Search Results (76)

Given the significant shifts in rural labor mobility patterns and their continuous influence on the transformation of the land factor market, it is crucial to understand the relationship between labor factor prices and land factor prices. This understanding is essential to keep land factor prices within a reasonable range. This study establishes a theoretical framework to investigate how migrant workers’ return shapes land price formation mechanisms. Using 2023 micro-level survey data from eight counties in Jiangsu Province, China, this study empirically examines how migrant workers’ return affects land transfer prices and its underlying mechanisms through OLS regression and instrumental variable approaches. The findings show that under the current pattern of labor mobility, the outflow factor alone is no longer sufficient to exert substantial downward pressure on land transfer prices. Instead, the localized return of labor has emerged as a key driver behind the rise in land transfer prices. This upward mechanism is primarily realized through the following pathways. First, factor substitution effect: this effect lowers labor prices and increases the relative marginal output value of land factors. Second, supply–demand effect: migrant workers’ return simultaneously increases land demand and reduces supply, intensifying market shortages and driving up transfer prices. Lastly, the results demonstrate that enhancing the stability of land tenure security or increasing local non-agricultural employment opportunities can mitigate the effect of rising land transfer prices caused by the migrant workers’ return. According to the study’s findings, stabilizing land factor prices depends on full non-agricultural employment for migrant workers. This underscores the significance of policies that encourage employment for returning rural labor. Full article

The agglomeration characteristics of innovation spaces reflect the intrinsic mechanisms of regional resource integration and collaborative innovation. Investigating the contributions of influencing factors to innovation space agglomeration and their spatial differentiation has significant implications for improving urban innovation quality. Taking the Nanjing central urban area as a case study, this research applied gradient boosting regression trees (GBRT) and multiscale geographically weighted regression (MGWR) models to explore the contributions of influencing factors to innovation space agglomeration and its spatial differentiation. Findings demonstrated that (1) Innovation platforms and patents emerged as the most significant driving factors, collectively accounting for 54.8% of the relative contributions; (2) The contributions of influencing factors to innovation space agglomeration exhibited marked nonlinear characteristics, specifically categorized into five distinct patterns: Sustained Growth Pattern, Growth-Stabilization Pattern, Growth-Decline Pattern, Global Stabilization Pattern, and Global Decline Pattern. The inflection thresholds of marginal effects across factors ranged from approximately 12% to 55% (e.g., 40% for metro stations, 13% for integrated commercial hubs); (3) Each influence factor’s contribution mechanism showed pronounced spatial heterogeneity across different regions. Based on these discoveries, governments should optimize innovation resource allocation according to regional characteristics and enhance spatial quality to promote efficient resource integration and transformation. This research provides a novel perspective for understanding innovation space agglomeration mechanisms and offers actionable references for urban policymakers to implement context-specific innovation economic development strategies. Full article

Background/Objectives: Digital prosthodontics increasingly utilize both additive (3D printing) and subtractive Computer-Aided Design/Computer-Aided Manufacturing (CAD/CAM), yet comprehensive comparisons remain limited. This scoping review evaluates their relative performance across prosthodontic applications. Methods: Systematic searches (PubMed, Scopus, Web of Science, Embase, 2015–2025) identified 28 studies (27 in vitro, 1 retrospective). Data were extracted on accuracy, efficiency, materials, and outcomes. Results: CAD/CAM milling demonstrated superior accuracy for fixed prostheses, with marginal gaps for milled zirconia (123.89 ± 56.89 µm), comparable to optimized 3D-printed interim crowns (123.87 ± 67.42 µm, p = 0.760). For removable prostheses, milled denture bases achieved a trueness of 65 ± 6 µm, while SLA-printed dentures post-processed at 40 °C for 30 min showed the lowest root mean square error (RMSE) (30 min/40 °C group). Three-dimensional printing excelled in material efficiency (<5% waste vs. milling > 30–40%) and complex geometries, such as hollow-pontic fixed dental prostheses (FDPs) (2.0 mm wall thickness reduced gaps by 33%). Build orientation (45° for crowns, 30–45° for veneers) and post-processing protocols significantly influenced accuracy. Milled resins exhibited superior color stability (ΔE00: 1.2 ± 0.3 vs. 3D-printed: 4.5 ± 1.1, p < 0.05), while 3D-printed Co-Cr frameworks (SLM) showed marginal fits of 8.4 ± 3.2 µm, surpassing milling (130.3 ± 13.8 µm). Digital workflows reduced chairside time by 29% (154.31 ± 13.19 min vs. 218.00 ± 20.75 min). All methods met clinical thresholds (<120 µm gaps). Conclusions: Milling remains preferred for high-precision fixed prostheses, while 3D printing offers advantages in material efficiency, complex designs, and removable applications. Critical gaps include long-term clinical data and standardized protocols. Future research should prioritize hybrid workflows, advanced materials, and AI-driven optimization to bridge technical and clinical gaps. Full article

