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, Available online ,
doi: 10.12202/j.0476-0301.20203073
Abstract:
In recent years, the emergence of non-fullerene organic small molecule acceptors has promoted the vigorous development of organic solar cell. However, the photophysical mechanism of non-fullerene organic small molecule acceptors and the photoelectric conversion mechanism of organic solar cell based on them are still unclear, which seriously hampers the efficient development of high-performance organic solar cell. This article briefly introduces the progress of our group in the study on the carrier dynamics in the acceptor materials of organic solar cell in recent years. Through studying the effects of terminal group engineering, side chain engineering and blonkbone engineering on the carrier dynamics of small molecule acceptors, we build a structure-dynamics-device performance relationship to promote the further development of organic solar cell.
In recent years, the emergence of non-fullerene organic small molecule acceptors has promoted the vigorous development of organic solar cell. However, the photophysical mechanism of non-fullerene organic small molecule acceptors and the photoelectric conversion mechanism of organic solar cell based on them are still unclear, which seriously hampers the efficient development of high-performance organic solar cell. This article briefly introduces the progress of our group in the study on the carrier dynamics in the acceptor materials of organic solar cell in recent years. Through studying the effects of terminal group engineering, side chain engineering and blonkbone engineering on the carrier dynamics of small molecule acceptors, we build a structure-dynamics-device performance relationship to promote the further development of organic solar cell.
, Available online ,
doi: 10.12202/j.0476-0301.2023137
Abstract:
The main ecological function water conservation in the upper reaches of the Yellow River in Sichuan is faced with severe challenges due to the influence of climate change and human activities. Building a reasonable ecological security pattern based on ecological network is an effective measure to improve the water conservation function in this region. Based on the assessment of the water conservation function and restoration potential of the upper Yellow River in Sichuan, this study used the morphological spatial pattern analysis (MSPA) to identify the ecological source area of the upper Yellow River in Sichuan, and used the minimum cumulative resistance model to identify the ecological corridor. The results showed that the water conservation capacity of the entire study area gradually decreased from south to north, and the areas with high potential for water conservation restoration were mainly distributed in the northern part of the study area. The core area identified by MSPA is mainly located in Ruoergai County and Shiqu County, accounting for 44.04% of the total area. The ecological security pattern of the upper Yellow River in Sichuan consisted of three levels of ecological source area and three levels of ecological corridor. The entire ecological network is concentrated in the north central part of the study area, while the ecological networks in the east, west and south are less distributed. The construction of ecological security pattern based on ecological network can provide an important basis for the ecological restoration layout of water conservation in Sichuan section of the upper Yellow River.
The main ecological function water conservation in the upper reaches of the Yellow River in Sichuan is faced with severe challenges due to the influence of climate change and human activities. Building a reasonable ecological security pattern based on ecological network is an effective measure to improve the water conservation function in this region. Based on the assessment of the water conservation function and restoration potential of the upper Yellow River in Sichuan, this study used the morphological spatial pattern analysis (MSPA) to identify the ecological source area of the upper Yellow River in Sichuan, and used the minimum cumulative resistance model to identify the ecological corridor. The results showed that the water conservation capacity of the entire study area gradually decreased from south to north, and the areas with high potential for water conservation restoration were mainly distributed in the northern part of the study area. The core area identified by MSPA is mainly located in Ruoergai County and Shiqu County, accounting for 44.04% of the total area. The ecological security pattern of the upper Yellow River in Sichuan consisted of three levels of ecological source area and three levels of ecological corridor. The entire ecological network is concentrated in the north central part of the study area, while the ecological networks in the east, west and south are less distributed. The construction of ecological security pattern based on ecological network can provide an important basis for the ecological restoration layout of water conservation in Sichuan section of the upper Yellow River.
, Available online ,
doi: 10.12202/j.0476-0301.2023072
Abstract:
Weyl semimetal is a novel topological quantum state with emergent relativistic Weyl fermions of opposite chiralities and surface Fermi arcs in the electronic structure. Such distinct electronic structure leads to many exotic physical properties, such as chiral anomaly and quantum oscillations. Based on the symmetry broken, Weyl semimetal can be classified as inversion symmetry breaking non-magnetic Weyl semimetal and time-reversal symmetry breaking magnetic Weyl semimetal. The latter is very sensitive to the magnetic structure so that the manipulation of the topological phase transition and the physical properties can be induced by external magnetic or electric field, that has great potential applications in the field of spintronics. The Kagome ferromagnet Co3Sn2S2 is the first experimentally discovered magnetic Weyl semimetal. We review its discovery in this paper including the transport properties, theoretical calculations and measurements of the electronic structure. We also discuss the prospects on the study of the magnetic semimetal in the end.
Weyl semimetal is a novel topological quantum state with emergent relativistic Weyl fermions of opposite chiralities and surface Fermi arcs in the electronic structure. Such distinct electronic structure leads to many exotic physical properties, such as chiral anomaly and quantum oscillations. Based on the symmetry broken, Weyl semimetal can be classified as inversion symmetry breaking non-magnetic Weyl semimetal and time-reversal symmetry breaking magnetic Weyl semimetal. The latter is very sensitive to the magnetic structure so that the manipulation of the topological phase transition and the physical properties can be induced by external magnetic or electric field, that has great potential applications in the field of spintronics. The Kagome ferromagnet Co3Sn2S2 is the first experimentally discovered magnetic Weyl semimetal. We review its discovery in this paper including the transport properties, theoretical calculations and measurements of the electronic structure. We also discuss the prospects on the study of the magnetic semimetal in the end.
, Available online ,
doi: 10.12202/j.0476-0301.2023198
Abstract:
Order-parameter theory of self-organized synchronization in complex systems is proposed. Low-dimensional dynamical equations of order parameters are derived in terms of dimension reduction schemes such as the Ott-Antonsen ansatz. The mechanisms, forms, and manifestations of the emergence of synchronization are explored at both microscopic and macroscopic levels. Order parameter dynamics of synchronization in heterogeneously coupled oscillators are investigated. It is found that coupling heterogeneity may induce the Bellerophon state. Explosive desynchronization transitions are revealed in coupled oscillators with multiplex network topologies, and these transition are irreversible. Synchronization dynamics are studied for oscillators with nonlinear couplings. Various transitions and scaling relations are investigated at the onset of synchronization. Three types of transitions, i.e., explosive, continuous and hybrid synchronizations, are identified. These studies shed light on both theoretical understandings and potential applications of collective behaviors in complex systems.
Order-parameter theory of self-organized synchronization in complex systems is proposed. Low-dimensional dynamical equations of order parameters are derived in terms of dimension reduction schemes such as the Ott-Antonsen ansatz. The mechanisms, forms, and manifestations of the emergence of synchronization are explored at both microscopic and macroscopic levels. Order parameter dynamics of synchronization in heterogeneously coupled oscillators are investigated. It is found that coupling heterogeneity may induce the Bellerophon state. Explosive desynchronization transitions are revealed in coupled oscillators with multiplex network topologies, and these transition are irreversible. Synchronization dynamics are studied for oscillators with nonlinear couplings. Various transitions and scaling relations are investigated at the onset of synchronization. Three types of transitions, i.e., explosive, continuous and hybrid synchronizations, are identified. These studies shed light on both theoretical understandings and potential applications of collective behaviors in complex systems.
, Available online ,
doi: 10.12202/j.0476-0301.2022057
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Poverty is a long-term dilemma faced by mankind. Exploring the ecological poverty reduction model is an important way to protect the ecological environment and effectively prevent poverty return. Taking the poor groups in the Matsutake Industrial Park in Yajiang County as the research object, this paper constructs an Ecological Multidimensional Poverty Reduction Index Evaluation System based on emergy analysis method, evaluates the changes of ecosystem services and poverty reduction in the living areas of poor households before and after entering the park, and evaluates the sustainability of the industrial poverty reduction model. The results show that the edible fungus industry system has a longer-term sustainable development than the farmland system, has a higher emergy of supply services and cultural services, and its poverty reduction ability has been improved to varying degrees. In addition, under the condition of using the same ecosystem services, the stronger the poverty reduction ability provided by the edible fungus industry system, and its comprehensive ecological poverty reduction ability is stronger than the farmland system. To a certain extent, realize the concept of “Clear waters and green mountains are as good as mountains of gold and silver.”
Poverty is a long-term dilemma faced by mankind. Exploring the ecological poverty reduction model is an important way to protect the ecological environment and effectively prevent poverty return. Taking the poor groups in the Matsutake Industrial Park in Yajiang County as the research object, this paper constructs an Ecological Multidimensional Poverty Reduction Index Evaluation System based on emergy analysis method, evaluates the changes of ecosystem services and poverty reduction in the living areas of poor households before and after entering the park, and evaluates the sustainability of the industrial poverty reduction model. The results show that the edible fungus industry system has a longer-term sustainable development than the farmland system, has a higher emergy of supply services and cultural services, and its poverty reduction ability has been improved to varying degrees. In addition, under the condition of using the same ecosystem services, the stronger the poverty reduction ability provided by the edible fungus industry system, and its comprehensive ecological poverty reduction ability is stronger than the farmland system. To a certain extent, realize the concept of “Clear waters and green mountains are as good as mountains of gold and silver.”
, Available online ,
doi: 10.12202/j.0476-0301.2023081
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The extrordinary optical performance of microbubble based optofliudic sensors makes it highly concerned in the field of microfliudic detection. However, the transport of analytes into the sensing surface is still lack of studies. In this papper, combining of theoretical analysis and finite-element-method simulation, the microfluidic transport inside the optofluidic sensors is systemetically studied. We found that the diffusion limited adsorption speed can be enhanced via the tapered capillary and microbubbles, which helps further optimization of those microfluidic sensors.
The extrordinary optical performance of microbubble based optofliudic sensors makes it highly concerned in the field of microfliudic detection. However, the transport of analytes into the sensing surface is still lack of studies. In this papper, combining of theoretical analysis and finite-element-method simulation, the microfluidic transport inside the optofluidic sensors is systemetically studied. We found that the diffusion limited adsorption speed can be enhanced via the tapered capillary and microbubbles, which helps further optimization of those microfluidic sensors.
, Available online ,
doi: 10.12202/j.0476-0301.2023195
Abstract:
First principle study reveals the stability or metastability of neon reactivity with ionic compounds at high pressure. The stability driven factor is reduction of long range Coulomb energy of the lattice. To verify this conclusion, neon was mixed with sodium oxide, sodium sulfide, and potassium oxide and potassium sulfide, respectively, at high pressure. The resulting structures formed in a certain pressure range were found to be stable or metastable through numerical calculations and analysis. The source of stability of neon-containing compounds systematically summarized in this work, and the results are of great significance in exploring the properties of neon at high pressures.
First principle study reveals the stability or metastability of neon reactivity with ionic compounds at high pressure. The stability driven factor is reduction of long range Coulomb energy of the lattice. To verify this conclusion, neon was mixed with sodium oxide, sodium sulfide, and potassium oxide and potassium sulfide, respectively, at high pressure. The resulting structures formed in a certain pressure range were found to be stable or metastable through numerical calculations and analysis. The source of stability of neon-containing compounds systematically summarized in this work, and the results are of great significance in exploring the properties of neon at high pressures.
, Available online ,
doi: 10.12202/j.0476-0301.2023200
Abstract:
Young's double-slit experiments exemplify the spatial coherence of light, while the second-order interference experiments, such as ghost interference and sub-wavelength interference, demonstrate the second-order coherence of spatially incoherent light. Phase-sensitive coherence, which describes the phase anti-correlation between two points, is rarely discussed in classically linear optical systems. In this paper, based on the conjugate symmetry of the Fourier transform, a novel phase-sensitive symmetric pseudothermal light source is generated by manipulating the spatial phase structure of an incident light field, which is characterized by the same amplitude but reversed-phase at spatially symmetric locations. Such a type of chaotic light still reflects the bunching effect of thermal light (with a peak correlation coefficient of 2), and produces an anomalously spatial super-bunching effect in second-order interference experiments, along with a theoretical peak of 3. Compared with other light sources, such as pseudo-thermal light, it is experimentally verified that the phase-sensitive symmetric thermal light can break through the upper limit of visibility of the second-order interference fringes from 1/3 to 1/2 of the original one. This work reveals an inner connection between phase-sensitive coherence and super-bunching correlation, which can be utilized to boost the visibility of various correlation-enabled applications, and also provides a new approach to generating super-bunching pseudothermal light.
