Why Some Strikes Last Longer: The Resilience Paradox of Partially Functional Institutions
研究通过建立动态模型探讨部分正常运作的机构如何影响劳工冲突持续时间,揭示了剩余活动可能增加而非减少罢工参与度的反直观现象。
研究通过建立动态模型探讨部分正常运作的机构如何影响劳工冲突持续时间,揭示了剩余活动可能增加而非减少罢工参与度的反直观现象。
针对口腔扫描图像分割中空间连续性和频率分布问题,FU-Mamba框架通过动态扫描和频域增强方法提高了分割精度。
This study addresses the lack of quantitative analysis regarding how specific refactoring types affect code merge costs. Analyzing 64 Java projects through refactoring detection and association rule mining, this work provides the first fine-grained quantification of the independent and synergistic impacts of individual refactorings and their combinations on merge effort. Results indicate that refactorings such as attribute renaming significantly increase merge costs, while the volume, diversity, and cross-branch co-occurrence of refactorings independently elevate merge effort. By elucidating the intrinsic mechanisms through which refactorings induce merge conflicts, this research offers empirical evidence to inform and optimize code merging strategies.
In highly polarized societies, traditional electoral models struggle to account for the coexistence of voter stability and localized mobility. This study proposes a parsimonious dynamical model that partitions the electorate into two stable partisan blocs and a mobile group, employing a Fermi-like probabilistic rule from statistical physics to govern the dynamic allocation of mobile voters. Central to this framework is a moving electoral interface, which serves as the core of a new paradigm for understanding polarization dynamics. Theoretical analysis reveals that macroscopic electoral responses are primarily driven by fluctuations of this interface rather than large-scale ideological shifts. Moreover, the system’s sensitivity to external perturbations scales linearly with the steady-state size of the mobile interface, uncovering a continuous mechanism that bridges frozen polarization and highly responsive electoral states.
This study explains how systemic political corruption can persist over extended periods without centralized coordination. By constructing a parsimonious compartmental dynamical model and integrating mean-field approximation, phase transition analysis, and stability theory, the work conceptualizes corruption as a macro-level emergent phenomenon arising from the co-evolution of political power concentration and supportive relational structures. The model demonstrates that corruption stabilizes through self-reinforcing mechanisms into a collective state and identifies a critical threshold of interaction strength: beyond this point, the system enters a “corruption-captured” regime capable of autonomously recovering from perturbations, thereby sustaining corruption across electoral cycles. This framework transcends conventional explanatory paradigms centered on individual misconduct or institutional failure, offering a novel perspective on the systemic nature and resilience of corruption.
研究通过建立动态模型探讨部分正常运作的机构如何影响劳工冲突持续时间,揭示了剩余活动可能增加而非减少罢工参与度的反直观现象。
针对口腔扫描图像分割中空间连续性和频率分布问题,FU-Mamba框架通过动态扫描和频域增强方法提高了分割精度。
This study addresses the lack of quantitative analysis regarding how specific refactoring types affect code merge costs. Analyzing 64 Java projects through refactoring detection and association rule mining, this work provides the first fine-grained quantification of the independent and synergistic impacts of individual refactorings and their combinations on merge effort. Results indicate that refactorings such as attribute renaming significantly increase merge costs, while the volume, diversity, and cross-branch co-occurrence of refactorings independently elevate merge effort. By elucidating the intrinsic mechanisms through which refactorings induce merge conflicts, this research offers empirical evidence to inform and optimize code merging strategies.
In highly polarized societies, traditional electoral models struggle to account for the coexistence of voter stability and localized mobility. This study proposes a parsimonious dynamical model that partitions the electorate into two stable partisan blocs and a mobile group, employing a Fermi-like probabilistic rule from statistical physics to govern the dynamic allocation of mobile voters. Central to this framework is a moving electoral interface, which serves as the core of a new paradigm for understanding polarization dynamics. Theoretical analysis reveals that macroscopic electoral responses are primarily driven by fluctuations of this interface rather than large-scale ideological shifts. Moreover, the system’s sensitivity to external perturbations scales linearly with the steady-state size of the mobile interface, uncovering a continuous mechanism that bridges frozen polarization and highly responsive electoral states.
This study explains how systemic political corruption can persist over extended periods without centralized coordination. By constructing a parsimonious compartmental dynamical model and integrating mean-field approximation, phase transition analysis, and stability theory, the work conceptualizes corruption as a macro-level emergent phenomenon arising from the co-evolution of political power concentration and supportive relational structures. The model demonstrates that corruption stabilizes through self-reinforcing mechanisms into a collective state and identifies a critical threshold of interaction strength: beyond this point, the system enters a “corruption-captured” regime capable of autonomously recovering from perturbations, thereby sustaining corruption across electoral cycles. This framework transcends conventional explanatory paradigms centered on individual misconduct or institutional failure, offering a novel perspective on the systemic nature and resilience of corruption.