Balance control in pirouettes has previously been characterized by constraint of the topple angle. However, there is a paucity of research using the margin of stability (MoS) as a dynamic measure of balance related to pirouettes. Therefore, this study aimed primarily to examine the MoS as a metric of balance during a single-turn en dehors pirouette in healthy female amateur ballet dancers. Four participants performed pirouettes until five successful pirouettes were achieved without hopping or loss of balance. Three-dimensional motion capture was used to record the motion trajectories of anatomical markers based on the Plug-in-Gait and Oxford Foot models. Motion synchronized with ground reaction forces was used to calculate the center of pressure (CoP), base of support (BoS), center of the pivot foot, center of mass (CoM), and extrapolated center of mass (XCoM) throughout the turn phase, using laboratory (LCS) and virtual left foot (LFT) coordinate systems. In the LCS and LFT coordinate system, the excursions and patterns of motion of both the CoM and XCoM relative to the CoP were similar, suggesting a neurological relationship. Two different measures of the margin of stability (MoS) in the LFT coordinate system were tabulated: the distance between the (1) XCoM and CoP and (2) XCoM and BoS center. The magnitude of both versions of the MoS was greatest at turn initiation and toe-touch, which was associated with two foot contacts. The MoS values were at a minimum approximately 50% of the stance during the turn phase: close to zero along the anteroposterior (A/P) axis and approximately 50 mm along the mediolateral (M/L) axis. On average, MoS magnitudes were reduced (mean across participants: approximately 20 mm) along the A/P axis, and larger MoS magnitudes (mean across participants: approximately 50 mm) along the M/L axis throughout the turn phase. Although all turns analyzed were completed successfully, the larger MoS values along the M/L axis suggest a fall potential. The variability between trials within a dancer and across participants and trials was documented and showed moderate inter-trial (16% to 51%) and across-participant CV% (range: 10% to 28%), with generally larger variations along the A/P axis. Although our results are preliminary, they suggest that the MoS may be useful for detecting faults in the control of dynamic balance in dehors pirouette performance, as a part of training and rehabilitation following injury. Full article

Load frequency control (LFC) remains a critical challenge in ensuring the stability of modern power grids. The integration of nonlinear dynamics into LFC design is paramount to achieving robust performance, which directly underpins grid reliability. This study introduces a novel hybrid control strategy—a fuzzy fractional-order proportional–integral–derivative (Fuzzy FOPID) controller augmented with a proportional–integral (PI) compensator—for LFC applications in two distinct dual-area interconnected power systems. To optimize the controller’s parameters, the recently developed Catch Fish Optimization Algorithm (CFOA) is employed, leveraging the Integral Time Absolute Error (ITAE) as the primary cost function for precision tuning. A comprehensive comparative analysis is conducted to benchmark the proposed controller against the existing methodologies documented in the literature. Nonlinear elements’ impact on the system stability is also investigated. The investigation evaluates the impact of critical nonlinearities, including governor dead band (GDB) and generation rate constraints (GRCs), on system performance. The simulation results demonstrate that the CFOA-tuned Fuzzy FOPID + PI controller exhibits superior robustness and dynamic response compared to conventional approaches, effectively mitigating frequency deviations and maintaining grid stability under nonlinear operating conditions. Furthermore, the CFOA demonstrates marginally superior convergence and tuning accuracy relative to the widely adopted Particle Swarm Optimization (PSO) algorithm. These findings underscore the proposed controller’s potential as a high-performance solution for real-world LFC systems, particularly in scenarios characterized by nonlinearities and interconnected grid complexities. This study advances the field by bridging the gap between fractional-order fuzzy control theory and practical power system applications, offering a validated strategy for enhancing grid resilience in dynamic environments. Full article

