)-induced neuroinflammation mice.EBN,SCP,and SA pretreatment and intervention reduced interleukin-1β(IL-1β),tumor necrosis factor-α(TNF-α),and interleukin-6(IL-6)levels in hippocampus and cortex,meanwhile inhibited the activation of microglia,astrogliosis and neuron apoptosis,which were consistent with the learning and memory improvement and anti-depression effects in behavioral tests.The counts of leukocytes,neutrophils and monocytes,as well as IL-1β,TNF-α,and IL-6 levels in peripheral circulation were significantly reduced by SCP.Results of plasma metabolomics suggested SCP up-regulated energy metabolism,promoted the recovery of primary and secondary bile acid metabolism and indole metabolism,where microbiota may involve.16S rDNA sequencing of colonic contents showed EBN,SCP and SA repaired dysbacteriosis in LPS-treated mice by significantly up-regulating the anti-inflammatory Muribaculaceae and inhibiting pro-inflammatory related Desulfovibrio and Candidatus_Saccharimonas.In addition,both EBN and SCP could significantly enrich Aerococcus,while SA could specifically enrich Prevotellaceae_UCG_001.The gut-brain axis was preliminarily established,and SCP may have the potential to be a functional factor for neuroprotection applied in EBN industry.展开更多
The intricate relationship between origami and mechanism underscores the fertile ground for innovation,which is particularly evident in the construction theory of thick-panel origami.Despite its potential,thick panel ...The intricate relationship between origami and mechanism underscores the fertile ground for innovation,which is particularly evident in the construction theory of thick-panel origami.Despite its potential,thick panel origami remains relatively unexplored in the context of single-loop metamorphic mechanisms.Drawing inspiration from thickpanel origami,particularly Miura origami,this study proposes a pioneering single-loop 6R multiple metamorphic mechanism.Through rigorous mathematical modeling(including the construction and resolution of the D-H closed-loop equation)and leveraging advanced analytical tools such as the screw theory and Lie theory,this study meticulously elucidates the planar,spherical,and Bennett motion branches of the mechanism.Furthermore,it delineates all the three bifurcation points between the motion branches,thereby providing a comprehensive understanding of the kinematic behavior of the mechanism.A metamorphic network can be constructed by applying several single-loop mechanisms to a symmetrical layout.Owing to its metamorphic properties,this network can act as a structural backbone for deployable antennas,aerospace shelters,and morphing wing units,thereby enabling a single mechanism to achieve multiple folding configurations.This paper not only introduces innovative metamorphic mechanisms but also suggests a promising method for uncovering and designing metamorphic mechanisms by developing new mechanisms from thick-panel origami.展开更多
The voltage stability is substantially a dynamic stability, but the primary method which is more mature and engineering practical to analyze the stability of voltage is still static analysis. The time-domain simulatio...The voltage stability is substantially a dynamic stability, but the primary method which is more mature and engineering practical to analyze the stability of voltage is still static analysis. The time-domain simulation is an important measure in research of complex power grid. With the development of full dynamic simulation technology, the research of dynamic voltage stability by using full dynamic simulation program which is based on time-domain simulation can be carried out. This paper uses full dynamic simulation program in dynamic voltage stability research, lays special stress on research in how generator over-excitation limiter functioned and influence in dynamic voltage stability research, and raise 2 methods and steps to figure out dynamic stable voltage in both over-excitation counted and not counted. The simulation results of examples indicate the correctness and effectiveness of these methods, and also fully verify the function and influence of generator over-excitation limiter in full dynamic voltage stability research.展开更多