Young's double-slit experiments exemplify the spatial coherence of light, while the second-order interference experiments, such as ghost interference and sub-wavelength interference, demonstrate the second-order coherence of spatially incoherent light. Phase-sensitive coherence, which describes the phase anti-correlation between two points, is rarely discussed in classically linear optical systems. In this paper, based on the conjugate symmetry of the Fourier transform, a novel phase-sensitive symmetric pseudothermal light source is generated by manipulating the spatial phase structure of an incident light field, which is characterized by the same amplitude but reversed-phase at spatially symmetric locations. Such a type of chaotic light still reflects the bunching effect of thermal light (with a peak correlation coefficient of 2), and produces an anomalously spatial super-bunching effect in second-order interference experiments, along with a theoretical peak of 3. Compared with other light sources, such as pseudo-thermal light, it is experimentally verified that the phase-sensitive symmetric thermal light can break through the upper limit of visibility of the second-order interference fringes from 1/3 to 1/2 of the original one. This work reveals an inner connection between phase-sensitive coherence and super-bunching correlation, which can be utilized to boost the visibility of various correlation-enabled applications, and also provides a new approach to generating super-bunching pseudothermal light.
, Available online ,
doi: 10.12202/j.0476-0301.2023189
Abstract:
Since Slater suggested that a gap could be opened by magnetic ordering with spin-dependent electronic energy, applying the magnetic field has been a powerful means to tune properties of Dirac fermion systems, especially 2D graphene system. Using the determinant quantum Monte Carlo method, we investigate the phase transitions induced by Zeeman field in 2D graphene lattice. The competition between Coulomb repulsion U, disorder Δ and magnetic fields B drives the semimetallic regime to insulating phases exhibiting different characters. Furthermore, the critical Zeeman field Bc triggering the band-insulator is largely reduced by the presence of interaction and disorder. As the magnetic field continues to increase, the B-induced symmetry breaking introduces an antiferromagnetic(AFM) phase, and eventually the system enters a fully spin-polarized state. In the correlated system, the weak interaction would enhance the effect of magnetic field on AFM phase, while the strong interaction larger than Uc=4.5 would inhibit this effect. Applying parallel magnetic fields provides the possibility to observe transport and magnetic transitions in real materials.
Since Slater suggested that a gap could be opened by magnetic ordering with spin-dependent electronic energy, applying the magnetic field has been a powerful means to tune properties of Dirac fermion systems, especially 2D graphene system. Using the determinant quantum Monte Carlo method, we investigate the phase transitions induced by Zeeman field in 2D graphene lattice. The competition between Coulomb repulsion U, disorder Δ and magnetic fields B drives the semimetallic regime to insulating phases exhibiting different characters. Furthermore, the critical Zeeman field Bc triggering the band-insulator is largely reduced by the presence of interaction and disorder. As the magnetic field continues to increase, the B-induced symmetry breaking introduces an antiferromagnetic(AFM) phase, and eventually the system enters a fully spin-polarized state. In the correlated system, the weak interaction would enhance the effect of magnetic field on AFM phase, while the strong interaction larger than Uc=4.5 would inhibit this effect. Applying parallel magnetic fields provides the possibility to observe transport and magnetic transitions in real materials.
, Available online ,
doi: 10.12202/j.0476-0301.2023199
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This article briefly reviews the history of the BNU’s research group on general relativity in its early years. We focus on two of our original research result here. One is that we have found a way to calculate the temperature on the surface of non-stationary black holes through point by point. Another one is that we have shown the zeroth law of thermodynamics to be equivalent to the transitive property of the clock rate synchronization.
This article briefly reviews the history of the BNU’s research group on general relativity in its early years. We focus on two of our original research result here. One is that we have found a way to calculate the temperature on the surface of non-stationary black holes through point by point. Another one is that we have shown the zeroth law of thermodynamics to be equivalent to the transitive property of the clock rate synchronization.
, Available online ,
doi: 10.12202/j.0476-0301.2023193
Abstract:
Thermal chaos under temporally/spatially periodic perturbations in the extended phase space of Bardeen-Anti de Sitter black holes surrounded by quintessence dark energy is investigated. The occurring condition of chaos is obtained with the Melnikov integral. It is shown that the spatial chaos is always supposed to occur even for a tiny spatially periodic perturbation imposed on the equilibrium configuration. However, the temporal chaos will arise in the unstable spinodal region only if the given perturbed amplitude\begin{document}$ \gamma $\end{document} ![]()
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Thermal chaos under temporally/spatially periodic perturbations in the extended phase space of Bardeen-Anti de Sitter black holes surrounded by quintessence dark energy is investigated. The occurring condition of chaos is obtained with the Melnikov integral. It is shown that the spatial chaos is always supposed to occur even for a tiny spatially periodic perturbation imposed on the equilibrium configuration. However, the temporal chaos will arise in the unstable spinodal region only if the given perturbed amplitude
, Available online ,
doi: 10.12202/j.0476-0301.2023196
Abstract:
Graphene is an important system in the fundamental research of low-dimensional condensed matter physics． Due to its two-dimensional structure with only a single atomic layer, graphene exhibits excellent structural flexibility and can sustain diverse structural deformations． This mechanical property makes strain control of graphene properties extremely convenient． Starting from a continuum model, this article explores the out-of-plane resonance with different modes of fixed boundary graphene sheets driven by a vertical external electric field． These resonance modes are closely related to the phonon properties of graphene． Atomic level phonon calculations reveal that the out-of-plane polarized phonon modes capture such modes and the frequencies of these phonon are consistent with the prediction of the continuous model． The non-uniform deformation of graphene structure induced by external fields provides a new approach for strain engineering of graphene．
Graphene is an important system in the fundamental research of low-dimensional condensed matter physics． Due to its two-dimensional structure with only a single atomic layer, graphene exhibits excellent structural flexibility and can sustain diverse structural deformations． This mechanical property makes strain control of graphene properties extremely convenient． Starting from a continuum model, this article explores the out-of-plane resonance with different modes of fixed boundary graphene sheets driven by a vertical external electric field． These resonance modes are closely related to the phonon properties of graphene． Atomic level phonon calculations reveal that the out-of-plane polarized phonon modes capture such modes and the frequencies of these phonon are consistent with the prediction of the continuous model． The non-uniform deformation of graphene structure induced by external fields provides a new approach for strain engineering of graphene．
, Available online ,
doi: 10.12202/j.0476-0301.2023188
Abstract:
How to understand strong correlated electrons states in a checkerboard lattice is an interesting problem. In frustrated systems, quantum Monte Carlo simulation often suffers the sign problem. We use the constrained path quantum Monte Carlo method which could effectively avoid the sign problem, and study the superconducting pairing correlation in doped Hubbard model on a checkerboard lattice. We find that the superconducting pairing correlation function with d-wave symmetry dominates over other symmetries, and the d-wave pairing correlation function increases with next-nearest neighbor hopping strength t ' decreases, and increases when the coulomb interaction increases. Our results provide some valid points for further theoretical research on the correlation effect and superconductivity in superconductors, also provide ideas for understanding the relationship between frustration and superconductivity.
How to understand strong correlated electrons states in a checkerboard lattice is an interesting problem. In frustrated systems, quantum Monte Carlo simulation often suffers the sign problem. We use the constrained path quantum Monte Carlo method which could effectively avoid the sign problem, and study the superconducting pairing correlation in doped Hubbard model on a checkerboard lattice. We find that the superconducting pairing correlation function with d-wave symmetry dominates over other symmetries, and the d-wave pairing correlation function increases with next-nearest neighbor hopping strength t ' decreases, and increases when the coulomb interaction increases. Our results provide some valid points for further theoretical research on the correlation effect and superconductivity in superconductors, also provide ideas for understanding the relationship between frustration and superconductivity.
, Available online ,
doi: 10.12202/j.0476-0301.2023201
Abstract:
To enhance the luminescence effect of rare-earth organic thin films, gold nano core-shell structures (Au@SiO2) were introduced during the preparation process of rare-earth luminescent films. Using the drop-casting method, Au@SiO2 nanostructures with different molar concentrations were applied onto quartz slides; subsequently, a mixture of Eu(dbm)3phen: PMMA:CH2Cl2 was spin-coated onto the quartz slides to fabricate thin film samples. Post-characterization of these samples revealed that introducing Au@SiO2 significantly enhanced the luminescence intensity of the films. The maximum excitation and luminescence enhancement factors were 279.1% and 222.9% respectively, and the fluorescent lifetime of the film samples was extended as well. Incorporating Au@SiO2 into the fabrication process of rare-earth luminescent films effectively improves their luminous performance, showing promising application potential.
To enhance the luminescence effect of rare-earth organic thin films, gold nano core-shell structures (Au@SiO2) were introduced during the preparation process of rare-earth luminescent films. Using the drop-casting method, Au@SiO2 nanostructures with different molar concentrations were applied onto quartz slides; subsequently, a mixture of Eu(dbm)3phen: PMMA:CH2Cl2 was spin-coated onto the quartz slides to fabricate thin film samples. Post-characterization of these samples revealed that introducing Au@SiO2 significantly enhanced the luminescence intensity of the films. The maximum excitation and luminescence enhancement factors were 279.1% and 222.9% respectively, and the fluorescent lifetime of the film samples was extended as well. Incorporating Au@SiO2 into the fabrication process of rare-earth luminescent films effectively improves their luminous performance, showing promising application potential.
, Available online ,
doi: 10.12202/j.0476-0301.2023187
Abstract:
In this paper, Brownian motion with higher-derivative dynamics is investigated. As a model, we consider a particle coupling with a heat bath consisting of harmonic oscillators. Assume that the motion of the particle without the bath is determined by a Lagrangian\begin{document}$ L = L\left(t,x,{x}_{1},\cdots ,{x}_{N}\right) $\end{document} ![]()
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In this paper, Brownian motion with higher-derivative dynamics is investigated. As a model, we consider a particle coupling with a heat bath consisting of harmonic oscillators. Assume that the motion of the particle without the bath is determined by a Lagrangian
, Available online ,
doi: 10.12202/j.0476-0301.2023190
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Quantum metrology based on quantum entanglement and quantum coherence improves the accuracy of measurement. In this paper, we briefly review the schemes of quantum metrology in various complex environments, including non-Markovian noise, correlated noise, two-photon relaxation. On the other hand, the booming development of quantum information allows us to utilize quantum simulation experiments to test the feasibility of various theoretical schemes and demonstrate the rich physical phenomena in different baths.
Quantum metrology based on quantum entanglement and quantum coherence improves the accuracy of measurement. In this paper, we briefly review the schemes of quantum metrology in various complex environments, including non-Markovian noise, correlated noise, two-photon relaxation. On the other hand, the booming development of quantum information allows us to utilize quantum simulation experiments to test the feasibility of various theoretical schemes and demonstrate the rich physical phenomena in different baths.
, Available online ,
doi: 10.12202/j.0476-0301.2023194
Abstract:
Micro-lasers with micro/nano scale cavities have mode volume at wavelength or sub-wavelength scale, which are characterized with small size, easy integration, low threshold, wide band, tenability. Micro-lasers play a core role in the generation, transmission, coupling, modulation, detection and other functions of optical information on photonic chips, which is an important frontier in the field of micro/ nano optics. The application research of micro-lasers are related to their optical field characteristics. In order to realize the multi-functional application of micro-lasers, studies on optical field modulation of micro-laser have been conducted, referring to theory, experimental and device application. Here, the research progress of micro-lasers are summarized from optical field modulation and application. The modulating methods based on pumping light, gain and micro-cavity are emphatically described. The application progress of micro-lasers in sensing, anti-counterfeiting, imaging and display fields is summarized. And the future research direction is prospeced.
Micro-lasers with micro/nano scale cavities have mode volume at wavelength or sub-wavelength scale, which are characterized with small size, easy integration, low threshold, wide band, tenability. Micro-lasers play a core role in the generation, transmission, coupling, modulation, detection and other functions of optical information on photonic chips, which is an important frontier in the field of micro/ nano optics. The application research of micro-lasers are related to their optical field characteristics. In order to realize the multi-functional application of micro-lasers, studies on optical field modulation of micro-laser have been conducted, referring to theory, experimental and device application. Here, the research progress of micro-lasers are summarized from optical field modulation and application. The modulating methods based on pumping light, gain and micro-cavity are emphatically described. The application progress of micro-lasers in sensing, anti-counterfeiting, imaging and display fields is summarized. And the future research direction is prospeced.
