Transition Path Research Articles

Splitting probabilities and mean first-passage times across multiple thresholds of jump-and-drift transition paths

Splitting probabilities and mean first-passage times across multiple thresholds of jump-and-drift transition paths

Roadmap towards clean and low-carbon heating to 2060: The case of northern urban region in China

With higher requirements for living comfort, heating demand continue rising. Currently, heating in northern urban region is still dominated by coal consumption, which combined with inefficient equipment systems, presents a severe challenge for building sector to achieve net-zero emissions. In this study, by predicting final heating demand in northern urban region to 2060 and inputting it into Northern Urban Region Heating System Model, we solve the production structure of heating technologies with cost-optimal way and then account for energy consumption and carbon emissions. Finally, the energy conservation and emission reduction potential of clean and low-carbon strategies were analyze. The results show that the share of clean heating technologies is 91%, 97%, and 100%, and coal-fired CHP technology still accounts for approximately 37%–46% in 2060 under different scenarios. In two abatement scenarios, heating energy consumption decreased by 31% and 55%, and carbon emissions reduced by 71% and 88% by 2060. From the energy conservation and emission reduction potential analysis, clean heating technology application and low-carbon technology application will contribute the main force to future. This research is of great significance, on the one hand, it provides a theoretical basis for the modeling heating system. On the other hand, it provides feasible heating transition paths, which assist building sector achieving net-zero emissions.

Carbon (CO2) emission and food availability convergence in the Niger Basin region: Insight from a club clustering algorithm

The study employed the Phillips and Sul log-t convergence test to analyse the degree of convergence for the Niger Basin region (NBR) countries in terms of per capita carbon emission and food availability. We found that, between the years 1986 and 2020, the Niger Basin region produced 13.5% less food per person than it did during the base period of 2004 to 2006. This study also found a strong convergence among the NBR countries on per capita food production. The result for the region’s convergence of per capita carbon emission was rejected. The non-convergence of the entire sample, and the presence of the different subgroup convergence clubs for per capita CO2 emission for the region, implies that individual factors characterise the NBR countries in terms of per capita CO2 emissions, which in turn determine an idiosyncratic course of their transition path for per capita CO2 emission policies. Considering that the transboundary river basin links nine countries, this study recommends that the NBR countries formulate and implement CO2 emission policies based on cluband country-specific policies to achieve convergence in relation to a concerted food security threat facing the region.

Full-cycle chains of strategic mineral raw materials – new opportunities for the Russian North

The paper analyzes the relationship between the global energy transition and the possibilities of Russia and its northern regions to enter the world markets for strategic raw materials and components necessary for a green economy. The acceleration of the energy transition in developed countries leads to an increased demand for strategic metals and their compounds (primarily REM and lithium). Solar and wind energy are becoming the largest energy producers in the world. Thanks to these processes, countries with technological competencies and resource capabilities in the field of «green» metals can significantly strengthen the potential of their own industries[1]producers and consumers of strategic raw materials. The role of technological value chains localized within the country is growing. A feature of Russia is the imbalance between the extraction of strategic mineral raw materials and the production of high-tech products based on it. This means the fragmented nature of value chains. The directions of the evolutionary path of transition to the interaction of different participants in the chain are proposed based on the formation of full-cycle chains focused on creating demand for high-tech raw materials within the country. Thus, the deposits of strategic raw materials in the northern regions of Russia can and should be based on chains «from ore mining to the production of high-tech products».

Reducing the Cost of Neural Network Potential Generation for Reactive Molecular Systems.

Although machine learning potentials have recently had a substantial impact on molecular simulations, the construction of a robust training set can still become a limiting factor, especially due to the requirement of a reference ab initio simulation that covers all the relevant geometries of the system. Recognizing that this can be prohibitive for certain systems, we develop the method of transition tube sampling that mitigates the computational cost of training set and model generation. In this approach, we generate classical or quantum thermal geometries around a transition path describing a conformational change or a chemical reaction using only a sparse set of local normal mode expansions along this path and select from these geometries by an active learning protocol. This yields a training set with geometries that characterize the whole transition without the need for a costly reference trajectory. The performance of the method is evaluated on different molecular systems with the complexity of the potential energy landscape increasing from a single minimum to a double proton-transfer reaction with high barriers. Our results show that the method leads to training sets that give rise to models applicable in classical and path integral simulations alike that are on par with those based directly on ab initio calculations while providing the computational speedup we have come to expect from machine learning potentials.