The ongoing energy transition,essential for mitigating global warming,stands to benefit significantly from advances in building energy consumption prediction.With the rise of big data,data-driven models have become in...The ongoing energy transition,essential for mitigating global warming,stands to benefit significantly from advances in building energy consumption prediction.With the rise of big data,data-driven models have become increasingly effective in forecasting,with machine learning emerging as the most efficient method for constructing these predictive models.While previous reviews have typically listed various machine learning models for energy consumption prediction,they have often lacked a theoretical perspective explaining why certain models are suitable for different aspects of this domain.In contrast,this review introduces machine learning techniques based on their application phases,covering preprocessing techniques such as feature selection,extraction,and clustering,as well as state-of-the-art predictive models.We provide a comparative theoretical analysis of various models,examining their strengths,weaknesses,and suitability for different forecasting tasks.Additionally,we discuss spatial-temporal considerations in energy consumption forecasting,including the role of Graph Neural Networks and multitask learning.Furthermore,we address a significant challenge in the field,the difficulty of accurately predicting high-fluctuation electricity consumption,and propose potential solutions to tackle this issue.展开更多
Multi-component transition metal carbides(MTMCs)have garnered significant attention for their out-standing high-temperature stability and versatile properties,which make them ideal candidates for a wide range of indus...Multi-component transition metal carbides(MTMCs)have garnered significant attention for their out-standing high-temperature stability and versatile properties,which make them ideal candidates for a wide range of industrial applications.However,the underlying mechanisms governing the crystal growth and morphological evolution of MTMCs remain poorly understood,hindering the design of materials with tailored characteristics.In this paper,we employ an in-situ liquid-solid reaction method to synthesize(HfTaZrNbTi)C MTMC powders and explore their crystal growth and morphology evolution.The synthesized(TiZrHfNbTa)C powders exhibit two distinct morphologies:cubic,primarily composed of Ti,Hf,Ta,and Zr with a small amount of Nb,and octahedral,rich in Ti and Ta with minor amounts of Hf,Nb,and Zr.First-principles calculations show that the surface energy of the(100)plane is lower than the(111)plane,leading to the formation of the cubic morphology.The octahedral morphology forms due to decreased mixing entropy and higher theoretical density compared to cubic particles.Our findings provide valuable insights into the crystal growth and morphology evolution mechanisms of high-entropy ceramics,contributing to the rational design of MTMCs with engineered crystal structures for diverse structural and functional applications.展开更多
基金funded by Central Nervous System Product Research and Development Key Laboratory of Sichuan Province(230048-01SZ).
文摘Edible bird's nest(EBN),abundant in sialic acid(SA)has been recognized as a natural substance beneficial to brain development and cognitive ability.In order to investigate active component of EBN,sialylated glycopeptides(SCP)were extracted from EBN by 60%ethanol after trypsin hydrolysis and its effects on central nervous system was evaluated in lipopolysaccharide(LPS)-induced neuroinflammation mice.EBN,SCP,and SA pretreatment and intervention reduced interleukin-1β(IL-1β),tumor necrosis factor-α(TNF-α),and interleukin-6(IL-6)levels in hippocampus and cortex,meanwhile inhibited the activation of microglia,astrogliosis and neuron apoptosis,which were consistent with the learning and memory improvement and anti-depression effects in behavioral tests.The counts of leukocytes,neutrophils and monocytes,as well as IL-1β,TNF-α,and IL-6 levels in peripheral circulation were significantly reduced by SCP.Results of plasma metabolomics suggested SCP up-regulated energy metabolism,promoted the recovery of primary and secondary bile acid metabolism and indole metabolism,where microbiota may involve.16S rDNA sequencing of colonic contents showed EBN,SCP and SA repaired dysbacteriosis in LPS-treated mice by significantly up-regulating the anti-inflammatory Muribaculaceae and inhibiting pro-inflammatory related Desulfovibrio and Candidatus_Saccharimonas.In addition,both EBN and SCP could significantly enrich Aerococcus,while SA could specifically enrich Prevotellaceae_UCG_001.The gut-brain axis was preliminarily established,and SCP may have the potential to be a functional factor for neuroprotection applied in EBN industry.
基金Supported by National Natural Science Foundation of China(Grant Nos.52192634,52305015,52335003)Guangdong Basic and Applied Basic Research Foundation(Grant No.2023A1515011268)Science and Technology Innovation Committee of Shenzhen(Grant Nos.GXWD20231129102029003,KQTD20210811090146075).