, Available online ,
doi: 10.12202/j.0476-0301.2023146
Abstract:
With rapid development of renewable energy and acceleration of construction of renewable-dominated new-type power systems, the dynamic characteristics and synchronous stability of modern power systems become much more complicated. This review paper first briefly introduces the development of the traditional power systems and the research status of the renewable-dominated new-type power systems. Then, based on the key method of combined holism and reductionism, three typical renewable energy equipment (nodes) including permanent magnetic synchronous generator, double-fed induction generator, and photovoltaic and the AC transmission line (network) models are established within the three timescales (including the AC current control, DC-link voltage control, and electromechanical timescales) according to the multi-timescale characteristics of the new-type power systems. At the same time, the machine-network interface relationship between the nodes and network is uncovered. The dynamic model framework of the new-type power systems is preliminarily established. Finally, this paper reveals the synchronous stability mechanism of the new-type power systems. This paper could help deepen our understanding of the dynamics of the renewable-dominated new-type power systems and promote interdisciplinary collaborative research among electrical engineering, complex systems and statistical physics on these fundamental problems.
With rapid development of renewable energy and acceleration of construction of renewable-dominated new-type power systems, the dynamic characteristics and synchronous stability of modern power systems become much more complicated. This review paper first briefly introduces the development of the traditional power systems and the research status of the renewable-dominated new-type power systems. Then, based on the key method of combined holism and reductionism, three typical renewable energy equipment (nodes) including permanent magnetic synchronous generator, double-fed induction generator, and photovoltaic and the AC transmission line (network) models are established within the three timescales (including the AC current control, DC-link voltage control, and electromechanical timescales) according to the multi-timescale characteristics of the new-type power systems. At the same time, the machine-network interface relationship between the nodes and network is uncovered. The dynamic model framework of the new-type power systems is preliminarily established. Finally, this paper reveals the synchronous stability mechanism of the new-type power systems. This paper could help deepen our understanding of the dynamics of the renewable-dominated new-type power systems and promote interdisciplinary collaborative research among electrical engineering, complex systems and statistical physics on these fundamental problems.
, Available online ,
doi: 10.12202/j.0476-0301.2023197
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With the development of artificial intelligence, science exploration based on artificial intelligence has gradually become the forefront of technological advancement. Simultaneously, the mathematical foundation of intelligent phenomena has also emerged as a crucial scientific issue requiring urgent resolution behind the rapid development of artificial intelligence. Among numerous artificial intelligence algorithms, the reservoir computing method due to its simple structure, flexible and diverse implementation methods, as well as characteristics such as nonlinearity and memory, has been widely applied in the research of time series and dynamical system-related problems. Besides, the trained reservoir itself forms a complex dynamical system. Serving as a bridge, the analysis based on dynamical system theory through the reservoir plays an important role in exploring the intelligent phenomena of the learning process. This paper reviews and prospects the latest research progress of the reservoir computing algorithm, outlining two complementary research directions as the reservoir computing for dynamical systems, and dynamical System Foundations of reservoir computing. This paper will contribute to deepening researchers' understanding of artificial intelligence algorithms, promoting interdisciplinary research and communication among artificial intelligence, complex systems, and statistical physics-related disciplines.
With the development of artificial intelligence, science exploration based on artificial intelligence has gradually become the forefront of technological advancement. Simultaneously, the mathematical foundation of intelligent phenomena has also emerged as a crucial scientific issue requiring urgent resolution behind the rapid development of artificial intelligence. Among numerous artificial intelligence algorithms, the reservoir computing method due to its simple structure, flexible and diverse implementation methods, as well as characteristics such as nonlinearity and memory, has been widely applied in the research of time series and dynamical system-related problems. Besides, the trained reservoir itself forms a complex dynamical system. Serving as a bridge, the analysis based on dynamical system theory through the reservoir plays an important role in exploring the intelligent phenomena of the learning process. This paper reviews and prospects the latest research progress of the reservoir computing algorithm, outlining two complementary research directions as the reservoir computing for dynamical systems, and dynamical System Foundations of reservoir computing. This paper will contribute to deepening researchers' understanding of artificial intelligence algorithms, promoting interdisciplinary research and communication among artificial intelligence, complex systems, and statistical physics-related disciplines.
, Available online ,
doi: 10.12202/j.0476-0301.2023095
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Currently, in the context of the construction of ecological civilization, adaptation to climate change has become an important path to strengthen the construction of ecological civilization, help build a beautiful China and promote high-quality development. Actively adapted to climate change concerns the sustainable development of the city. Xiong'an new area is a city under construction. It is typical and exemplary to carry out adaptation to climate change, which is conducive to reducing the adverse effects of climate change under the background of global warming. This research summarized the prediction of climate change situation of Xiong'an New Area made by experts and scholars, and identified that Xiong'an new area faces climate risks such as high temperature, rainstorm and flood. In the future, Xiong’an area would has critical problems of large-scale population increase, industrial layout updating, exposure degree of population increase, imitated water resource carrying capacity, insufficient in cognitive and ability of adaptation to climate change. During the construction of Xiong'an new area, we should base on the strategic positioning of the "millennium plan", formulate strategies to adapt to climate change, emphasize on people-centered, build a collaborative governance mechanism to adapt to climate change, and enhance the publicity and capacity-building of Xiong'an new area's model work to climate change adaptation.
Currently, in the context of the construction of ecological civilization, adaptation to climate change has become an important path to strengthen the construction of ecological civilization, help build a beautiful China and promote high-quality development. Actively adapted to climate change concerns the sustainable development of the city. Xiong'an new area is a city under construction. It is typical and exemplary to carry out adaptation to climate change, which is conducive to reducing the adverse effects of climate change under the background of global warming. This research summarized the prediction of climate change situation of Xiong'an New Area made by experts and scholars, and identified that Xiong'an new area faces climate risks such as high temperature, rainstorm and flood. In the future, Xiong’an area would has critical problems of large-scale population increase, industrial layout updating, exposure degree of population increase, imitated water resource carrying capacity, insufficient in cognitive and ability of adaptation to climate change. During the construction of Xiong'an new area, we should base on the strategic positioning of the "millennium plan", formulate strategies to adapt to climate change, emphasize on people-centered, build a collaborative governance mechanism to adapt to climate change, and enhance the publicity and capacity-building of Xiong'an new area's model work to climate change adaptation.
, Available online ,
doi: 10.12202/j.0476-0301.2023093
Abstract:
High quality development is the key to Chinese path to modernization. On the basis of clarifying the logical relationship between the economy, society, ecology and urban construction of the Yellow River basin, the study builds an evaluation index system of high-quality development efficiency of the multi-dimensional system of the Yellow River basin, selects MinDS model and coupling coordination degree to calculate the multi system coupling coordination evolution of high-quality development efficiency of the Yellow River basin in different scales from 2009 to 2020, and uses Tobit model to discuss its impact mechanism. The results show that:(1) The high quality development efficiency of the Yellow River basin shows a slow upward trend in general, in which the high-quality economic development efficiency shows an "inverted U" development trend, and the downstream > midstream > upstream; The efficiency of high-quality social development declines slowly, and the upstream > downstream > midstream; The efficiency of high-quality ecological development rises rapidly, and the midstream > upstream > the downstream; The efficiency of high-quality urban development fluctuates steadily, and the midstream > upstream > downstream.(2)The high quality development efficiency of the whole Yellow River basin、upstream and midstream belongs to a relatively coordinated state, The downstream as a whole is close to coordination.(3) The impacts of economic development level, industrial structure transformation, scientific and technological input intensity, scientific and technological output level, energy consumption intensity, environmental regulation, openness, infrastructure guarantee and urbanization level on the high-quality development efficiency of the Yellow River basin and multi system coupling coordination in different river basins show spatial heterogeneity. Based on this, this study puts forward policy recommendations to promote the high-quality development of the Yellow River basin.
High quality development is the key to Chinese path to modernization. On the basis of clarifying the logical relationship between the economy, society, ecology and urban construction of the Yellow River basin, the study builds an evaluation index system of high-quality development efficiency of the multi-dimensional system of the Yellow River basin, selects MinDS model and coupling coordination degree to calculate the multi system coupling coordination evolution of high-quality development efficiency of the Yellow River basin in different scales from 2009 to 2020, and uses Tobit model to discuss its impact mechanism. The results show that:(1) The high quality development efficiency of the Yellow River basin shows a slow upward trend in general, in which the high-quality economic development efficiency shows an "inverted U" development trend, and the downstream > midstream > upstream; The efficiency of high-quality social development declines slowly, and the upstream > downstream > midstream; The efficiency of high-quality ecological development rises rapidly, and the midstream > upstream > the downstream; The efficiency of high-quality urban development fluctuates steadily, and the midstream > upstream > downstream.(2)The high quality development efficiency of the whole Yellow River basin、upstream and midstream belongs to a relatively coordinated state, The downstream as a whole is close to coordination.(3) The impacts of economic development level, industrial structure transformation, scientific and technological input intensity, scientific and technological output level, energy consumption intensity, environmental regulation, openness, infrastructure guarantee and urbanization level on the high-quality development efficiency of the Yellow River basin and multi system coupling coordination in different river basins show spatial heterogeneity. Based on this, this study puts forward policy recommendations to promote the high-quality development of the Yellow River basin.
, Available online ,
doi: 10.12202/j.0476-0301.2023136
Abstract:
Hangzhou City possesses diverse and abundant wetland resources. However, with the rapid urbanization, the area of wetlands has been shrinking, and issues such as degradation of ecosystem quality and functional decline have become increasingly severe. As a result, conducting a refined classification research on land cover and wetland types in Hangzhou City is crucial for creating effective wetland protection and management policies. In this study, we employed the Google Earth Engine (GEE) cloud platform and Sentinel-2 satellite imagery data to perform a classification of wetland in Hangzhou City using the Random Forest algorithm. Our findings revealed that a combination of multiple feature information substantially enhanced classification accuracy, compared to using single-feature information when executing refined wetland classification. The optimal feature combination encompassed traditional spectral features, red-edge spectral features, transformed features, texture features, and topographic features, yielding an overall accuracy of 81.2% and a Kappa coefficient of 0.75. Different feature information significantly contributed to the extraction of various wetland types. Traditional spectral features were particularly advantageous for identifying tidal flats and aquaculture ponds, while red-edge spectral features and transformed features were more effective for recognizing herbaceous marshes and lakes, respectively. Furthermore, combining red-edge spectral features and texture features proved beneficial for identifying canals and water channels. The feature comparison experiment in this study serves as a reference for future case studies on refined wetland classification, and the wetland classification results provide data support for the remote sensing identification of wetland information in Hangzhou City.
Hangzhou City possesses diverse and abundant wetland resources. However, with the rapid urbanization, the area of wetlands has been shrinking, and issues such as degradation of ecosystem quality and functional decline have become increasingly severe. As a result, conducting a refined classification research on land cover and wetland types in Hangzhou City is crucial for creating effective wetland protection and management policies. In this study, we employed the Google Earth Engine (GEE) cloud platform and Sentinel-2 satellite imagery data to perform a classification of wetland in Hangzhou City using the Random Forest algorithm. Our findings revealed that a combination of multiple feature information substantially enhanced classification accuracy, compared to using single-feature information when executing refined wetland classification. The optimal feature combination encompassed traditional spectral features, red-edge spectral features, transformed features, texture features, and topographic features, yielding an overall accuracy of 81.2% and a Kappa coefficient of 0.75. Different feature information significantly contributed to the extraction of various wetland types. Traditional spectral features were particularly advantageous for identifying tidal flats and aquaculture ponds, while red-edge spectral features and transformed features were more effective for recognizing herbaceous marshes and lakes, respectively. Furthermore, combining red-edge spectral features and texture features proved beneficial for identifying canals and water channels. The feature comparison experiment in this study serves as a reference for future case studies on refined wetland classification, and the wetland classification results provide data support for the remote sensing identification of wetland information in Hangzhou City.
, Available online ,
doi: 10.12202/j.0476-0301.2023098
Abstract:
Taking Qianjiang District of Chongqing Municipality as an example, 23 evaluation factors are selected to construct a landslide disaster-causing factor database, and the optimal combination of factors is chosen by utilizing two kinds of factor screening methods, i.e., geodetector and Pearson-principal component analysis. Based on the Bayesian-LightGBM-SHAP hybrid model for landslide susceptibility evaluation, and verify the model accuracy, the dominant factors affecting the occurrence of landslides in Qianjiang District are analyzed. The initial model has an AUC value of 0.801, the Person Correlation Coefficient-Bayesian-LightGBM model has an AUC value of 0.824, and the GeoDetector-Bayesian-LightGBM model has an AUC of 0.835. From the importance of the factors, it can be seen that the average multi-year rainfall, elevation, POI kernel density and distance from the rivers are the most important factors for the occurrence of landslides, while the sand transport index, hydrodynamic index and slope position have a weaker effect on the occurrence of landslides. The hybrid model combining factor screening method-Bayesian-LightGBM can improve the accuracy of the model and provide a reference framework for constructing a rational factor database. By integrating the analysis with factor significance, it is verified that the geoprobe can accurately detect the contribution value of each factor to landslide occurrence, highlight the correlation between each combination of landslide conditioning factors, and thus explore the relationship between each factor and landslides.
