Search Results (37,916)

The growth of rural residents’ disposable income is essential for narrowing the income gap between urban and rural areas and promoting integrated development. This study explores how China’s National Main Functional Zoning Plan influences rural household income through its regulatory impact on construction land expansion. Using data from county−level administrative units across China, the research identified the construction land regulation index as a key mediating variable linking zoning policy to changes in household income. By shifting the analytical perspective from a traditional urban–rural classification to a framework aligned with the National Main Functional Zoning Plan, the study reveals how spatial planning tools, particularly differentiated land quota allocations, influence household income. The empirical results confirm a structured causal chain in which zoning policy affects land development intensity, which in turn drives rural income growth. This relationship varies across different functional zones. In key development zones, strict land control limits income potential by constraining land supply. In main agricultural production zones, moderate regulatory control enhances land use efficiency and contributes to higher income levels. In key ecological function zones, ecological constraints require diverse approaches to value realization. The investigation contributes both theoretical and practical insights by elucidating the microeconomic effects of national spatial planning policies and offering actionable guidance for optimizing land use regulation to support income growth tailored to regional functions. Full article

This paper presents field investigations of a corrugated steel soil–steel arch structure with a span of 25.7 m and a rise of 9.0 m—currently the largest single-span structure of its kind in Europe. The structure, serving as a wildlife crossing along the DK16 expressway in northeastern Poland, was constructed using deep corrugated steel plates (500 mm× 237 mm) made from S315MC steel, without additional reinforcements such as stiffening ribs or geosynthetics. The study focused on monitoring the structural behavior during the critical backfilling phase. Displacements and strains were recorded using 34 electro-resistant strain gauges and a geodetic laser system at successive backfill levels, with particular attention to the loading stage at the crown. The measured results were compared with predictions based on the Swedish Design Method (SDM). The SDM equations did not accurately predict internal forces during backfilling. At the crown level, bending moments and axial forces were overestimated by approximately 69% and 152%, respectively. At the final backfill level, the SDM underestimated bending moments by 55% and overestimated axial forces by 90%. These findings highlight limitations of current design standards and emphasize the need for revised analytical models and long-term monitoring of large-span soil–steel structures. Full article

A wide range of strategies have been developed to modulate dysfunctional brain activities. This narrative review provides a comparative analysis of biophysical, genetic, and biological neuromodulation approaches with an emphasis on their known or unknown molecular targets and translational potential. The review incorporates data from both preclinical and clinical studies covering deep brain stimulation, transcranial electrical and magnetic stimulation, focused ultrasound, chemogenetics, optogenetics, magnetogenetics, and toxin-based neuromodulation. Each method was assessed based on specificity, safety, reversibility, and mechanistic clarity. Biophysical methods are widely used in clinical practice but often rely on empirical outcomes due to undefined molecular targets. Genetic tools offer cell-type precision in experimental systems but face translational barriers related to delivery and safety. Biological agents, such as botulinum neurotoxins, provide long-lasting yet reversible inhibition via well-characterized molecular pathways. However, they require stereotaxic injections and remain invasive. To overcome individual limitations and improve targeting, delivery, and efficacy, there is a growing interest in the synthesis of multiple approaches. This review highlights a critical gap in the mechanistic understanding of commonly used methods. Addressing this gap by identifying molecular targets may help to improve therapeutic precision. This concise review could be valuable for researchers looking to enter the evolving field of the neuromodulation of brain function. Full article

The spatial variability in rock mass mechanical parameters critically affects slope stability assessments. This study investigated the southern slope of the Bayan Obo open-pit mine. A representative elementary volume (REV) with a side length of 14 m was determined through discrete fracture network (DFN) simulations. Based on the rock quality designation (RQD) data from 40 boreholes, a three-dimensional spatial distribution model of the RQD was constructed using Ordinary Kriging interpolation. The RQD values were converted into geological strength index (GSI) values through an empirical correlation, and the generalized Hoek–Brown criterion was applied to develop a spatially heterogeneous equivalent mechanical parameter field. Numerical simulations were performed using FLAC3D, with the slope stability evaluated using the point safety factor (PSF) method. For comparison, three homogeneous benchmark models based on the 5th, 25th, and 50th percentiles produced profile-scale safety factors of 0.96–1.92 and failed to replicate the observed failure geometry. By contrast, the heterogeneous model yielded safety factors of approximately 1.03–1.08 and accurately reproduced the mapped sliding surface. These findings demonstrate that incorporating spatial heterogeneity significantly improves the accuracy of slope stability assessments, providing a robust theoretical basis for targeted monitoring and reinforcement design. Full article