文摘The intricate relationship between origami and mechanism underscores the fertile ground for innovation,which is particularly evident in the construction theory of thick-panel origami.Despite its potential,thick panel origami remains relatively unexplored in the context of single-loop metamorphic mechanisms.Drawing inspiration from thickpanel origami,particularly Miura origami,this study proposes a pioneering single-loop 6R multiple metamorphic mechanism.Through rigorous mathematical modeling(including the construction and resolution of the D-H closed-loop equation)and leveraging advanced analytical tools such as the screw theory and Lie theory,this study meticulously elucidates the planar,spherical,and Bennett motion branches of the mechanism.Furthermore,it delineates all the three bifurcation points between the motion branches,thereby providing a comprehensive understanding of the kinematic behavior of the mechanism.A metamorphic network can be constructed by applying several single-loop mechanisms to a symmetrical layout.Owing to its metamorphic properties,this network can act as a structural backbone for deployable antennas,aerospace shelters,and morphing wing units,thereby enabling a single mechanism to achieve multiple folding configurations.This paper not only introduces innovative metamorphic mechanisms but also suggests a promising method for uncovering and designing metamorphic mechanisms by developing new mechanisms from thick-panel origami.
文摘The voltage stability is substantially a dynamic stability, but the primary method which is more mature and engineering practical to analyze the stability of voltage is still static analysis. The time-domain simulation is an important measure in research of complex power grid. With the development of full dynamic simulation technology, the research of dynamic voltage stability by using full dynamic simulation program which is based on time-domain simulation can be carried out. This paper uses full dynamic simulation program in dynamic voltage stability research, lays special stress on research in how generator over-excitation limiter functioned and influence in dynamic voltage stability research, and raise 2 methods and steps to figure out dynamic stable voltage in both over-excitation counted and not counted. The simulation results of examples indicate the correctness and effectiveness of these methods, and also fully verify the function and influence of generator over-excitation limiter in full dynamic voltage stability research.
文摘The ongoing energy transition,essential for mitigating global warming,stands to benefit significantly from advances in building energy consumption prediction.With the rise of big data,data-driven models have become increasingly effective in forecasting,with machine learning emerging as the most efficient method for constructing these predictive models.While previous reviews have typically listed various machine learning models for energy consumption prediction,they have often lacked a theoretical perspective explaining why certain models are suitable for different aspects of this domain.In contrast,this review introduces machine learning techniques based on their application phases,covering preprocessing techniques such as feature selection,extraction,and clustering,as well as state-of-the-art predictive models.We provide a comparative theoretical analysis of various models,examining their strengths,weaknesses,and suitability for different forecasting tasks.Additionally,we discuss spatial-temporal considerations in energy consumption forecasting,including the role of Graph Neural Networks and multitask learning.Furthermore,we address a significant challenge in the field,the difficulty of accurately predicting high-fluctuation electricity consumption,and propose potential solutions to tackle this issue.
基金supported by the National Natural Science Foun-dation of China(Nos.U24A2026 and52271033)the Natural Science Foundation of Jiangsu Province,China(No.BK20221493).
文摘Multi-component transition metal carbides(MTMCs)have garnered significant attention for their out-standing high-temperature stability and versatile properties,which make them ideal candidates for a wide range of industrial applications.However,the underlying mechanisms governing the crystal growth and morphological evolution of MTMCs remain poorly understood,hindering the design of materials with tailored characteristics.In this paper,we employ an in-situ liquid-solid reaction method to synthesize(HfTaZrNbTi)C MTMC powders and explore their crystal growth and morphology evolution.The synthesized(TiZrHfNbTa)C powders exhibit two distinct morphologies:cubic,primarily composed of Ti,Hf,Ta,and Zr with a small amount of Nb,and octahedral,rich in Ti and Ta with minor amounts of Hf,Nb,and Zr.First-principles calculations show that the surface energy of the(100)plane is lower than the(111)plane,leading to the formation of the cubic morphology.The octahedral morphology forms due to decreased mixing entropy and higher theoretical density compared to cubic particles.Our findings provide valuable insights into the crystal growth and morphology evolution mechanisms of high-entropy ceramics,contributing to the rational design of MTMCs with engineered crystal structures for diverse structural and functional applications.