Taking Qianjiang District of Chongqing Municipality as an example, 23 evaluation factors are selected to construct a landslide disaster-causing factor database, and the optimal combination of factors is chosen by utilizing two kinds of factor screening methods, i.e., geodetector and Pearson-principal component analysis. Based on the Bayesian-LightGBM-SHAP hybrid model for landslide susceptibility evaluation, and verify the model accuracy, the dominant factors affecting the occurrence of landslides in Qianjiang District are analyzed. The initial model has an AUC value of 0.801, the Person Correlation Coefficient-Bayesian-LightGBM model has an AUC value of 0.824, and the GeoDetector-Bayesian-LightGBM model has an AUC of 0.835. From the importance of the factors, it can be seen that the average multi-year rainfall, elevation, POI kernel density and distance from the rivers are the most important factors for the occurrence of landslides, while the sand transport index, hydrodynamic index and slope position have a weaker effect on the occurrence of landslides. The hybrid model combining factor screening method-Bayesian-LightGBM can improve the accuracy of the model and provide a reference framework for constructing a rational factor database. By integrating the analysis with factor significance, it is verified that the geoprobe can accurately detect the contribution value of each factor to landslide occurrence, highlight the correlation between each combination of landslide conditioning factors, and thus explore the relationship between each factor and landslides.
, Available online ,
doi: 10.12202/j.0476-0301.2023145
Abstract:
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, Available online ,
doi: 10.12202/j.0476-0301.2023135
Abstract:
Aiming at the inability to effectively reveal the mechanism of energy flow in the process of land transfer, this article utilized the land transfer data of Donggaochang Village in Tai-hang Mountains of Hebei Province from 2016 to 2019, and applied the Energy System Language model to simulate and evaluate the process before and after land transfer in Tai-hang Mountains of Hebei Province, and further simulated the system energy change after land transfer based on the land use scenarios and the viewpoint of labor inputs. The energy changes of the system after land transfer were further simulated based on land use scenarios and labor input perspectives. The results showed that: (1) crop biomass, capital and ecological environment were significantly increased after land transfer compared with before land transfer; after 10 years, crop biomass, capital and forest biomass were 12.97 times, 2.10 times and 36.54 times higher than before land transfer respectively; after 50 years, crop biomass, capital and forest biomass were 15.34 times, 4.23 times and 39.22 times higher than before land transfer respectively; after 100 years, crop biomass, capital and forest biomass were 26.79 times, 7.39 times and 66.60 times higher than before land transfer respectively. (2) The effect of the transfer of changing the planting structure was general, but the adjustment of the labor input structure made the biomass and capital of pumpkin after the land transfer showed an inverted U-shaped trend, with the biomass of pumpkin reaching the peak in 24 years and the capital reaching the peak in 48 years. Inputting local labor increased crop biomass by 46.5% and capital by 212%, which was the most significant effect.
Aiming at the inability to effectively reveal the mechanism of energy flow in the process of land transfer, this article utilized the land transfer data of Donggaochang Village in Tai-hang Mountains of Hebei Province from 2016 to 2019, and applied the Energy System Language model to simulate and evaluate the process before and after land transfer in Tai-hang Mountains of Hebei Province, and further simulated the system energy change after land transfer based on the land use scenarios and the viewpoint of labor inputs. The energy changes of the system after land transfer were further simulated based on land use scenarios and labor input perspectives. The results showed that: (1) crop biomass, capital and ecological environment were significantly increased after land transfer compared with before land transfer; after 10 years, crop biomass, capital and forest biomass were 12.97 times, 2.10 times and 36.54 times higher than before land transfer respectively; after 50 years, crop biomass, capital and forest biomass were 15.34 times, 4.23 times and 39.22 times higher than before land transfer respectively; after 100 years, crop biomass, capital and forest biomass were 26.79 times, 7.39 times and 66.60 times higher than before land transfer respectively. (2) The effect of the transfer of changing the planting structure was general, but the adjustment of the labor input structure made the biomass and capital of pumpkin after the land transfer showed an inverted U-shaped trend, with the biomass of pumpkin reaching the peak in 24 years and the capital reaching the peak in 48 years. Inputting local labor increased crop biomass by 46.5% and capital by 212%, which was the most significant effect.
, Available online ,
doi: 10.12202/j.0476-0301.2022338
Abstract:
In order to better explore the land use and land cover change (LUCC)in Xiong’an New Area and evaluate the ecological quality impacted by construction, 9 Landsat 8 images from 2013 to 2021 in this area were classified with the object-oriented supervision classification method. Based on all results, the following main conclusions were drawn: (1) The overall accuracy of the new classification results was greater than 86.8% and the kappa coefficients ranged from 0.81 to 0.88, which were superior to that from the FROM-GLC and GLC_FCS global land cover product. (2) Since 2017 when Xiong’an New Area was established, the area of cropland has decreased and the area of impervious area and forest have increased, while the area proportion of the blue-green space has increased from 12% to 30%. Besides, the different LUCC patterns were also observed in three counties within Xiong’an New Area, which met the planning requirements very well. (3) Although the expansion of impervious area and urban construction have the inevitable negative impacts on ecological quality, the positive impacts owing to the increase of forest coverage and the blue-green space have increased gradually and would take the lead in the near future. In conclusion, the LUCC in Xiong’an New Area complies with the construction policy and reflects the achievements of economic and social development in this area.
In order to better explore the land use and land cover change (LUCC)in Xiong’an New Area and evaluate the ecological quality impacted by construction, 9 Landsat 8 images from 2013 to 2021 in this area were classified with the object-oriented supervision classification method. Based on all results, the following main conclusions were drawn: (1) The overall accuracy of the new classification results was greater than 86.8% and the kappa coefficients ranged from 0.81 to 0.88, which were superior to that from the FROM-GLC and GLC_FCS global land cover product. (2) Since 2017 when Xiong’an New Area was established, the area of cropland has decreased and the area of impervious area and forest have increased, while the area proportion of the blue-green space has increased from 12% to 30%. Besides, the different LUCC patterns were also observed in three counties within Xiong’an New Area, which met the planning requirements very well. (3) Although the expansion of impervious area and urban construction have the inevitable negative impacts on ecological quality, the positive impacts owing to the increase of forest coverage and the blue-green space have increased gradually and would take the lead in the near future. In conclusion, the LUCC in Xiong’an New Area complies with the construction policy and reflects the achievements of economic and social development in this area.
, Available online ,
doi: 10.12202/j.0476-0301.2023050
Abstract:
In this paper, we considered the magnetic WSe2 superlattice system, explored the effects of non-resonant circularly polarized light and gate voltage on tunneling, valley polarization and spin polarization, the manipulation of ballistic transport in single-layer WSe2 and control of the quantum transport in the periodic array of NM/FM/NM junctions based on magnetic WSe2. The results show that the critical value of circularly polarized light can eliminate the transmission energy gap by increasing the number of potential barriers; The circularly polarized light and gate voltage can be regarded as a transmission valve and a sensitive knob for controlling the spin and valley polarization; Klein tunneling in WSe2 super lattice is spin-valley dependent; spin-valley polarization can be adjusted and converted by grid voltage and circularly polarized light.
In this paper, we considered the magnetic WSe2 superlattice system, explored the effects of non-resonant circularly polarized light and gate voltage on tunneling, valley polarization and spin polarization, the manipulation of ballistic transport in single-layer WSe2 and control of the quantum transport in the periodic array of NM/FM/NM junctions based on magnetic WSe2. The results show that the critical value of circularly polarized light can eliminate the transmission energy gap by increasing the number of potential barriers; The circularly polarized light and gate voltage can be regarded as a transmission valve and a sensitive knob for controlling the spin and valley polarization; Klein tunneling in WSe2 super lattice is spin-valley dependent; spin-valley polarization can be adjusted and converted by grid voltage and circularly polarized light.
, Available online ,
doi: 10.12202/j.0476-0301.2022361
Abstract:
Taking Tibet and Qinghai Province as the study areas, we evaluate the cultivated land quality in terms of soil properties and technical conditions, identify its dominant limiting factors, and explore its macroscopic influences, with a view to providing support for enhancing the productivity of cultivated land and ensuring food security in the plateau region. The evaluation indicators weights are determined based on the combining of subjective and objective weighting, and the random forest method is introduced to explore the influence of regional macro natural-economic-social factors. The results show that the cultivated land in the Tibet and Qinghai is mainly medium land, accounting for 44.6% of the area, and the medium land is mostly sloping land in the “Huangshui” Valley area of Qinghai and the high slope of the field surface restricts the utilization use of arable land. Elevation and the Distances to City have important effects on the cultivated land quality globally. In most areas, Elevation and arable land quality show a negative correlation. The influence of Distances to City on the cultivated land quality varies spatially. In the central and southern Tibetan and frontier belt areas, high quality cultivated land is often laid out around cities due to the improvment of technical conditions. In contrast, in the valley areas of the northeastern plateau, the soil quality of arable land adjacent to the urban periphery is lower and degradation is more likely to occur.
Taking Tibet and Qinghai Province as the study areas, we evaluate the cultivated land quality in terms of soil properties and technical conditions, identify its dominant limiting factors, and explore its macroscopic influences, with a view to providing support for enhancing the productivity of cultivated land and ensuring food security in the plateau region. The evaluation indicators weights are determined based on the combining of subjective and objective weighting, and the random forest method is introduced to explore the influence of regional macro natural-economic-social factors. The results show that the cultivated land in the Tibet and Qinghai is mainly medium land, accounting for 44.6% of the area, and the medium land is mostly sloping land in the “Huangshui” Valley area of Qinghai and the high slope of the field surface restricts the utilization use of arable land. Elevation and the Distances to City have important effects on the cultivated land quality globally. In most areas, Elevation and arable land quality show a negative correlation. The influence of Distances to City on the cultivated land quality varies spatially. In the central and southern Tibetan and frontier belt areas, high quality cultivated land is often laid out around cities due to the improvment of technical conditions. In contrast, in the valley areas of the northeastern plateau, the soil quality of arable land adjacent to the urban periphery is lower and degradation is more likely to occur.
, Available online ,
doi: 10.12202/j.0476-0301.2023035
Abstract:
Using the reanalysis data and precipitation dataset during 1961-2020, this paper analyzes the influence of developing phase of the Eastern Pacific El Niño events on the summer extreme precipitation in China. Results are shown as follows. During the developing summer, El Niño mainly affected Eastern China, resulting in the extreme precipitation in North China and Jiangnan region decreased, while the extreme precipitation in Jianghuai region increased significantly. The physical process is further analyzed. When the Eastern Pacific El Niño event is in the developing summer, significant positive SST anomalies were observed in the equatorial Eastern Pacific and negative SST anomalies were observed in the Western Pacific, which are associated with anticyclonic circulation anomalies. There were positive SST anomalies in the Northwest Pacific, corresponding to the cyclonic circulation anomalies. The anomalous SST stimulated the “+ - +” EAP wave train anomalies and caused “- + -” precipitation configuration. At the intersection of anomalous circulations, it showed a significant anomalous convergence and ascent, which brought sufficient water vapor to the Jianghuai region. However, North China was mainly controlled by anticyclonic circulation and Mongolian high, and was affected by the anomalous northwest wind from the high latitudes. There was a significant anomalous divergence and sinking, the dynamic conditions of precipitation were insufficient. In addition, during the developing phase of the Eastern Pacific El Niño events, the Western Pacific subtropical high shifted eastward, which weakened the occurrence of precipitation and water vapor transport in Jiangnan region, resulting in the extreme precipitation in Jiangnan region decreased. The above results highlight the important impact of the Eastern Pacific El Niño events on extreme precipitation in China during the developing summer, and provide a theoretical basis for regional extreme climate prediction.