Inverse problems involving time-fractional differential equations have become increasingly important for modeling systems with memory-dependent dynamics, particularly in biotransport and viscoelastic materials. Despite their potential, these problems remain challenging due to issues of stability, non-uniqueness, and limited data availability. Recent advancements in Physics-Informed Neural Networks (PINNs) offer a data-efficient framework for solving such inverse problems, yet most implementations are restricted to integer-order derivatives. In this work, we develop a PINN-based framework tailored for inverse problems involving time-fractional derivatives. We consider two representative applications: anomalous diffusion and fractional viscoelasticity. Using both synthetic and experimental datasets, we infer key physical parameters including the generalized diffusion coefficient and the fractional derivative order in the diffusion model and the relaxation parameters in a fractional Maxwell model. Our approach incorporates a customized residual loss function scaled by the standard deviation of observed data to enhance robustness. Even under 25% Gaussian noise, our method recovers model parameters with relative errors below 10%. Additionally, the framework accurately predicts relaxation moduli in porcine tissue experiments, achieving similar error margins. These results demonstrate the framework’s effectiveness in learning fractional dynamics from noisy and sparse data, paving the way for broader applications in complex biological and mechanical systems. Full article

Since the beginning of the 21st century, the supercritical carbon dioxide (sCO₂) Brayton cycle has emerged as a hot topic of research in the energy field. Among its key components, the sCO₂ compressor has received significant attention. In particular, axial-flow sCO₂ compressors are increasingly being investigated as power systems advance toward high power scaling. This paper reviews global research progress in this field. As for performance characteristics, currently, sCO₂ axial-flow compressors are mostly designed with large mass flow rates (>100 kg/s), near-critical inlet conditions, multistage configurations with relatively low stage pressure ratios (1.1–1.2), and high isentropic efficiencies (87–93%). As for internal flow characteristics, although similarity laws remain applicable to sCO₂ turbomachinery, the flow dynamics are strongly influenced by abrupt variations in thermophysical properties (e.g., viscosities, sound speeds, and isentropic exponents). High Reynolds numbers reduce frictional losses and enhance flow stability against separation but increase sensitivity to wall roughness. The locally reduced sound speed may induce shock waves and choke, while drastic variation in the isentropic exponent makes the multistage matching difficult and disperses normalized performance curves. Additionally, the quantitative impact of a near-critical phase change remains insufficiently understood. As for the experimental investigation, so far, it has been publicly shown that only the University of Notre Dame has conducted an axial-flow compressor experimental test, for the first stage of a 10 MW sCO₂ multistage axial-flow compressor. Although the measured efficiency is higher than that of all known sCO₂ centrifugal compressors, the inlet conditions evidently deviate from the critical point, limiting the applicability of the results to sCO₂ power cycles. As for design and optimization, conventional design methodologies for axial-flow compressors require adaptations to incorporate real-gas property correction models, re-evaluations of maximum diffusion (e.g., the DF parameter) for sCO₂ applications, and the intensification of structural constraints due to the high pressure and density of sCO₂. In conclusion, further research should focus on two aspects. The first is to carry out more fundamental cascade experiments and numerical simulations to reveal the complex mechanisms for the near-critical, transonic, and two-phase flow within the sCO₂ axial-flow compressor. The second is to develop loss models and design a space suitable for sCO₂ multistage axial-flow compressors, thus improving the design tools for high-efficiency and wide-margin sCO₂ axial-flow compressors. Full article