Quadruped Rotary Galloping Gait Pattern within a Constant Radius Bend Using Accelerometry

This paper provides an initial investigation of quadruped rotary galloping gait patterns using data from racing greyhounds as they navigate their way around a constant radius bend. This study reviewed actual race data collected over a five month period from 2986 racing greyhounds. Using numerical dynamics modelling and value range analysis important factors were identified and analysed. By cleaning and synthesising simple X and Y data and also processing data for accuracy greyhound motion path dynamics results were produced for analysis. The results show that the galloping path greyhounds took going into the bend was different from the path coming out of the bend. It also shows that more than 50% of the greyhounds naturally optimised their path for a longer transition while minimising jerk when entering and exiting the bend. This research verified that individual greyhounds naturally chose different path transition lengths for accommodating their dynamic conditions. Finally, it was found that the greyhound galloping path dynamics state is less intense during the second half of the bend.

Enhanced spall strength of single crystal aluminum by temperature rise mitigation and structural phase transition under shock pulse

Investigating the spalling behavior is beneficial for the microscale modeling of impact failure. However, the correlation between pulse shape and spallation remains elusive due to limited experimental methods. Here, we simulate the shock deformation and spalling behavior of [100] single-crystal aluminum by Molecular Dynamics under equivalent ramp waves, square waves, and decaying shock waves. The synergistic effects of structural transition and thermodynamic path from the pulse shape affect the systems' fracture. Despite the intersecting influences of spall mechanisms like defects dominating heterogeneous void nucleation, pulse shape primarily affects the spall strength by influencing the compression temperature rise. Higher spall strength σsp and milder injuries in a wide range are achieved by the ramp wave loading pattern through gradual compression with subtle temperature softening. Additionally, pulse shape regulates the evolution of damage through wave propagation and applied tensile strain rates, in which a ramp wave causes rapid and a decaying shock wave delays the coalescence of voids. This study provides new insight for predicting the dynamic failure of metal materials.

Pathways of hLL-3717-29 Aggregation Give Insight into the Mechanism of α-Amyloid Formation.

α-amyloids present a novel self-assembly principle that can be utilized to prepare functional biomaterials. Evidence of α-amyloid formation in the active core of the human LL-37 protein (comprising residues 17 to 29) was associated with this peptide's membranolytic property. Though mechanistic pathways of β-amyloid formation are known, such studies are scarce in α-amyloids. Modern computational techniques allow such mechanistic studies in molecular detail. Here, we propose aggregation pathways in hLL-3717-29 through molecular dynamics simulations. We first identified oligomers among peptides based on a distance criterion. The distribution of oligomers was then used to build Markov state models from which pathways were obtained using the framework of transition path theory. We checked the structural stability of the peptides during oligomerization, which is crucial from their functional point of view. We also investigated the key residues that participate in oligomer formation, the interactions between them, and the effect of residue mutations on the binding free energy of the peptides. Our findings suggest that larger oligomers are produced from the association of smaller and intermediate oligomers. The peptides retain their helical structure during aggregation with transient occurrences of 3-10 helix and turns. Hydrophobic interactions are vital in the aggregation of these peptides with Ile24 playing a crucial role. Mutation of this residue to alanine decreases the peptides' binding free energy, resulting in reduced aggregation tendency.

Characteristics and Variations in Korea through the Lens of Net-Zero Carbon Transformation in Cities

As climate issues become more severe, the necessity and importance of urban transformation are being widely recognized, and the breadth and depth of research in various disciplines of social sciences to promote net-zero carbon (NZC) transformation in cities is increasing. In this study, between 2015 and 2021, 17 major cities and administrative regions in Korea from were taken as the target and based on the driving force-pressure-state-impact-response (DPSIR) model, a framework of 23 indicators of energy, environment, and economic systems (3ES) was constructed through the coupling coordination degree (CCD) assessment system. The development level, development speed, coordination index of subsystems, and coupled coordination relationship were analyzed successively. Finally, a gray correlation model was adopted to extract the 3ES of each city and their key driving factors. The findings indicate that: (1) There is a phenomenon of high coupling and low coordination within the subsystem, with the environmental factors layer being the most critical concern. (2) The overall coupling of the system has improved continuously since 2015, but it is still at the moderate coupling stage, owing to the long-term nature of system contradictions and processing lags. (3) The driving causes of urban transformation have shifted from economic to environmental restrictions, resulting in noticeable regional differences later in the study period and a rise in the necessity for hierarchical zoning governance. Finally, based on the perspective of restricted subsystems and the consolidation of the 3ES coordination relationship, this study demonstrates the significant relationship between environmental protection, energy transition, and economic development, thus enriching the associated literature at the periphery. It also provides a theoretical foundation for investigating the transition path of NZC cities, thus enhancing research in this area.