Using the reanalysis data and precipitation dataset during 1961-2020, this paper analyzes the influence of developing phase of the Eastern Pacific El Niño events on the summer extreme precipitation in China. Results are shown as follows. During the developing summer, El Niño mainly affected Eastern China, resulting in the extreme precipitation in North China and Jiangnan region decreased, while the extreme precipitation in Jianghuai region increased significantly. The physical process is further analyzed. When the Eastern Pacific El Niño event is in the developing summer, significant positive SST anomalies were observed in the equatorial Eastern Pacific and negative SST anomalies were observed in the Western Pacific, which are associated with anticyclonic circulation anomalies. There were positive SST anomalies in the Northwest Pacific, corresponding to the cyclonic circulation anomalies. The anomalous SST stimulated the “+ - +” EAP wave train anomalies and caused “- + -” precipitation configuration. At the intersection of anomalous circulations, it showed a significant anomalous convergence and ascent, which brought sufficient water vapor to the Jianghuai region. However, North China was mainly controlled by anticyclonic circulation and Mongolian high, and was affected by the anomalous northwest wind from the high latitudes. There was a significant anomalous divergence and sinking, the dynamic conditions of precipitation were insufficient. In addition, during the developing phase of the Eastern Pacific El Niño events, the Western Pacific subtropical high shifted eastward, which weakened the occurrence of precipitation and water vapor transport in Jiangnan region, resulting in the extreme precipitation in Jiangnan region decreased. The above results highlight the important impact of the Eastern Pacific El Niño events on extreme precipitation in China during the developing summer, and provide a theoretical basis for regional extreme climate prediction.
, Available online ,
doi: 10.12202/j.0476-0301.2022362
Abstract:
In the new era of ecological civilization, the traditional principles and the adjustment of administrative division in China do not take ecological factors into account adequately, and even are in conflict with ecological governance. This study proposes that the administrative division should follow the ecological principle, that is, to take the ecological protection and development as an important starting point for the adjustment and optimization of administrative division. The adjustment of administrative divisions could become an important means to improve ecological governance and promote ecological civilization. In order to adjust and optimize the administrative divisions in accordance with the ecological principle, it is necessary to exert the guiding role of the ecological functional divisions. The Tibetan Plateau has important ecological functions in China, but the division of administrative divisions has affected the ecological governance to some certain extent, and the planning and construction of important ecological projects also challenges the existing administrative division in this area. In the future, we should consider the adjustment of administrative divisions as a means to promote the ecological governance of the Tibetan Plateau. Relying on the resource effect of the administrative divisions, the spatial governance capacity of the Tibetan Plateau and ecological civilization could be promoted.
In the new era of ecological civilization, the traditional principles and the adjustment of administrative division in China do not take ecological factors into account adequately, and even are in conflict with ecological governance. This study proposes that the administrative division should follow the ecological principle, that is, to take the ecological protection and development as an important starting point for the adjustment and optimization of administrative division. The adjustment of administrative divisions could become an important means to improve ecological governance and promote ecological civilization. In order to adjust and optimize the administrative divisions in accordance with the ecological principle, it is necessary to exert the guiding role of the ecological functional divisions. The Tibetan Plateau has important ecological functions in China, but the division of administrative divisions has affected the ecological governance to some certain extent, and the planning and construction of important ecological projects also challenges the existing administrative division in this area. In the future, we should consider the adjustment of administrative divisions as a means to promote the ecological governance of the Tibetan Plateau. Relying on the resource effect of the administrative divisions, the spatial governance capacity of the Tibetan Plateau and ecological civilization could be promoted.
, Available online ,
doi: 10.12202/j.0476-0301.2022327
Abstract:
In the context of global advocacy of sustainable development, China is striving to reach a peak in CO2 emissions before 2030. Land use change is closely related to carbon emissions and forest stock volume. Thus, it is necessary to balance and optimize land use under different development scenarios before carbon peaks. In terms of achieving carbon peaking, Fujian Province is a crucial area for China because the forest coverage rate of Fujian Province is the highest in China. At the same time, Fujian Province is also necessary for China’s economic growth. Therefore, future land use changes in Fujian Province are affected by the trade-off between carbon-peaking actions and economic development. The study uses the CLUMondo model to explore the optimal land use allocation under 3 scenarios. Specifically, the 3 scenarios are the ecological target scenario (maximizing ecological benefits, and the forest stock volume is not lower than the target value), the economic target scenario (satisfying the land use status in 2030 under the economic development target, and the forest area is not degraded) and the conventional coordinated target scenario (ecological and economic goals are developed steadily according to the current situation). The study draws the following conclusions: (1) The CLUMondo model is suitable for the land use/land cover change simulation in Fujian Province. (2) To achieve economic development while maintaining the existing forest area as much as possible in the future, Fujian Province needs to improve further forest management lever, forest quality, and the forest ecological benefit compensation system. (3) Fujian Province should optimize the urban development pattern and strengthen the intensive development of urban, ecological functional areas. The study provides reference suggestions for promoting the economic development of Fujian Province and helping China’s carbon peak.
In the context of global advocacy of sustainable development, China is striving to reach a peak in CO2 emissions before 2030. Land use change is closely related to carbon emissions and forest stock volume. Thus, it is necessary to balance and optimize land use under different development scenarios before carbon peaks. In terms of achieving carbon peaking, Fujian Province is a crucial area for China because the forest coverage rate of Fujian Province is the highest in China. At the same time, Fujian Province is also necessary for China’s economic growth. Therefore, future land use changes in Fujian Province are affected by the trade-off between carbon-peaking actions and economic development. The study uses the CLUMondo model to explore the optimal land use allocation under 3 scenarios. Specifically, the 3 scenarios are the ecological target scenario (maximizing ecological benefits, and the forest stock volume is not lower than the target value), the economic target scenario (satisfying the land use status in 2030 under the economic development target, and the forest area is not degraded) and the conventional coordinated target scenario (ecological and economic goals are developed steadily according to the current situation). The study draws the following conclusions: (1) The CLUMondo model is suitable for the land use/land cover change simulation in Fujian Province. (2) To achieve economic development while maintaining the existing forest area as much as possible in the future, Fujian Province needs to improve further forest management lever, forest quality, and the forest ecological benefit compensation system. (3) Fujian Province should optimize the urban development pattern and strengthen the intensive development of urban, ecological functional areas. The study provides reference suggestions for promoting the economic development of Fujian Province and helping China’s carbon peak.
, Available online ,
doi: 10.12202/j.0476-0301.2023133
Abstract:
In the context of intensifying global warming, accurate predictions of climate change in the coming period are essential. Based on the 15 GCM models (GCMs) in the newly released Coupled Model Intercomparison Project 6 (CMIP6), this paper quantifies the uncertainty of temperature and precipitation estimates in the Tibetan Plateau under the next four shared socioeconomic pathways and typical concentration pathway combination scenarios. Then, the CMIP6 mode output data is biased corrected using the DT method. By comparing the magnitude of the uncertainty before and after DT, the potential of the bias correction method in reducing the uncertainty of temperature and precipitation estimates is discussed. The results show that the correction results of the DT method are closer to the measured values. In the long run, model uncertainty dominates, while the contribution of scenario uncertainty and internal variability is relatively low. The DT method has a good effect on reducing the uncertainty of precipitation prediction, and almost reduces the model uncertainty by 80%, which has little effect on the size of scenario uncertainty but affects the relative contribution of uncertainty. In summary, the use of the DT method for deviation correction can reduce the uncertainty of estimation to a certain extent. Results have important implications for the impact of climate change on water cycles in alpine regions.
In the context of intensifying global warming, accurate predictions of climate change in the coming period are essential. Based on the 15 GCM models (GCMs) in the newly released Coupled Model Intercomparison Project 6 (CMIP6), this paper quantifies the uncertainty of temperature and precipitation estimates in the Tibetan Plateau under the next four shared socioeconomic pathways and typical concentration pathway combination scenarios. Then, the CMIP6 mode output data is biased corrected using the DT method. By comparing the magnitude of the uncertainty before and after DT, the potential of the bias correction method in reducing the uncertainty of temperature and precipitation estimates is discussed. The results show that the correction results of the DT method are closer to the measured values. In the long run, model uncertainty dominates, while the contribution of scenario uncertainty and internal variability is relatively low. The DT method has a good effect on reducing the uncertainty of precipitation prediction, and almost reduces the model uncertainty by 80%, which has little effect on the size of scenario uncertainty but affects the relative contribution of uncertainty. In summary, the use of the DT method for deviation correction can reduce the uncertainty of estimation to a certain extent. Results have important implications for the impact of climate change on water cycles in alpine regions.
, Available online ,
doi: 10.12202/j.0476-0301.2023064
Abstract:
The evaluation of the service function of artificial forest ecosystems is a hot topic in the field of applied ecology, and it is also a demand for high-quality development of digital ecology and forestry,theBadaling forest plantation ecosystem (mixed forest, coniferous forest and broad-leaved forest) as well as shrub forest as the research object, in Beijing． The second type of forest resources inventory data of Beijing (in 2004, 2009, 2014) and Badaling forestry carbon flux which real-time monitoring as data sources, and through field investigation and observation of typical samples as well as sample analysis to evaluate the ecosystem service function． The purpose of this study was to explore the forest management suggestions for optimizing the structure and improving the function of forest ecosystem.The analysis and evaluated results show: from 2004 to 2014, (1) the area growth rate of coniferous forest and shrub forest in Badaling forest farm was 40.3% and 174%, respectively, while that of broadleaved forest and mixed forest decreased to 36.31% and 11.61%, respectively． The forest farm was still dominated by coniferous forest and mixed forest, and these two forest area was 642 hm2 and 632.73 hm2, respectively in 2014． (2) Linden trees in broadleaf forests gradually became the main tree species, and the water conservation in 2014 increased by 1.55 times compared with 2009． As the dominant tree species in mixed forests, the physical amount of water conservation in Pinus tabulara increased by 67% in 2014 compared with 2004． In 2014, the shrub forest showed a large increase, and the physical amount of water conservation increased by about 1 times compared with 2004, and its value also increased accordingly． The functions and values of regulating services which carbon sequestration, oxygen release, negative oxygen ion supply, dust retention and pollutant absorption were in the order of mixed forest highest, coniferous forest follow,broadleaf forest least (P > 0.05).The value of service function of each stand had the same trend as that of functional substance． The soil fixation and fertilizer conservation functions of shrub forest were better than those of the other three stands (mixed forest, coniferous forest, broad-leaved forest, shrub forest), and the nutrient accumulation and biodiversity conservation of mixed forest and coniferous forest were better than those of broad-leaved forest． (3) The contribution of soil conservation (92.9%), biodiversity conservation (4.3%) and water conservation (2.3%) to ecosystem services more than carbon sequestration and oxygen release (0.4%), forest protection (0.04%) and air purification (0.02%)． The contribution of mixed forest and coniferous forest to plantation ecosystem services was greater than that of broad-leaved forest and shrub forest． Thus, stand types and forest area are the main determinants of ecosystem service function of plantation ecosystem． The management of plantation should be guided by soil an water conservation function, on the condition of ensuring biodiversity, attention should be paid to the function of carbon sequestration and sequestration,the existing stand should be adjusted to mixed forest and shrub forest, so as to construct an ideal plantation ecosystem with different age and multi-layer, and gradually improve ecosystem service functions of Badaling plantations in Beijing.
The evaluation of the service function of artificial forest ecosystems is a hot topic in the field of applied ecology, and it is also a demand for high-quality development of digital ecology and forestry,theBadaling forest plantation ecosystem (mixed forest, coniferous forest and broad-leaved forest) as well as shrub forest as the research object, in Beijing． The second type of forest resources inventory data of Beijing (in 2004, 2009, 2014) and Badaling forestry carbon flux which real-time monitoring as data sources, and through field investigation and observation of typical samples as well as sample analysis to evaluate the ecosystem service function． The purpose of this study was to explore the forest management suggestions for optimizing the structure and improving the function of forest ecosystem.The analysis and evaluated results show: from 2004 to 2014, (1) the area growth rate of coniferous forest and shrub forest in Badaling forest farm was 40.3% and 174%, respectively, while that of broadleaved forest and mixed forest decreased to 36.31% and 11.61%, respectively． The forest farm was still dominated by coniferous forest and mixed forest, and these two forest area was 642 hm2 and 632.73 hm2, respectively in 2014． (2) Linden trees in broadleaf forests gradually became the main tree species, and the water conservation in 2014 increased by 1.55 times compared with 2009． As the dominant tree species in mixed forests, the physical amount of water conservation in Pinus tabulara increased by 67% in 2014 compared with 2004． In 2014, the shrub forest showed a large increase, and the physical amount of water conservation increased by about 1 times compared with 2004, and its value also increased accordingly． The functions and values of regulating services which carbon sequestration, oxygen release, negative oxygen ion supply, dust retention and pollutant absorption were in the order of mixed forest highest, coniferous forest follow,broadleaf forest least (P > 0.05).The value of service function of each stand had the same trend as that of functional substance． The soil fixation and fertilizer conservation functions of shrub forest were better than those of the other three stands (mixed forest, coniferous forest, broad-leaved forest, shrub forest), and the nutrient accumulation and biodiversity conservation of mixed forest and coniferous forest were better than those of broad-leaved forest． (3) The contribution of soil conservation (92.9%), biodiversity conservation (4.3%) and water conservation (2.3%) to ecosystem services more than carbon sequestration and oxygen release (0.4%), forest protection (0.04%) and air purification (0.02%)． The contribution of mixed forest and coniferous forest to plantation ecosystem services was greater than that of broad-leaved forest and shrub forest． Thus, stand types and forest area are the main determinants of ecosystem service function of plantation ecosystem． The management of plantation should be guided by soil an water conservation function, on the condition of ensuring biodiversity, attention should be paid to the function of carbon sequestration and sequestration,the existing stand should be adjusted to mixed forest and shrub forest, so as to construct an ideal plantation ecosystem with different age and multi-layer, and gradually improve ecosystem service functions of Badaling plantations in Beijing.