This study aims to clarify the nonlinear pressure loss patterns of the pneumatic system in a pneumatic seeder under varying pipeline structures and airflow parameters, and to develop a rapid prediction equation for the main pipe’s pressure loss. The studied multi-branch pipeline system consists of a main pipe, a header, and ten branch pipes. The main pipe is vertically installed at the center of the header in a straight-line configuration. The ten branch pipes are symmetrically and evenly spaced along the axial direction of the header, distributed on both sides of the main pipe. The outlet directions of the branch pipes are arranged in a 180° orientation opposite to the inlet direction of the main pipe, forming a symmetric multi-branch configuration. Firstly, this study investigated the flow characteristics within the multi-branch pipeline of the pneumatic system and elaborated on the mechanism of flow division in the pipeline. The key geometric factors affecting airflow were identified. Secondly, from a microscopic perspective, CFD simulations were employed to analyze the fundamental causes of pressure loss in the multi-branch pipeline system. Finally, from a macroscopic perspective, a dimensional analysis method was used to establish an empirical equation describing the relationship between the pressure loss (P) and several influencing factors, including the air density (ρ), air’s dynamic viscosity (μ), closed-end length of the header (Δl), branch pipe 1’s flow rate (Q), main pipe’s inner diameter (D), header’s inner diameter (γ), branch pipe’s inner diameter (d), and the spacing of the branch pipe (δ). The results of the bench tests indicate that when 0.0018 m³·s⁻¹ ≤ Q ≤ 0.0045 m³·s⁻¹, 0.0272 m < d ≤ 0.036 m, 0.225 m < δ ≤ 0.26 m, 0.057 m ≤ γ ≤ 0.0814 m, and 0.0426 m ≤ D ≤ 0.0536 m, the prediction accuracy of the empirical equation can be controlled within 10%. Therefore, the equation provides a reference for the structural design and optimization of pneumatic seeders’ multi-branch pipelines. Full article

A multilayer linear response model (MLRM) is proposed to generate time-series data based on linear response theory. The proposed MLRM is designed to generate data for anomalous dynamics by extending the conventional single-layer linear response model (SLRM) into multiple layers. While the SLRM is a linear equation with respect to external forces, the MLRM introduces nonlinear interactions, enabling the generation of a wider range of dynamics. The MLRM is applicable to various fields, such as finance, as it does not rely on machine learning techniques and maintains interpretability. We investigated whether the MLRM could generate anomalous dynamics, such as those observed during the coronavirus disease 2019 (COVID-19) pandemic, using pre-pandemic data. Furthermore, an analysis of the log returns and realized volatility derived from the MLRM-generated data demonstrated that both exhibited heavy-tailed characteristics, consistent with empirical observations. These results indicate that the MLRM can effectively reproduce the extreme fluctuations and tail behavior seen during high-volatility periods. Full article

This study employs k-means clustering to group 30 Chinese provinces into four CO${}_2$ emission patterns, characterized by increasing emission levels and distinct energy consumption structures, and captures their dynamic evolution from 2000 to 2021 using a discrete endogenous Markov chain approach. While Shanghai, Jiangxi, and Hebei retained their original classifications, provinces such as Beijing, Fujian, Tianjin, and Anhui transitioned from higher to lower emission patterns, indicating notable reversals in emission trajectories. To identify the determinants of these transitions, GDP growth rate, population growth rate, and energy investment are incorporated as time varying covariates. The empirical findings demonstrate that GDP growth substantially increases interpattern mobility, thereby weakening state persistence, whereas population growth and energy investment tend to reinforce emission pattern stability. These results imply that policy responses must be tailored to regional dynamics. In rapidly growing regions, fiscal incentives and technological upgrading may facilitate downward transitions in emission states, whereas in provinces where emissions remain persistent due to demographic or investment related rigidity, structural adjustments and long term mitigation frameworks are essential. The study underscores the importance of integrating economic, demographic, and investment characteristics into carbon reduction strategies through a region specific and data informed approach. Full article