Unveiling the nexus and promoting integration of diverse factors: Prospects of big data-driven artificial intelligence technology in achieving carbon neutrality in Chongming District

Climate change is one of the most pressing challenges facing the world today. The large amount of greenhouse gas emissions produced by human activities, especially the emission of carbon dioxide, is an important driving factor behind climate issues. Under the background of China’s “3060” decarbonization goal”, Chongming District in Shanghai is actively promoting the construction of a world-class ecological island and is committed to creating a carbon–neutral demonstration zone with global influence. However, Chongming District faces challenges as the mechanism of carbon-neutrality transition path remains unclear. The data related to evaluating carbon neutrality status are heterogeneous from multiple sources. It is difficult to effectively implement relevant evaluation and response measures, impeding the progress of its low-carbon transformation. In response to the aforementioned challenges, this paper will propose and discuss the potential methods based on the new generation of information technology, represented by big data and artificial intelligence. These technologies aim to facilitate the integration of diverse factors, including carbon, and explore the nexus among them, thus exploring pathways for low-carbon transformation, and ultimately achieving decarbonization goal in Chongming District. Hopefully, the research conducted in this paper will contribute to the efforts of China and the global community in addressing carbon-related challenges and advancing towards a more sustainable and low-carbon future.

Multinational corporations’ capital allocation decisions across asymmetric risk locations: intertemporal equilibrium and optimal transitional adjustment paths

Abstract Multinational corporations operate across locations with different risk profiles. We examine how multinational corporations address the optimal allocation of capital across multiple locations and analyse the transition path to the intertemporal equilibrium. Our model considers returns, risks and adjustment costs to reflect the dynamics of allocating capital assets across locations over time, as well as the mix of assets across locations in equilibrium. Variational calculus is employed to show that the model confirms standard expectations that where a location’s rates of return on assets increase, or adjustment costs decrease, equilibrium capital allocation and transitional capital flows to that location will increase. Symmetrically, rising (falling) risk increases (decreases) the proportion of the capital asset holdings of a location. The crucial insight is that for the transitional dynamics to intertemporal equilibrium, the optimal relative capital flow response to changes in risk can generate relative portfolio allocations that may initially move in the opposite direction to that implied by the stock equilibrium. Specifically, an increase in risk for the high-risk location may initially result in an increase in the relative capital asset flow to the high-risk location relative to the low-risk location. Empirical research must account for the possibility of non-monotonicity in asset allocation flows to avoid misspecification. Moreover, policy makers will have to anticipate possible pressure for reversal resulting from short-term worsening capital flows. These reflections are mirrored in recent research calls for separating structural and transition effects of institutional change on the investment decisions by multinational corporations.

Controlling brain dynamics: Landscape and transition path for working memory.

Understanding the underlying dynamical mechanisms of the brain and controlling it is a crucial issue in brain science. The energy landscape and transition path approach provides a possible route to address these challenges. Here, taking working memory as an example, we quantified its landscape based on a large-scale macaque model. The working memory function is governed by the change of landscape and brain-wide state switching in response to the task demands. The kinetic transition path reveals that information flow follows the direction of hierarchical structure. Importantly, we propose a landscape control approach to manipulate brain state transition by modulating external stimulation or inter-areal connectivity, demonstrating the crucial roles of associative areas, especially prefrontal and parietal cortical areas in working memory performance. Our findings provide new insights into the dynamical mechanism of cognitive function, and the landscape control approach helps to develop therapeutic strategies for brain disorders.

Adulthood status and its associations with stress and well-being among Chinese emerging adults: A person-centred approach.