, Available online ,
doi: 10.12202/j.0476-0301.2023051
Abstract:
Superluminous supernovae have been the focus of supernova research for nearly two decades. Their high luminosity makes them of great significance for studying the first-generation stars and the early universe. However, the underlying energy mechanism remains unclear. In this study, we collected 91 hydrogen-poor superluminous supernovae （SLS-I） with well-sampled light curves （LCs）, and extracted their LC characteristics for statistical analysis. Markov Chain Monte Carlo （MCMC） simulations were carried out to reproduce these observables considering three power mechanisms. The constraints combining observations on their energy mechanism were systematically explored. The results show that the average peak absolute magnitude of SLS-I at g band was −21.34 ± 0.8 mag, and the rising and declining time scales were distributed in 7~79 days and 14~114 days, where a strong correlation exists. The simulation results show that both the magnetar and the interaction mechanism can power most SLS-I. Under the interaction framework, the shell-like scenario is preferred based on the comparison with observations. In the future, domestic telescopes and all-sky surveys （such as CSST and SiTian） will detect more superluminous supernovae at high redshift, providing important information for a more comprehensive understanding of massive star evolution and explosions.
Superluminous supernovae have been the focus of supernova research for nearly two decades. Their high luminosity makes them of great significance for studying the first-generation stars and the early universe. However, the underlying energy mechanism remains unclear. In this study, we collected 91 hydrogen-poor superluminous supernovae （SLS-I） with well-sampled light curves （LCs）, and extracted their LC characteristics for statistical analysis. Markov Chain Monte Carlo （MCMC） simulations were carried out to reproduce these observables considering three power mechanisms. The constraints combining observations on their energy mechanism were systematically explored. The results show that the average peak absolute magnitude of SLS-I at g band was −21.34 ± 0.8 mag, and the rising and declining time scales were distributed in 7~79 days and 14~114 days, where a strong correlation exists. The simulation results show that both the magnetar and the interaction mechanism can power most SLS-I. Under the interaction framework, the shell-like scenario is preferred based on the comparison with observations. In the future, domestic telescopes and all-sky surveys （such as CSST and SiTian） will detect more superluminous supernovae at high redshift, providing important information for a more comprehensive understanding of massive star evolution and explosions.
, Available online ,
doi: 10.12202/j.0476-0301.2023046
Abstract:
This review focuses on the demand for innovative research methods in psychology, starting with data collection and analysis, and examines the application trends and potential issues of artificial intelligence technology in psychological research. It also explores the development and application of artificial intelligence technology in various sub-disciplines of psychology, including cognitive neuroscience, social and consumer psychology, psychopathology, and psychometrics. The review highlights the technical support provided by artificial intelligence technology for the transformation of research methods and paradigms in psychology. It also discusses the limitations of data-driven research and the bias of big data, as well as the current interdisciplinary path and future prospects of the intersection of artificial intelligence technology and psychology. Ultimately, the review is aimed to provide a reference for promoting the deep intersection, mutual empowerment, and collaborative development of psychology and artificial intelligence technology.
This review focuses on the demand for innovative research methods in psychology, starting with data collection and analysis, and examines the application trends and potential issues of artificial intelligence technology in psychological research. It also explores the development and application of artificial intelligence technology in various sub-disciplines of psychology, including cognitive neuroscience, social and consumer psychology, psychopathology, and psychometrics. The review highlights the technical support provided by artificial intelligence technology for the transformation of research methods and paradigms in psychology. It also discusses the limitations of data-driven research and the bias of big data, as well as the current interdisciplinary path and future prospects of the intersection of artificial intelligence technology and psychology. Ultimately, the review is aimed to provide a reference for promoting the deep intersection, mutual empowerment, and collaborative development of psychology and artificial intelligence technology.
, Available online ,
doi: 10.12202/j.0476-0301.2023078
Abstract:
The cell cycle is a continuous process of cell division and proliferation in eukaryotes, transmitting genetic materials from parental generation to filial generation． Eukaryotic cells complete cell division and proliferation through periodic regulation at the protein molecular level, and the cell cycle disorder is usually closely related to cancer and other diseases． Protein phosphorylation is a major regulation mode in the process of cell cycle, which can change the molecular structure of protein, affect its interaction with other molecules, and thus regulate the biological activity and function of related molecules． The changes in the phosphorylation and non-phosphorylation states of cell cycle related proteins are like “molecular switches”, finely controlling cell cycle progression and cell division events． The study of multisite phosphorylation for cell cycle related proteins is a hotspot in the field of protein phosphorylation． This article provides a comprehensive review of the phosphorylation modification mechanisms of some important proteins in the process of cell cycle regulation． It summarizes the novel discoveries and breakthroughs in protein phosphorylation modification in the field of cell cycle in recent years, providing reference for further understanding of protein phosphorylation and cell cycle regulation mechanisms.
The cell cycle is a continuous process of cell division and proliferation in eukaryotes, transmitting genetic materials from parental generation to filial generation． Eukaryotic cells complete cell division and proliferation through periodic regulation at the protein molecular level, and the cell cycle disorder is usually closely related to cancer and other diseases． Protein phosphorylation is a major regulation mode in the process of cell cycle, which can change the molecular structure of protein, affect its interaction with other molecules, and thus regulate the biological activity and function of related molecules． The changes in the phosphorylation and non-phosphorylation states of cell cycle related proteins are like “molecular switches”, finely controlling cell cycle progression and cell division events． The study of multisite phosphorylation for cell cycle related proteins is a hotspot in the field of protein phosphorylation． This article provides a comprehensive review of the phosphorylation modification mechanisms of some important proteins in the process of cell cycle regulation． It summarizes the novel discoveries and breakthroughs in protein phosphorylation modification in the field of cell cycle in recent years, providing reference for further understanding of protein phosphorylation and cell cycle regulation mechanisms.
, Available online ,
doi: 10.12202/j.0476-0301.2023084
Abstract:
With a high concentration of population and industries, Guangdong Province is highly dependent on WEF resources, and the contradiction between supply and demand of resources is increasingly prominent． It is of great practical significance to rationally allocate WEF resources and realize sustainable utilization of resources． Based on the complex network method, this study constructed the WEF resource network model of Guangdong Province in 2007, 2012 and 2017． By exploring resource network topology, key nodes and critical paths of the network were discovered, which were the focus of resource optimization allocation． The results show that: （1） WEF resource networks in Guangdong Province had small-world attribute, the energy network had the strongest small-world attribute, and the water resource network had the weakest small-world attribute． The regulation of key nodes and key edges will have a great influence on WEF resource networks． （2） Key nodes such as agriculture, food and tobacco industry, chemical product industry, electricity and heat production and supply industry, construction industry, communication equipment, computer and other electronic equipment manufacturing industry had relatively high strength, and their resource regulation played a significant role in multiple saving of WEF resources in Guangdong Province． （3） The electrical machinery and equipment manufacturing industry, construction industry, communication equipment, computer and other electronic equipment manufacturing industry had hub positions in the WEF resource network, and their resource saving effect could be quickly transmitted to the whole network． （4） Agriculture→food and tobacco industry, agriculture→textile industry, food and tobacco→accommodation and catering industry frequently appeared in the critical paths of WEF resource network． Changing their resources circulation flow could significantly change the critical path or even the circulation flow of the whole WEF resource network.
With a high concentration of population and industries, Guangdong Province is highly dependent on WEF resources, and the contradiction between supply and demand of resources is increasingly prominent． It is of great practical significance to rationally allocate WEF resources and realize sustainable utilization of resources． Based on the complex network method, this study constructed the WEF resource network model of Guangdong Province in 2007, 2012 and 2017． By exploring resource network topology, key nodes and critical paths of the network were discovered, which were the focus of resource optimization allocation． The results show that: （1） WEF resource networks in Guangdong Province had small-world attribute, the energy network had the strongest small-world attribute, and the water resource network had the weakest small-world attribute． The regulation of key nodes and key edges will have a great influence on WEF resource networks． （2） Key nodes such as agriculture, food and tobacco industry, chemical product industry, electricity and heat production and supply industry, construction industry, communication equipment, computer and other electronic equipment manufacturing industry had relatively high strength, and their resource regulation played a significant role in multiple saving of WEF resources in Guangdong Province． （3） The electrical machinery and equipment manufacturing industry, construction industry, communication equipment, computer and other electronic equipment manufacturing industry had hub positions in the WEF resource network, and their resource saving effect could be quickly transmitted to the whole network． （4） Agriculture→food and tobacco industry, agriculture→textile industry, food and tobacco→accommodation and catering industry frequently appeared in the critical paths of WEF resource network． Changing their resources circulation flow could significantly change the critical path or even the circulation flow of the whole WEF resource network.
, Available online ,
doi: 10.12202/j.0476-0301.2023056
Abstract:
Based on multi-source remote sensing data, this study constructs a comprehensive evaluation model of natural environment comfort of urban living with the help of principal component analysis method and take the Beijing-Tianjin-Hebei region as an example to evaluate the changes in natural environment comfort under the background of urban development in 2000,2010 and 2020.The research results show that :1) the over all comfort level of urban residents in the Beijing-Tianjin-Hebei regions gradually improving, as from the city center to the city periphery, with an increase of about 10%; 2)compared with 2000, the comfort level of district and counties in 2020 is also improving yearly, and the number of high-comfort districts and counties has nearly doubled; 3) The change of comfort level in typical cities is generally consistent with the overall change, but there are differences in the speed of improvement due to city functions and scales. This study has certain reference and application value for promoting sustainable development of cities.
Based on multi-source remote sensing data, this study constructs a comprehensive evaluation model of natural environment comfort of urban living with the help of principal component analysis method and take the Beijing-Tianjin-Hebei region as an example to evaluate the changes in natural environment comfort under the background of urban development in 2000,2010 and 2020.The research results show that :1) the over all comfort level of urban residents in the Beijing-Tianjin-Hebei regions gradually improving, as from the city center to the city periphery, with an increase of about 10%; 2)compared with 2000, the comfort level of district and counties in 2020 is also improving yearly, and the number of high-comfort districts and counties has nearly doubled; 3) The change of comfort level in typical cities is generally consistent with the overall change, but there are differences in the speed of improvement due to city functions and scales. This study has certain reference and application value for promoting sustainable development of cities.
Hydrogeomorphic characteristics and runoff relationships of Beichuan River basin in Qinghai Province
, Available online ,
doi: 10.12202/j.0476-0301.2022345
Abstract:
we used runoff observation data of 5 gauging stations to calculate the average annual runoff in the Beichuan River basin, and used 30 m DEM data to extract the hydrogeomorphic characteristic factors related to runoff. The results show the topography of the Beichuan River basin tends to be flat from the upstream to the downstream, and the catchment capacity becomes stronger with the increase of river network development. we completed the correlation analysis between the average annual runoff and the hydrogeomorphic characteristic factors. Screen hydrogeomorphic characteristic factors through collinearity diagnosis, and establish linear regression equation. From the perspective of macro topographic factors, there are two factors with high contribution rates, namely terrain humidity index (50.66%) and surface roughness (44.33%). For micro topographic factors, the order of contribution rate is profile curvature contributes (36.25%), elevation (27.26%) and slope aspect variation (24.31%). Accordingly, for river network form index, node connection rate (54.16%) and area elevation integral (32.95%). Those results provide a in-depth understanding of the relationships between hydrogeomorphic characteristics and runoff, which can provide a reference for studying the hydrogeomorphic characteristics of the upstream and downstream.
we used runoff observation data of 5 gauging stations to calculate the average annual runoff in the Beichuan River basin, and used 30 m DEM data to extract the hydrogeomorphic characteristic factors related to runoff. The results show the topography of the Beichuan River basin tends to be flat from the upstream to the downstream, and the catchment capacity becomes stronger with the increase of river network development. we completed the correlation analysis between the average annual runoff and the hydrogeomorphic characteristic factors. Screen hydrogeomorphic characteristic factors through collinearity diagnosis, and establish linear regression equation. From the perspective of macro topographic factors, there are two factors with high contribution rates, namely terrain humidity index (50.66%) and surface roughness (44.33%). For micro topographic factors, the order of contribution rate is profile curvature contributes (36.25%), elevation (27.26%) and slope aspect variation (24.31%). Accordingly, for river network form index, node connection rate (54.16%) and area elevation integral (32.95%). Those results provide a in-depth understanding of the relationships between hydrogeomorphic characteristics and runoff, which can provide a reference for studying the hydrogeomorphic characteristics of the upstream and downstream.