This study uses financial data from 872 Chinese listed companies (2018–2022). It tests the triple dividend effect and threshold effect of China’s environmental protection tax (EPT) using high-dimensional fixed effects models and panel threshold models. We document that (1) EPT creates an environmental dividend for Chinese listed companies. It significantly reduces pollution emissions. A 1-unit tax increase reduces LnTPPE by 2.5%. (2) EPT creates a significant innovation dividend. It forces enterprises to improve the quality of authorized patents. A 1-unit tax increase raises patent technological complexity by 0.79%. (3) EPT creates an economic dividend. It significantly improves firm performance. A 1-unit tax increase raises relative corporate revenue by 38.1%. (4) EPT exerts significant threshold effects on micro-level triple dividend outcomes among Chinese listed companies. A heterogeneity analysis shows significant differences in threshold effects between non-heavily polluting and heavily polluting industries. This study confirms that China’s EPT generates a micro-level triple dividend effect alongside coexisting threshold effects for listed companies. This provides literature references for China to design and implement differentiated policies and offers a quantitative empirical case for implementing globally sustainable EPT strategies. Full article

Accurate above-ground biomass (AGB) quantification is confounded by signal saturation and data fusion challenges, particularly in structurally complex ecosystems like bamboo forests. To address these gaps, this study developed a two-stage framework to map the AGB of Dendrocalamus giganteus in a subtropical mountain environment. This study first employed Empirical Bayesian Kriging Regression Prediction (EBKRP) to spatialize sparse GEDI and ICESat-2 LiDAR metrics using Sentinel-2 and topographic covariates. Subsequently, a stacked ensemble model, integrating four machine learning algorithms, predicted AGB from the full suite of continuous variables. The stacking model achieved high predictive accuracy (R² = 0.84, RMSE = 11.07 Mg ha⁻¹) and substantially mitigated the common bias of underestimating high AGB, improving the predicted observed regression slope from a base model average of 0.63 to 0.81. Furthermore, SHAP analysis provided mechanistic insights, identifying the canopy photon rate as the dominant predictor and quantifying the ecological thresholds governing AGB distribution. The mean AGB density was 71.8 ± 21.9 Mg ha⁻¹, with its spatial pattern influenced by elevation and human settlements. This research provides a robust framework for synergizing multi-source remote sensing data to improve AGB estimation, offering a refined methodological pathway for large-scale carbon stock assessments. Full article

This study examines how the newly established United States pursued economic development through diplomatic and commercial initiatives with the Ottoman Empire, navigating regional powers and the era’s political-economic conditions. It analyzes using American archival sources how America endeavored to establish commercial and diplomatic relations with the Ottoman Empire in the Mediterranean and Black Sea regions, which it viewed as critical markets in the late 18th and early 19th centuries, before signing any formal agreement. The research tracks how these early efforts laid foundations for what would become one of the world’s largest economies. The study analyzes America’s diplomatic efforts to secure an agreement with the Ottoman Empire prior to the 7 May 1830 trade agreement—which laid the foundation for bilateral relations—alongside the reactions of regional powers, the prevailing conditions of the period, and the Ottoman administration’s reluctance due to various factors, based on U.S. archival sources that, to the best of our knowledge, have not previously been utilized in existing studies. Full article

This paper develops empirical relationships to estimate FAA/EASA and MIL-3013B rules-compliant take-off field performance for single and multi-engine aircraft. Recent experience with modern aircraft flight manuals revealed that popular empirical legacy methods are no longer accurate; improvements in tires and brakes lead to significantly shorter certified distances. This work relies upon a survey of current operational aircraft and extensive numerical simulations of generic configurations to support the development of a collection of new equations to estimate take-off performance for single and multi-engine aircraft under dry and wet conditions. These relationships are individually tailored for civilian and U.S. Military rules; they account for the superior capability of modern braking systems and the implications of minimum-control speed on the certified distance. Full article

Background/Objectives: Collaboration in mental health care is essential for implementing a model oriented towards the psychosocial rehabilitation of people based on multifaceted interventions involving different actors and sectors of society to respond to demands. Despite the benefits presented by the scientific evidence, there are still many barriers to collaborative care, and professionals continue to struggle in reorienting their conduct. The current situation demands organization and the framing of well-founded action plans to overcome challenges, which in turn requires a detailed understanding of collaborative practices in mental health care and their conceptual boundaries. A concept analysis was undertaken to propose a working definition of collaborative practices in mental health care (CPMHC). Methods: This paper used the Walker and Avant concept analysis method. This includes identifying the defining concept attributes, antecedents, consequences, and empirical referents. A literature search was carried out from November 2024 to February 2025 in three databases (Medline, CINAHL, and LILACS), considering studies published between 2010 and 2024. Results: The final sample of literature investigated consisted of 30 studies. The key attributes were effective communication, building bonds, co-responsibility for care, hierarchical flexibility, articulation between services, providers and community, monitoring and evaluating of care processes, and attention to the plurality of sociocultural contexts. Conclusions: This comprehensive analysis contributes to guiding future research and policy development of collaborative practices in mental health, considering the individual, relational, institutional, and social levels. Further research is possible to deepen the understanding of the production of collaborative practices in mental health in the face of the complexity of social relations and structural inequities. Full article