Energy absorption capacity (EAC) is a parameter that expresses how much energy materials can store or dissipate under an external load or impact. EAC plays a critical role in understanding soil deformations and dynamic stability under impact loads (e.g., falling masses, projectile penetration, blast impacts, or vehicle collisions). Impact loads are sudden and high-accelerated forces that cause soils to deform rapidly and absorb energy differently. Understanding the EAC of soils under impact loads is critical for various geotechnical applications, particularly understanding soil behavior under blast loads, which is critical for military and civil structures, and the reinforcement of soils and design of protective structures that will be subjected to similar sudden impacts. This study aims to develop a novel experimental method and apparatus to evaluate the EAC of sandy soils under controlled laboratory conditions. A custom-designed test device was used to measure impact forces exerted by a metal sphere dropped from a fixed height onto soil samples with varying grain sizes (coarse, medium, and fine) and relative densities (40%, 70%, and 90%) under different moisture conditions (dry, optimum, and wet). The results showed that fine-grained sands exhibited the highest EAC, with absorbed energy values reaching 23.15 J, while coarse-grained sands under dense and saturated conditions exhibited the lowest capacity (22.05 J). An increase in moisture content from dry water content to optimum water content resulted in a moderate increase in energy absorption followed by a slight decrease under saturated conditions. Similarly, higher relative density marginally reduced energy absorption, reflecting reduced soil deformation at higher densities. The study introduces a potentially standardizable testing procedure for assessing soil impact response, providing valuable insights for geotechnical engineering applications, including soil stabilization, pavement design, and impact-resistant infrastructure. Full article

In this paper, a numerical study of two-phase flow instability in parallel rectangular channels is presented. Using the homogeneous flow model, marginal stability boundaries (MSBs) are derived in the parameter space defined by the phase change number (N_pch) and subcooling number (N_sub) under various operating conditions. Comparison with experimental data shows that the model predicts stability trends with a deviation of ±12.5%. The study reveals that, under constant mass flux conditions, stability decreases as the equivalent diameter (De) of the channels increases. Additionally, the exit area ratio of the two parallel tubes has minimal effect on the MSB, indicating that exit geometry does not significantly influence system stability. However, an increase in the inlet area ratio, from 0.1 to 1, reduces system stability, suggesting that larger inlet areas relative to tube cross-sectional areas may lead to greater flow disturbances, thereby decreasing stability. Moreover, increasing the length of the tubes enhances system stability, which may be attributed to the extended development length allowing for dissipation of flow disturbances. The study further demonstrates that higher flow rates, between 0.15 kg/s and 0.25 kg/s, enhance stability, while increasing the outlet flow resistance coefficient reduces stability. Conversely, increasing the inlet flow resistance coefficient improves stability. At system pressures of 3 MPa, 6 MPa, and 9 MPa, it is observed that higher pressures shift the boundary of complete vaporization (X_e = 1) to the left on the N_pch and N_sub graph, reducing the region susceptible to instability. The study also employs Fast Fourier Transform (FFT) analysis to identify peak frequencies across different parameter ranges. By examining the stability map and frequency spectra, the study provides deeper insights into two-phase flow instabilities in parallel channels. Full article

This study examines the coupling coordination between digital inclusive finance (DIF) and rural industrial integration development (RIID) in China from 2011 to 2021, using panel data from 282 prefecture-level cities. By employing the coupling coordination model and entropy method, the research analyzes the spatiotemporal evolution and regional disparities of DIF and RIID. Key findings include the following: (1) The coupling coordination degree between DIF and RIID shows a consistent upward trend, transitioning from mild imbalance to primary coordination, though RIID lags behind DIF. (2) Significant regional disparities exist, with an “N-shaped” spatial distribution pattern from south to north, where eastern and northeastern regions exhibit higher coordination levels compared to central and western regions. (3) Regional differences are narrowing, driven primarily by inter-regional disparities, with strong spatial spillover effects observed in “high–high” and “low–low” agglomerations. (4) The overall spatial network tightness and stability have improved, with eastern regions playing a central role in the network, while northeastern and western regions remain relatively marginal. Policy recommendations include expanding DIF applications in rural industries, reducing regional disparities through resource allocation, promoting rural industrial integration in underdeveloped areas, and strengthening regional coordination to facilitate resource flow. Full article