Display Method:
2023, 59(5): 691-704.
doi: 10.12202/j.0476-0301.2023153
Abstract:
This paper reviews the related research work on“complex network modeling and analysis”published by the School of Systems Science, Beijing Normal University since its establishment in 2013． Firstly, according to different network types, we introduce the important achievements in the field of complex networks theory from the aspects of network structure and dynamics analysis． Secondly, we summarize the main research results of the application of complex networks analysis in socioeconomic systems and earth systems． Finally, we put forward some suggestions on the development direction of complex networks research in the School of Systems Science, Beijing Normal University．
This paper reviews the related research work on“complex network modeling and analysis”published by the School of Systems Science, Beijing Normal University since its establishment in 2013． Firstly, according to different network types, we introduce the important achievements in the field of complex networks theory from the aspects of network structure and dynamics analysis． Secondly, we summarize the main research results of the application of complex networks analysis in socioeconomic systems and earth systems． Finally, we put forward some suggestions on the development direction of complex networks research in the School of Systems Science, Beijing Normal University．
2023, 59(5): 705-715.
doi: 10.12202/j.0476-0301.2023158
Abstract:
Various interpretations and definitions of “new economy” are described in the face of obvious ambiguities in current definition criteria． Changes in the form of economic relations in industries widely recognized as “new economy” are identified, key differences between “new economy” and traditional economy relate to production． The “new economy” industries involve series of changes on the form of production organizations and social relations． Such changes are represented mainly by a set of new elements in the level of relations to production that reflects the future form named by “joint economy”． According to these elements, the “new economy” industries can be clearly and strictly defined． The development level of these elements are used to further propose series of key indicators measuring development level of “new economy”．
Various interpretations and definitions of “new economy” are described in the face of obvious ambiguities in current definition criteria． Changes in the form of economic relations in industries widely recognized as “new economy” are identified, key differences between “new economy” and traditional economy relate to production． The “new economy” industries involve series of changes on the form of production organizations and social relations． Such changes are represented mainly by a set of new elements in the level of relations to production that reflects the future form named by “joint economy”． According to these elements, the “new economy” industries can be clearly and strictly defined． The development level of these elements are used to further propose series of key indicators measuring development level of “new economy”．
2023, 59(5): 716-724.
doi: 10.12202/j.0476-0301.2023172
Abstract:
As a method that converts graph structure into vector representations, graph representation learning has gained significant attention in recent years in various fields such as social networks, biological networks, world trade webs, and computer networks． To document the development of graph representation learning, and to provide a comprehensive overview of different methods and their related applications, the present work summarizes progress in two important categories of graph representation learning: graph embedding and graph neural networks． A detailed overview of several classical algorithms is presented． Application of graph representation learning is introduced in biology, chemistry, and medicine． Challenges and future directions that graph representation learning faces are discussed．
As a method that converts graph structure into vector representations, graph representation learning has gained significant attention in recent years in various fields such as social networks, biological networks, world trade webs, and computer networks． To document the development of graph representation learning, and to provide a comprehensive overview of different methods and their related applications, the present work summarizes progress in two important categories of graph representation learning: graph embedding and graph neural networks． A detailed overview of several classical algorithms is presented． Application of graph representation learning is introduced in biology, chemistry, and medicine． Challenges and future directions that graph representation learning faces are discussed．
2023, 59(5): 725-733.
doi: 10.12202/j.0476-0301.2023049
Abstract:
Focusing on complex systems: a quantitative description is provided for emergence, causality, and causal emergence．The relationship between causality and emergence is elucidated． Two quantitative methods, coarse-graining and information decomposition, are reviewed for characterizing causal emergence． Two causal emergence identification methods based on information decomposition and neural information compression are presented． Basic principles, advantages, disadvantages, and relevant applications of each method are detailed． The framework of causal emergence is defined based on coarse-graining method, which can be applied to discrete dynamical systems． The use of information decomposition method in solving problems relies on redundant information． The proposed indicators based on information decomposition can identify causal emergence in data and find a sufficient condition． The data-driven neural information compression method is scalable and applicable to continuous dynamical systems． It can automatically extract coarse-grained functions at different levels and construct hierarchical dynamics, and identify causal emergence in different types of dynamical systems． Existing methods are improved and applied to identify more complex systems, automate learning groups, and address challenges in general dynamics of large-scale models and other related problems．
Focusing on complex systems: a quantitative description is provided for emergence, causality, and causal emergence．The relationship between causality and emergence is elucidated． Two quantitative methods, coarse-graining and information decomposition, are reviewed for characterizing causal emergence． Two causal emergence identification methods based on information decomposition and neural information compression are presented． Basic principles, advantages, disadvantages, and relevant applications of each method are detailed． The framework of causal emergence is defined based on coarse-graining method, which can be applied to discrete dynamical systems． The use of information decomposition method in solving problems relies on redundant information． The proposed indicators based on information decomposition can identify causal emergence in data and find a sufficient condition． The data-driven neural information compression method is scalable and applicable to continuous dynamical systems． It can automatically extract coarse-grained functions at different levels and construct hierarchical dynamics, and identify causal emergence in different types of dynamical systems． Existing methods are improved and applied to identify more complex systems, automate learning groups, and address challenges in general dynamics of large-scale models and other related problems．
2023, 59(5): 734-739.
doi: 10.12202/j.0476-0301.2023160
Abstract:
This work aims to explain how materials like glass are structured, one of the most important puzzles in the field of complex physical systems． The atomic packing formula in glass materials is found to correlate with lattice structure and symmetry of their crystalline counterparts, this holds well both in numerical and realistic experimental glass systems． This indicates that structure homology also exists between a glassy solid and its parent crystal, leading us to the proposal that, in the study of glass physics and material science, thinking in terms of homology may open new doors to understanding the nature of atomic structures and structure-property relationships in glass materials．
This work aims to explain how materials like glass are structured, one of the most important puzzles in the field of complex physical systems． The atomic packing formula in glass materials is found to correlate with lattice structure and symmetry of their crystalline counterparts, this holds well both in numerical and realistic experimental glass systems． This indicates that structure homology also exists between a glassy solid and its parent crystal, leading us to the proposal that, in the study of glass physics and material science, thinking in terms of homology may open new doors to understanding the nature of atomic structures and structure-property relationships in glass materials．
2023, 59(5): 740-748.
doi: 10.12202/j.0476-0301.2023150
Abstract:
Urban heavy trucks are an important part of urban freight transportation system． The study of urban heavy trucks mobility network characteristics is of potential reference value for urban freight transportation system planning and management． Statistical characteristics of heavy trucks mobility networks in four typical cities in China are analyzed in this paper． Using the trip chains extracted from the heavy trucks GPS track data, individual heavy trucks mobility networks are established and then merged into population mobility network． It is found that in individual mobility networks, travel motif composed of connected edges of individual mobility networks has obvious heterogeneity characteristics, the node return steps approximately obey truncated power-law distribution, the node weights approximately obey Zipf’s law, the number of network nodes has sublinear growth characteristics． It is found that in population mobility networks of heavy trucks, node weights approximately obey power-law tail distribution, edge weights approximately obey power-law distribution, mobility distances approximately obey exponential distribution, relationship between edge weights, node weights and distances approximately obeys social gravity law． The underlying mechanisms of these statistical characteristics are analyzed． Theoretical model of reproducing these statistical characteristics, time-varying characteristics analysis of individual and population mobility networks, construction of multi-layer interdependent complex networks of freight systems, etc． are preliminarily discussed．
Urban heavy trucks are an important part of urban freight transportation system． The study of urban heavy trucks mobility network characteristics is of potential reference value for urban freight transportation system planning and management． Statistical characteristics of heavy trucks mobility networks in four typical cities in China are analyzed in this paper． Using the trip chains extracted from the heavy trucks GPS track data, individual heavy trucks mobility networks are established and then merged into population mobility network． It is found that in individual mobility networks, travel motif composed of connected edges of individual mobility networks has obvious heterogeneity characteristics, the node return steps approximately obey truncated power-law distribution, the node weights approximately obey Zipf’s law, the number of network nodes has sublinear growth characteristics． It is found that in population mobility networks of heavy trucks, node weights approximately obey power-law tail distribution, edge weights approximately obey power-law distribution, mobility distances approximately obey exponential distribution, relationship between edge weights, node weights and distances approximately obeys social gravity law． The underlying mechanisms of these statistical characteristics are analyzed． Theoretical model of reproducing these statistical characteristics, time-varying characteristics analysis of individual and population mobility networks, construction of multi-layer interdependent complex networks of freight systems, etc． are preliminarily discussed．
2023, 59(5): 749-757.
doi: 10.12202/j.0476-0301.2023069
Abstract:
A decentralized stabilization method based on adaptive dynamic programming (ADP) is proposed for a class of interconnected nonlinear systems with constant-value state constraints． A barrier function is introduced so that the original system is converted into an unconstrained system by coordinate transformation． Auxiliary subsystems and improved cost functions enabled transformation of robust decentralized stabilization problem into an optimal regulation problem． The Hamilton-Jacobi-Bellman (HJB) equation is solved by policy iteration after constructing a local critic neural network for each auxiliary subsystem so that an approximate optimal stabilization control law is obtained． According to the Lyapunov stability theory, the proposed method can drive estimation errors of closed-loop interconnected system and local critic neural networks to be ultimately uniformly bounded dynamically． Numerical simulations validate the effectiveness of proposed decentralized stabilization method．
A decentralized stabilization method based on adaptive dynamic programming (ADP) is proposed for a class of interconnected nonlinear systems with constant-value state constraints． A barrier function is introduced so that the original system is converted into an unconstrained system by coordinate transformation． Auxiliary subsystems and improved cost functions enabled transformation of robust decentralized stabilization problem into an optimal regulation problem． The Hamilton-Jacobi-Bellman (HJB) equation is solved by policy iteration after constructing a local critic neural network for each auxiliary subsystem so that an approximate optimal stabilization control law is obtained． According to the Lyapunov stability theory, the proposed method can drive estimation errors of closed-loop interconnected system and local critic neural networks to be ultimately uniformly bounded dynamically． Numerical simulations validate the effectiveness of proposed decentralized stabilization method．
2023, 59(5): 758-762.
doi: 10.12202/j.0476-0301.2023157
Abstract:
Diffusion is crucial for biomolecule transportation in cells and is the physical basis for various life processes． Due to complexity of intracellular microenvironment, biomolecule diffusion inside cells exhibits novel dynamic characteristics such as anomalous diffusion, spatial heterogeneity, and anisotropy． The relationship between intracellular diffusion dynamics and spatial dimensions of intracellular microenvironment is not well understood． Live-cell single-molecule fluorescence tracking techniques were used in this study to investigate the diffusion of quantum dots inside cells, to quantitatively analyze dynamic features of intracellular quasi-two-dimensional diffusion and quasi-one-dimensional diffusion in filopodia． Compared to intracellular quasi-two-dimensional diffusion, diffusion within filopodia was found to exhibit higher rate, and the phenomenon of diffusion acceleration was inversely proportional to the diameter of the filopodia, suggesting that the filopodia is a more efficient pathway for intracellular substance transport． The relationship between intracellular diffusion dynamics and spatial dimensions of intracellular environment is elucidated, mechanisms of cellular regulation of biomolecule transport through subcellular structures are clarified．
Diffusion is crucial for biomolecule transportation in cells and is the physical basis for various life processes． Due to complexity of intracellular microenvironment, biomolecule diffusion inside cells exhibits novel dynamic characteristics such as anomalous diffusion, spatial heterogeneity, and anisotropy． The relationship between intracellular diffusion dynamics and spatial dimensions of intracellular microenvironment is not well understood． Live-cell single-molecule fluorescence tracking techniques were used in this study to investigate the diffusion of quantum dots inside cells, to quantitatively analyze dynamic features of intracellular quasi-two-dimensional diffusion and quasi-one-dimensional diffusion in filopodia． Compared to intracellular quasi-two-dimensional diffusion, diffusion within filopodia was found to exhibit higher rate, and the phenomenon of diffusion acceleration was inversely proportional to the diameter of the filopodia, suggesting that the filopodia is a more efficient pathway for intracellular substance transport． The relationship between intracellular diffusion dynamics and spatial dimensions of intracellular environment is elucidated, mechanisms of cellular regulation of biomolecule transport through subcellular structures are clarified．
2023, 59(5): 763-768.