Background/Objectives: Evidence-based nursing practice (EBNP) is essential in high-acuity settings such as intensive care units (ICUs) and emergency departments (EDs), where nurses are frequently required to make time-critical, high-stakes clinical decisions that directly influence patient safety and outcomes. Despite its recognized importance, the implementation of EBNP remains inconsistent, with frontline nurses often facing barriers to accessing and applying current evidence. Methods: This descriptive, cross-sectional study systematically mapped and prioritized clinical questions generated by ICU and ED nurses at a tertiary hospital in South Korea. Using open-ended questionnaires, 204 clinical questions were collected from 112 nurses. Each question was coded and classified according to the Nursing Interventions Classification (NIC) taxonomy (8th edition) through a structured cross-mapping methodology. Inter-rater reliability was assessed using Cohen’s kappa coefficient. Results: The majority of clinical questions (56.9%) were mapped to the Physiological: Complex domain, with infection control, ventilator management, and tissue perfusion management identified as the most frequent areas of inquiry. Patient safety was the second most common domain (21.6%). Notably, no clinical questions were mapped to the Family or Community domains, highlighting a gap in holistic and transitional care considerations. The mapping process demonstrated high inter-rater reliability (κ = 0.85, 95% CI: 0.80–0.89). Conclusions: Frontline nurses in high-acuity environments predominantly seek evidence related to complex physiological interventions and patient safety, while holistic and community-oriented care remain underrepresented in clinical inquiry. Utilizing the NIC taxonomy for systematic mapping establishes a reliable framework to identify evidence gaps and support targeted interventions in nursing practice. Regular protocol evaluation, alignment of continuing education with empirically identified priorities, and the integration of concise evidence summaries into clinical workflows are recommended to enhance EBNP implementation. Future research should expand to multicenter and interdisciplinary settings, incorporate advanced technologies such as artificial intelligence for automated mapping, and assess the long-term impact of evidence-based interventions on patient outcomes. Full article

The construction industry has been troubled by a shortage of skilled labor and safety accidents in recent years. Therefore, more and more robots are introduced to undertake dangerous and repetitive jobs, so that human workers can concentrate on higher-value and creative problem-solving tasks. Nevertheless, although human–robot collaboration (HRC) shows great potential, most existing evaluation methods still focus on the single performance of either the human or robot, and systematic indicators for a whole HRC team remain insufficient. To fill this research gap, the present study constructs a comprehensive evaluation framework for HRC team performance in construction projects. Firstly, a detailed literature review is carried out, and three theories are integrated to build 33 indicators preliminarily. Afterwards, an expert questionnaire survey (N = 15) is adopted to revise and verify the model empirically. The survey yielded a Cronbach’s alpha of 0.916, indicating excellent internal consistency. The indicators rated highest in importance were task completion time (µ = 4.53) and dynamic separation distance (µ = 4.47) on a 5-point scale. Eight indicators were excluded due to mean importance ratings falling below the 3.0 threshold. The framework is formed with five main dimensions and 25 concrete indicators. Finally, an AHP-TOPSIS method is used to evaluate the HRC team performance. The AHP analysis reveals that Safety (weight = 0.2708) is prioritized over Productivity (weight = 0.2327) by experts, establishing a safety-first principle for successful HRC deployment. The framework is demonstrated through a case study of a human–robot plastering team, whose team performance scored as fair. This shows that the framework can help practitioners find out the advantages and disadvantages of HRC team performance and provide targeted improvement strategies. Furthermore, the framework offers construction managers a scientific basis for deciding robot deployment and team assignment, thus promoting safer, more efficient, and more creative HRC in construction projects. Full article

Parametric changes in the first coordination shell (FCS) of a vitreous metallic Pd_42.5Cu₃₀Ni_7.5P₂₀ alloy are analysed, aiming to confirm the identification of the glass transition temperature (T_g) via processing of XRD patterns utilising radial and pair distribution functions (RDFs and PDFs) and their evolution with temperature. The Wendt–Abraham empirical criterion of glass transition and its modifications are confirmed in line with previous works, which utilised the kink of the temperature dependences of the minima and maxima of both the PDF and the maxima of the structure factor S(q). Massive fluctuations are, however, identified near the T_g of the derivatives of the minima and maxima of the PDF and maxima of S(q), which adds value to understanding the glass transition in the system as a true second-order-like phase transformation in the non-equilibrium system of atoms. Full article