Aggressive behavior not only negatively affects an individual’s psycho-social adaptation but also undermines social harmony and stability. This study investigated the relationship between perceived crowdedness and aggression, examining the mediating role of relative deprivation and the moderating effects of upward social comparison and connectedness to nature based on the general strain theory and the I³ model. A cross-sectional design was employed, involving 848 participants (524 females, 61.8%) aged 20–75 (M = 33.15, SD = 6.83) in China. Structural equation modeling and bootstrapping procedures were used to test the hypothesized moderated mediation model. The results indicated that perceived crowdedness and upward social comparison positively predicted aggressive behavior, whereas connectedness to nature negatively predicted it. Relative deprivation mediated the relationship between perceived crowdedness and aggressive behavior. Only upward social comparison moderated the relationship between perceived crowdedness and relative deprivation, and connectedness to nature showed a marginally significant moderating effect on the relationship between perceived crowdedness and aggressive behavior. Unexpected trends are discussed, along with directions for future research. Full article

The Pamir is located on the northwestern margin of the Tibetan Plateau, which is an area of intense continental deformation and part of the famous India–Himalaya collision zone. The dominant structural deformation in the eastern Pamir is characterized by a 250 km long east–west extensional fault system, known as the Kongur Shan extensional system (KSES), which has developed a series of faults with different orientations and characteristics, resulting in highly complex structural deformation and lacking sufficient geodetic constraints. We collected Sentinel-1 SAR data from December 2016 to March 2023, obtained high-resolution ascending and descending LOS velocities and 3D deformation fields, and combined them with GPS data to constrain the current motion characteristics of the northeastern Pamirs for the first time. Based on the two-dimensional screw dislocation model and using the Bayesian Markov chain Monte Carlo (MCMC) inversion method, the kinematic parameters of the fault were calculated, revealing the fault kinematic characteristics in this region. Our results demonstrate that the present-day deformation of the KSES is dominated by nearly E–W extension, with maximum extensional motion concentrated in its central segment, reaching peak extension rates of ~7.59 mm/yr corresponding to the Kongur Shan. The right-lateral Muji fault at the northern end exhibits equivalent rates of extensional motion with a relatively shallow locking depth. The strike-slip rate along the Muji fault gradually increases from west to east, ranging approximately between 4 and 6 mm/yr, significantly influenced by the eastern normal fault. The Tahman fault (TKF) at the southernmost end of the KSES shows an extension rate of ~1.5 mm/yr accompanied by minor strike-slip motion. The Kashi anticline is approaching stability, while the Mushi anticline along the eastern Pamir frontal thrust (PFT) remains active with continuous uplift at ~2 mm/yr, indicating that deformation along the Tarim Basin–Tian Shan boundary has propagated southward from the South Tian Shan thrust (STST). Overall, this study demonstrates the effectiveness of integrated InSAR and GPS data in constraining contemporary deformation patterns along the northeastern Pamir margin, contributing to our understanding of the region’s tectonic characteristics. Full article

Background/Objectives: This study aims to broaden the knowledge on co-amorphous phospholipid systems (CAPSs) by exploring the formation of CAPSs with a broader range of poorly water-soluble drugs, celecoxib (CCX), furosemide (FUR), nilotinib (NIL), and ritonavir (RIT), combined with amphiphilic phospholipids (PLs), including soybean phosphatidylcholine (SPC), hydrogenated phosphatidylcholine (HPC), and mono-acyl phosphatidylcholine (MAPC). Methods: The CAPSs were initially prepared at equimolar drug-to-phospholipid (PL) ratios by mechano-chemical activation-based, melt-based, and solvent-based preparation methods, i.e., ball milling (BM), quench cooling (QC), and solvent evaporation (SE), respectively. The solid state of the product was characterized by X-ray powder diffraction (XRPD), polarized light microscopy (PLM), and differential scanning calorimetry (DSC). The long-term physical stability of the CAPSs was investigated at room temperature under dry conditions (0% RH) and at 75% RH. The dissolution behavior of the CCX CAPS and RIT CAPS was studied. Results: Our findings indicate that SE consistently prepared CAPSs for CCX-PLs, FUR-PLs, and RIT-PLs, whereas the QC method could only form CAPSs for RIT-PLs, CCX-SPC, and CCX-MAPC. In contrast, the BM method failed to produce CAPSs, but all drugs alone could be fully amorphized. While the stability of each drug varied depending on the PLs used, the SE CAPS consistently demonstrated the highest stability by a significant margin. Initially, a 1:1 molar ratio was used for screening all systems, though the optimal molar ratio for drug stability remained uncertain. To address this, various molar ratios were investigated to determine the ratio yielding the highest amorphous drug stability. Our results indicate that all systems remained physically stable at a 1.5:1 ratio and with excess of PL. Furthermore, the CAPS formed by the SE significantly improves the dissolution behavior of CCX and RIT, whereas the PLs provide a slight precipitation inhibition for supersaturated CCX and RIT. Conclusions: These findings support the use of a 1:1 molar ratio in screening processes and suggest that CAPSs can be effectively prepared with relatively high drug loads compared to traditional drug–polymer systems. Furthermore, the study highlights the critical role of drug selection, the preparation method, and the PL type in developing stable and effective CAPSs. Full article