With the implementation of China's one-child policy and the increasing living costs, a large number of young people are expected to postpone reaching adulthood. However, little research has explored the patterns of Chinese young people's transition to adulthood. Using a person-centred approach, the current study examined the commonly accepted markers of adulthood status endorsed and attained by 1203 Chinese emerging adults aged 18-29 years. We further compared the distinct adulthood statuses with regard to perceptions of stress and well-being. Latent profile analysis identified four adulthood status profiles: diffused (16.0%), moratorium (45.3%), transitional (23.3%) and achieved (15.4%). Females, those who had no job or came from low family socioeconomics, were more likely to be in the moratorium status. Compared to the other two profiles, participants in diffused and moratorium profiles reported higher levels of perceived stress and lower well-being. These results suggest that there are distinct profiles of Chinese emerging adults on the transition path to adulthood, with a large proportion of them not yet reaching adulthood, and that different statuses of adulthood may be associated with different psychological outcomes.

Quantifying cancer cell plasticity with gene regulatory networks and single-cell dynamics.

Phenotypic plasticity of cancer cells can lead to complex cell state dynamics during tumor progression and acquired resistance. Highly plastic stem-like states may be inherently drug-resistant. Moreover, cell state dynamics in response to therapy allow a tumor to evade treatment. In both scenarios, quantifying plasticity is essential for identifying high-plasticity states or elucidating transition paths between states. Currently, methods to quantify plasticity tend to focus on 1) quantification of quasi-potential based on the underlying gene regulatory network dynamics of the system; or 2) inference of cell potency based on trajectory inference or lineage tracing in single-cell dynamics. Here, we explore both of these approaches and associated computational tools. We then discuss implications of each approach to plasticity metrics, and relevance to cancer treatment strategies.

Micromagnetics simulations and phase transitions of ferromagnetics with Dzyaloshinskii–Moriya interaction

Magnetic skyrmions widely exist in a diverse range of magnetic systems, including chiral magnets with a non-centrosymmetric structure characterized by Dzyaloshinkii–Moriya interaction (DMI). In this study, we propose a generalized semi-implicit backward differentiation formula projection method, enabling the simulations of the Landau–Lifshitz (LL) equation in chiral magnets in a typical time step-size of 1 ps, markedly exceeding the limit subjected by the reported numerical methods of typically 0.1 ps. Using micromagnetics simulations, we show that the LL equation with strong DMI reveals an intriguing dynamic instability in magnetization configurations as the damping varies. Both the isolated skyrmionium and skyrmionium clusters can be consequently produced using a simple initialization strategy and a specific damping parameter. Assisted by the string method, the transition path between skyrmion and skyrmionium, along with the escape of a skyrmion from the skyrmion clusters, are then thoroughly examined. The numerical methods developed in this work not only provide a reliable paradigm to investigate the skyrmion-based textures and their transition paths, but also facilitate the understandings for magnetization dynamics in complex magnetic systems.

Conditioning Boltzmann generators for rare event sampling

Understanding the dynamics of complex molecular processes is often linked to the study of infrequent transitions between long-lived stable states. The standard approach to the sampling of such rare events is to generate an ensemble of transition paths using a random walk in trajectory space. This, however, comes with the drawback of strong correlations between subsequently sampled paths and with an intrinsic difficulty in parallelizing the sampling process. We propose a transition path sampling scheme based on neural-network generated configurations. These are obtained employing normalizing flows, a neural network class able to generate statistically independent samples from a given distribution. With this approach, not only are correlations between visited paths removed, but the sampling process becomes easily parallelizable. Moreover, by conditioning the normalizing flow, the sampling of configurations can be steered towards regions of interest. We show that this approach enables the resolution of both the thermodynamics and kinetics of the transition region for systems that can be sampled using exact-likelihood generative models.

Effect of normal magnetic field on the exact coherent state of channel flow at large Reynolds number

Laminar-turbulent subcritical transition has been always a hot issue in fluid mechanics. Exact coherent states are important for predicting the path of transition and understanding the cycle of turbulent self-sustaining process. One of the most common methods of investigating subcritical transition is dynamical system method and many different forms of invariant solutions have been obtained in many shear flows. In order to study the effect of magnetic field on the exact coherent state of channel flow at large Reynolds number, the direct numerical simulation combined with bisection method is used to calculate the exact coherent state-periodic orbit solution with different magnetic field strength at Re ⩾ 9000, and the structure and morphology in the flow field are compared. The results show that the magnetic field strength does not change the structure and shape of the solution and the scaling law between the transition threshold and Reynolds number does not change significantly, which shows obviously self-similarity. As the magnetic field strength increases, the period of the exact coherent state decreases and the perturbation energy in each direction exhibits periodical oscillation changes. In addition the shape of the amplitude curve also changes due to the magnetic field effect. The above results show that the magnetic field has a certain inhibition effect on the disturbance at large Reynolds number, and the flow field remains relatively stable.

