Besides improving environmental conditions, large scale ecological restoration initiatives carry implications for households' livelihoods. Therefore, evaluating whether restoration policies can align ecological objectives with income growth is important for promoting environmentally sustainable development. We study whether China's Integrated Protection and Restoration Project of Mountains, Rivers, Forests, Farmlands, Lakes, Grasslands, and Deserts, commonly known as the Shan-Shui Initiative, has helped promote rural income growth as well as the channels through which income effects operate. Using a panel of 1700 counties from 21 provinces, we estimate policy effects for the period 2016–2022 with a synthetic control approach that uses machine learning to construct counterfactual income paths for treated counties. Our results show that the initiative has increased rural incomes with gains growing over time. Estimated effects differ by pilot batch, with incomes rising by about 5% and 1.9% for the first two project cohorts implemented in 2016 and 2017, respectively, but decreasing by 0.9% for the final batch in 2018. After adjusting for potential anticipation effects, the estimated effect for the 2017 cohort increases to 3.7%. We demonstrate that ecological restoration promotes rural incomes via improvements in ecosystem services, infrastructure, and tourism development. Income effects are generally larger in more economically developed and less ecologically fragile areas, while differences across dominant project types are comparatively modest. The results provide insights into potential policies for aligning environmental protection objectives with rural development.
In this work, we investigate an approach that enriches the information encoded within the ACO pheromone structure in order to enhance the performance of swarm optimization. While this concept has been extensively studied in the context of single-objective optimization, this paper provides a comprehensive evaluation of its extension to multi-objective optimization problems. The results demonstrate that this enhanced pheromone representation remains effective in multi-objective settings.
Ammonia-based selective catalytic reduction (NH3-SCR) stands as the preeminent strategy for NOx mitigation in industrial flue gases. Nonetheless, incumbent V2O5–WO3/TiO2 catalysts are beset by constrained temperature operability, toxicity concerns, inadequate hydrothermal endurance, and susceptibility to SO2/H2O deactivation. Contemporary investigations have converged on advanced structural modulation—encompassing dimensionality, morphology, and pore hierarchy—to augment active-site utilization, acid-base equilibrium, and mass/electron conveyance. Diverging from recent reviews that predominantly address material-centric themes (e.g., Cu-based zeolites or core–shell motifs) or isolated attributes, this contribution furnishes a holistic, multiscale amalgamation of advancements in dimensional modulation (1D nanowires, 2D nanosheets, 3D scaffolds), morphological constructs (rod-like, laminar, core–shell, yolk-shell, hollow configurations), and hierarchical porosity (micro-meso-macro integration). We delineate core mechanisms, including pore-caliber-mediated molecular sieving, steric impediments, diffusion orchestration, and confinement-driven phenomena such as reactant sequestration, oriented translocation, and amplified adsorption-redox sequences. Merging these elements with state-of-the-art in situ/operando spectroscopic elucidations, we extrapolate pragmatic design tenets for low- to medium-temperature NOx abatement catalysts that harmonize exceptional efficacy, longevity, and antitoxin fortitude. This synoptic vista not only expedites the conception of resilient industrial NOx abatement architectures but also proffers an adaptable schema for structure–property refinement in heterogeneous catalysis writ large.
Research on mega sport events and tourism demand has largely overlooked domestic tourism and relied on aggregated data that mask individual behavioural adjustments. Using Paris 2024 as a case study, we propose a methodology to estimate the direct impact of mega sport events on domestic tourism at the individual level. A retrospective paired-sample survey is used to construct a two-period panel dataset (2023–2024). Individuals are classified as positively affected, negatively affected, or unaffected using self-reported motivations validated by counterfactual behaviour absent the event to mitigate ex-post rationalisation bias. Tourism demand remains unchanged based on the full sample due to offsetting behavioural responses: travel versus stay-at-home attraction among positively affected, and substitution versus crowding-out among negatively affected. However, focusing on actual travellers, affected individuals exhibit a larger increase in overnight stays than unaffected residents, without increasing visit frequency. Micro-level approaches are critical to capture how mega events reshape tourism demand.
The aim of this article is to study the dynamics of random products of weighted shifts on a separable Fréchet sequence space. That is, given a measure-preserving dynamical system (Ω,F,μ,τ), a Fréchet sequence space X with a basis (en)n≥0, and a strongly measurable map T:Ω→B(X) taking values in a finite set of weighted shifts on X, we study the dynamics of the sequence (T(τn−1ω)⋯T(τω)T(ω))n≥1 for almost every ω∈Ω. After proving criteria to determine whether this sequence is universal, weakly mixing or mixing for almost every ω∈Ω, we study some examples on the spaces X=ℓp, X=c0 and X=H(C) involving two shifts, first in the commuting case and then in the non-commuting one.