doi: 10.12202/j.0476-0301.2023149
Abstract:
The global COVID-19 epidemic and Russia-Ukraine conflict have seriously affected global food trade． How importing countries take proper measures to deal with food import shocks is a key issue to control risks of international food trade． An evolutionary game model for international food trade network was developed in this paper, with reference to the 2018 global rice import and export trade data． A key parameter of import strategies, historical dependence, was proposed, and its impact on food import shocks was analyzed． Low historical dependence was found to lead to a high trade concentration and increase the probability of high-intensity shocks． However, high historical dependence would increase the probability of shocks of medium or above intermediate intensity． To control the risk of food import shocks, importing countries need to maintain their historical dependence at moderate levels．
The global COVID-19 epidemic and Russia-Ukraine conflict have seriously affected global food trade． How importing countries take proper measures to deal with food import shocks is a key issue to control risks of international food trade． An evolutionary game model for international food trade network was developed in this paper, with reference to the 2018 global rice import and export trade data． A key parameter of import strategies, historical dependence, was proposed, and its impact on food import shocks was analyzed． Low historical dependence was found to lead to a high trade concentration and increase the probability of high-intensity shocks． However, high historical dependence would increase the probability of shocks of medium or above intermediate intensity． To control the risk of food import shocks, importing countries need to maintain their historical dependence at moderate levels．
2023, 59(5): 769-775.
doi: 10.12202/j.0476-0301.2023155
Abstract:
In predictive saccade tasks within precise time intervals, the reaction time of macaque exhibits a bimodal distribution． To investigate this phenomenon further, a parallel neural circuit model that includes the lateral intraparietal area (LIP), supplementary eye fields (SEF) in the cerebral cortex, the basal ganglia (BG) and superior colliculus (SC) is proposed in this study． Model simulations successfully reproduced a bimodal distribution． Competitive interaction among neuronal populations in SEF and LIP regions was found to give rise to two peaks． SEF region primarily was found to handle predictive saccades and dominated the first peak, while LIP region was found to be responsible for visually evoked reactive saccades and dominated the second peak． Key parameters that influence morphology of bimodal distribution are discussed． The process of time expectation from the perspective of computational neuroscience is explored．
In predictive saccade tasks within precise time intervals, the reaction time of macaque exhibits a bimodal distribution． To investigate this phenomenon further, a parallel neural circuit model that includes the lateral intraparietal area (LIP), supplementary eye fields (SEF) in the cerebral cortex, the basal ganglia (BG) and superior colliculus (SC) is proposed in this study． Model simulations successfully reproduced a bimodal distribution． Competitive interaction among neuronal populations in SEF and LIP regions was found to give rise to two peaks． SEF region primarily was found to handle predictive saccades and dominated the first peak, while LIP region was found to be responsible for visually evoked reactive saccades and dominated the second peak． Key parameters that influence morphology of bimodal distribution are discussed． The process of time expectation from the perspective of computational neuroscience is explored．
2023, 59(5): 776-784.
doi: 10.12202/j.0476-0301.2023159
Abstract:
Neuroimaging studies of human brain connectomics have revealed abnormal functional connectivity patterns in individuals with autism spectrum disorder (ASD)． Previous works primarily focused on static functional connectivity, but diversity in functional connectivity patterns and their abnormal features in ASD remains to be elucidated． Statistical eigen-microstate analysis of resting-state functional magnetic resonance imaging data from 45 children (6-10 years old, all males) was performed in this study, which included 27 children with ASD and 18 healthy controls． It was found that certain (i.e., six in total) leading basic modes made a dominant contribution to whole-brain spontaneous activity for both healthy children and children with ASD． Each leading mode showed distinct spatial distribution of brain activity and corresponded to functional system-dependent connectivity pattern． Compared to healthy developing children, children with ASD showed altered functional connectivity patterns for the first, second, and fourth leading modes, primarily involving connectivity within the visual network and connectivity between the dorsal attention network and the frontoparietal, default-mode, and visual networks． These data suggest that multiple abnormal connectivity patterns simultaneously occur in functional brain networks of children with ASD, offering novel insights into mechanisms underlying brain network alterations in autism．
Neuroimaging studies of human brain connectomics have revealed abnormal functional connectivity patterns in individuals with autism spectrum disorder (ASD)． Previous works primarily focused on static functional connectivity, but diversity in functional connectivity patterns and their abnormal features in ASD remains to be elucidated． Statistical eigen-microstate analysis of resting-state functional magnetic resonance imaging data from 45 children (6-10 years old, all males) was performed in this study, which included 27 children with ASD and 18 healthy controls． It was found that certain (i.e., six in total) leading basic modes made a dominant contribution to whole-brain spontaneous activity for both healthy children and children with ASD． Each leading mode showed distinct spatial distribution of brain activity and corresponded to functional system-dependent connectivity pattern． Compared to healthy developing children, children with ASD showed altered functional connectivity patterns for the first, second, and fourth leading modes, primarily involving connectivity within the visual network and connectivity between the dorsal attention network and the frontoparietal, default-mode, and visual networks． These data suggest that multiple abnormal connectivity patterns simultaneously occur in functional brain networks of children with ASD, offering novel insights into mechanisms underlying brain network alterations in autism．
2023, 59(5): 785-795.
doi: 10.12202/j.0476-0301.2023154
Abstract:
Population is a complex system, and population migration is a typical issue that has long been a concern of complex systems science. Based on the data of inter-provincial bilateral migration between provinces in China from the last three censuses, a complexity exploration study was conducted. 1) regional population migration patterns and their evolution in China are verified. 2) Based on multilateral probability migration model, a quantitative study is conducted on the barriers to inter-provincial population migration in China. Regression analysis reveals fundamental elements that affect regional mobility barriers, which can explain about 60% of all migrations．The influence of geographical distance, development index of migration destination and origin, housing prices of migration destination and origin on regional migration is found to be significant. Finally, a comprehensive analysis of pushing and pulling forces of five hot migration destinations (Beijing, Shanghai, Guangdong, Zhejiang, and Jiangsu) is conducted, similarities and differences among these destinations are discussed．
Population is a complex system, and population migration is a typical issue that has long been a concern of complex systems science. Based on the data of inter-provincial bilateral migration between provinces in China from the last three censuses, a complexity exploration study was conducted. 1) regional population migration patterns and their evolution in China are verified. 2) Based on multilateral probability migration model, a quantitative study is conducted on the barriers to inter-provincial population migration in China. Regression analysis reveals fundamental elements that affect regional mobility barriers, which can explain about 60% of all migrations．The influence of geographical distance, development index of migration destination and origin, housing prices of migration destination and origin on regional migration is found to be significant. Finally, a comprehensive analysis of pushing and pulling forces of five hot migration destinations (Beijing, Shanghai, Guangdong, Zhejiang, and Jiangsu) is conducted, similarities and differences among these destinations are discussed．
2023, 59(5): 796-805.
doi: 10.12202/j.0476-0301.2023156
Abstract:
This review aims to comprehensively recapitulate the latest scientific advancements in methods from statistical physics, complex systems science (such as critical phenomena, network theory, percolation, critical point analysis, and entropy), and machine learning in the research and application of complex Earth systems． The integration of these methods provides new insights and perspectives for understanding the dynamics of Earth systems． By applying these methods, we can better model and analyze the interrelationships and nonlinear effects in Earth systems, revealing the system’s complexity and critical properties．
This review aims to comprehensively recapitulate the latest scientific advancements in methods from statistical physics, complex systems science (such as critical phenomena, network theory, percolation, critical point analysis, and entropy), and machine learning in the research and application of complex Earth systems． The integration of these methods provides new insights and perspectives for understanding the dynamics of Earth systems． By applying these methods, we can better model and analyze the interrelationships and nonlinear effects in Earth systems, revealing the system’s complexity and critical properties．
2023, 59(5): 806-811.
doi: 10.12202/j.0476-0301.2023054
Abstract:
A multi-period public goods game model with collective risk is established, based on “Intended Nationally Determined Contributions” and “Global Stocktake” mechanisms proposed in the Paris Agreement． Subgame perfect Nash equilibrium method is applied to analyze whether and how to achieve emission reduction target when developed and developing countries have heterogeneity in endowment, emission reduction costs, and climate risk． If the weighted average of climate risk of all countries reaches or exceeds the coefficient of emission reduction target, then global cooperation can be the outcome of a subgame perfect Nash equilibrium through the Grim strategy． Further, emission reduction period and numbers of developed and non-developed countries do not affect global cooperation．
A multi-period public goods game model with collective risk is established, based on “Intended Nationally Determined Contributions” and “Global Stocktake” mechanisms proposed in the Paris Agreement． Subgame perfect Nash equilibrium method is applied to analyze whether and how to achieve emission reduction target when developed and developing countries have heterogeneity in endowment, emission reduction costs, and climate risk． If the weighted average of climate risk of all countries reaches or exceeds the coefficient of emission reduction target, then global cooperation can be the outcome of a subgame perfect Nash equilibrium through the Grim strategy． Further, emission reduction period and numbers of developed and non-developed countries do not affect global cooperation．
2023, 59(5): 812-821.
doi: 10.12202/j.0476-0301.2023151
Abstract:
The core ideas and concepts of educational system science are introduced, aiming to answer some core educational research questions with systems science approach, especially scientific research methods and system thinking． With a road map starting from accomplished projects to on-going and envisioned research work and practices, the formation and development of educational system science, an emerging branch of both systems science and education are proposed． From the system science point of view, educational system is a system with multiple entities of diverse types connected via relationships of diverse types, with ideally an overall function to society, to help students learn so that they will be able to create and creatively use knowledge, or to appreciate the creation and creative use of knowledge． A system with multiple parts and relations with overall function is typical object of research interest of systems science． Thus, education does need systems science．
The core ideas and concepts of educational system science are introduced, aiming to answer some core educational research questions with systems science approach, especially scientific research methods and system thinking． With a road map starting from accomplished projects to on-going and envisioned research work and practices, the formation and development of educational system science, an emerging branch of both systems science and education are proposed． From the system science point of view, educational system is a system with multiple entities of diverse types connected via relationships of diverse types, with ideally an overall function to society, to help students learn so that they will be able to create and creatively use knowledge, or to appreciate the creation and creative use of knowledge． A system with multiple parts and relations with overall function is typical object of research interest of systems science． Thus, education does need systems science．
2023, 59(5): 822-829.
doi: 10.12202/j.0476-0301.2023152
Abstract:
Combined neural network model LSTM-IPSO-BP was applied to study factors influencing the intensity and change trend in China’s carbon emission driven by future population and structure changes． It is found that continuous decline in China’s population in the future will lead to increased carbon emission intensity, the rate of population decline is positively correlated with carbon emission intensity． Although improved urbanization level will reduce carbon emission intensity, the slowdown of China’s future urbanization process will increase pressure on carbon emission reduction． Under current policies and development trend of various influencing factors, especially population and structural changes, it is difficult for China to achieve a carbon peak before 2030, therefore the Chinese government needs to strengthen the control of carbon emission policies in the following decade．
Combined neural network model LSTM-IPSO-BP was applied to study factors influencing the intensity and change trend in China’s carbon emission driven by future population and structure changes． It is found that continuous decline in China’s population in the future will lead to increased carbon emission intensity, the rate of population decline is positively correlated with carbon emission intensity． Although improved urbanization level will reduce carbon emission intensity, the slowdown of China’s future urbanization process will increase pressure on carbon emission reduction． Under current policies and development trend of various influencing factors, especially population and structural changes, it is difficult for China to achieve a carbon peak before 2030, therefore the Chinese government needs to strengthen the control of carbon emission policies in the following decade．
Since 1956 Bimonthly
Supervisor: Ministry of Education of P.R.C.
Sponsors by: Beijing Normal University
Director: SONG Changqing
Chief Editor:BAO Jiguang
Email:jbnuns_sub@bnu.edu.cn
ISSN 0476-0301
CN 11-1991/N
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