Quench dynamics of edge states in a finite extended Su-Schrieffer-Heeger system.

We examine the quench dynamics of an extended Su-Schrieffer-Heeger (SSH) model involving long-range hopping that can hold multiple topological phases. Using winding number diagrams to characterize the system's topological phases geometrically, it is shown that there can be multiple winding number transition paths for a quench between two topological phases. The dependence of the quench dynamics is studied in terms of the survival probability of the fermionic edge modes and postquench transport. For two quench paths between two topological regimes with the same initial and final topological phase, the survival probability of edge states is shown to be strongly dependent on the winding number transition path. This dependence is explained using energy band diagrams corresponding to the paths. Following this, the effect of the winding number transition path on transport is investigated. We find that the velocities of maximum transport channels varied along the winding number transition path. This variation depends on the path we choose, i.e., it increases or decreases depending upon the path. An analysis of the coefficient maps, energy spectrum, and spatial structure of the edge states of the final quench Hamiltonian provides an understanding of the path-dependent velocity variation phenomenon.

Compositional Verification in Rewriting Logic

AbstractIn previous work, summarized in this paper, we proposed an operation of parallel composition for rewriting-logic theories, allowing compositional specification of systems and reusability of components. The present paper focuses on compositional verification. We show how the assume/guarantee technique can be transposed to our setting, by giving appropriate definitions of satisfaction based on transition structures and path semantics. We also show that simulation and equational abstraction can be done componentwise. Appropriate concepts of fairness and deadlock for our composition operation are discussed, as they affect satisfaction of temporal formulas. We keep in parallel a distributed and a global view of composed systems. We show that these views are equivalent and interchangeable, which may help our intuition and also has practical uses as, for example, it allows global-style verification of a modularly specified system. Under consideration in Theory and Practice of Logic Programming (TPLP).

Spatiotemporal interaction characteristics and transition mechanism of tourism environmental efficiency in China

High-quality development is the theme of China’s economic and social development in the new era, and it is also an objective need for tourism development in the 14th Five-Year Plan period. This study presents an investigation of China’s patterns of tourism environmental efficiency from the perspective of spatiotemporal interactions. A nested analytical framework of quantile regression and spatiotemporal leaps was used to explore the driving mechanism patterns of tourism environmental efficiency under different leap types. Based on various spatial analysis methods, we posit that the patterns of tourism environmental efficiency differ through spatial associations, dynamic evolutions, and transition mechanisms. Our results indicate that there is a dynamic convergence trend of the overall differences in tourism environmental efficiency in China from 2000 to 2020 where a significant clustering phenomenon is observed in space and the level of spatial clustering gradually tends to be stable. In terms of local spatial structures and the dependence directions of tourism environmental efficiency, China’s northwest and northeast regions are more volatile, while eastern coastal regions are relatively stable. Spatiotemporal leaps of tourism environmental efficiency show certain transfer inertia with strong spatial dependence or path-locked characteristics, among which most central and western regions always maintain high carbon emission attributes. These regions are the most limited in the synergy of tourism environmental efficiency. The spatiotemporal network patterns of tourism environmental efficiency are mainly based on positive correlations and show strong spatial integration. However, a few neighboring provinces still have a certain degree of spatiotemporal competition. Driving patterns of the spatiotemporal leaps in tourism environmental efficiency among regions differ greatly. The eastern coastal provinces are driven by population-urbanization constraint patterns, and the northwest, southwest, and northeast regions are driven by technology regulation patterns. From the southeast to the northwest, the leap in the environmental efficiency of China's tourism gradually shows a stepwise pattern of "congruent constraint-reverse development-congruent development.” Therefore, the government should not only consider these various driving/constraining factors but also combine different environmentally-efficient tourism clustering types and transition paths to emphasize differentiated environmental tourism measures. This can help avoid the closure of inter-provincial tourism policies through inter-regional synergy.