With the load center’s continuous expansion and development of the AC power grid’s scale and construction, the recipient grid under the multi-feed DC environment is facing severe challenges of DC commutation failure and bipolar blocking due to the high strength of AC-DC coupling and the low level of system inertia, which brings many complexities and uncertainties to economic scheduling. In addition, the large-scale grid integration of wind power, photovoltaic, and other intermittent energy sources makes the ultra-high-voltage (UHV) DC channel operation state randomized. The deterministic scenario-based timing power simulation is no longer suitable for the current complex and changeable grid operation state. In this paper, we first start with the description and analysis of the uncertainty in renewable energy (RE) sources, such as wind and solar, and reconstruct the time-sequence power model by using the stochastic differential equation model. Then, a carbon emission trading cost (CET) model is constructed based on the CET mechanism, and the two-stage locating and capacity optimization model for the UHV DC receiving end is proposed under the constraint of dispatch safety and stability. Among them, the first stage starts with the objective of maximizing the carrying capacity of the UHV DC receiving end grid; the second stage checks its dynamic safety under the basic and fault modes according to the results of the first stage and corrects the drop point and capacity of the UHV DC line with the objective of achieving safe and stable UHV DC operation at the lowest economic investment. In addition, the two-stage model innovatively proposes UHV DC relative inertia constraints, peak adjustment margin constraints, transient voltage support constraints under commutation failure conditions, and frequency support constraints under a DC blocking state. In addition, to address the problem that the probabilistic constraints of the scheduling model are difficult to solve, the discrete step-size transformation and convolution sequence operation methods are proposed to transform the chance-constrained planning into mixed-integer linear planning for solving. Finally, the proposed model is validated with a UHV DC channel in 2023, and the results confirm the feasibility and effectiveness of the model. Full article

Green construction is considered to be a construction model that pursues high resource efficiency and the utilization of reduced environmental impacts through technological innovation and management optimization under the realization of the project’s iron triangle. The realization of its performance relies on the level of stakeholder capability configuration. To reveal the optimal capability configuration and interaction between regulators and executors, this study constructed a utility model based on a post-positivist methodology. By analyzing the optimal capability configuration and coordination levels of regulators and executors according to the practices and constraints of green construction, this study conducted a static analysis to compare the effects of marginal value on regulators’ capability input and coordination coefficients. Finally, a sensitivity analysis uncovers the changes in capability configuration interaction and coordination coefficients at different stages of green construction. The results indicate that high levels of coordination in green construction cannot be maintained in the long term; continuous capability input from regulators is required for sustained support. Only by eliminating external uncertainties, reducing the variable costs for executors in advancing green construction, and controlling their risk aversion can executors be truly motivated to promote green construction. The capability configuration of both regulators and executors adjusts with corresponding marginal values. The capability configuration of executors shows a trend of initially increasing and then decreasing as the progressive coefficient rises. The model proposed in this study ensures that the final coordination level stabilizes at a relatively high level, which is between 0.6 and 0.7. In summary, the breakthrough findings provide critical insights into green construction management, contributing to the achievement of the anticipated green construction objectives. Full article