Search Results (5,196)

Conventional project scheduling techniques often rely on manual trial-and-error methods, which can lead to inaccurate evaluations. This study presents a dynamic scheduling framework to dynamically adjust scheduling decisions based on real-time productivity and budget constraints, resulting in improvement in scheduling accuracy in project management. By integrating advanced computational tools, the proposed approach addresses complex scheduling challenges. The model integrates Building Information Modeling (BIM)-based 3D data, productivity and process simulation, and optimization techniques to provide a unified scheduling tool that supports informed decision-making while considering real-time constraints, including productivity performance and budget limitations. The results demonstrated notable improvements over conventional methods, including a 13% increase in scheduling accuracy relative to the actual total project cost and a 34.4% improvement in scheduling accuracy based on the actual project duration, compared to the contractor’s baseline. The framework dynamically adjusts schedules and budgets according to current project conditions. These findings demonstrate its reliability as a decision-making tool for construction project management. The study introduces an integrative scheduling framework that adapts to real-time project conditions and is validated against actual project data. The integration of BIM, system dynamics, process simulation, and ACOR optimization provides a novel approach to construction scheduling. This methodology improves project management efficiency by automating scheduling adjustments based on ongoing progress. Full article

We employed a global high-resolution inverse model to estimate sectoral methane emissions, integrating observations from the GOSAT-2 satellite for the first time, along with observations from the surface observation network. A similar set of inversions using GOSAT observations was carried out to evaluate the consistency between emissions estimates derived from these two satellites and to ensure that GOSAT-2 data could seamlessly integrate with the existing data series without disrupting the continuity of flux estimates. This analysis, covering the period from 2019 to 2022, utilized prior anthropogenic emissions data mainly from EDGAR v6 and incorporated additional natural sources and sinks as outlined by global methane budget, 2020. Our analysis reveals a general agreement between total methane emissions estimates from GOSAT and GOSAT-2. However, on a sectoral basis, we found notable regional differences in the flux estimates. While GOSAT inversion estimates ~8 Tg a⁻¹ more anthropogenic emissions for China and around 4 Tg a⁻¹ more wetland emissions for Brazil and Indonesia, the posterior error distribution suggests that GOSAT-2 inversion is closer to surface observations over Asia. These discrepancies are found in regions with significant differences in XCH₄ data from the two satellites, such as East Asia and North America, tropical South America, and tropical Africa. These regional biases persist due to limited representative surface reference sites for Level 2 bias correction. The relatively lower data volume from GOSAT also introduces seasonal biases in the flux estimates when the quality filtering of Level 2 data persistently reduces usable observations during certain seasons, resulting in inadequate representation of the seasonal cycle in regions such as East Asia. Similarly, in tropical South America, where the model is relatively under-constrained by the limited surface observations, the lower data volume of GOSAT-2 suffers. While the two inversions exhibit consistent overall performance across North America and Europe, the GOSAT-2-based inversion demonstrates a better performance over East Asia. Therefore, while the two satellite datasets are broadly consistent, considering the fact that the biases in the XCH₄ data overlap with regions under-constrained by surface observations, establishing additional surface reference measurement sites is desirable to ensure consistent inversion results. Full article

Background/Objectives: Idiopathic pulmonary fibrosis (IPF) is a chronic and progressive fibrosing interstitial disease that incurs significant healthcare costs due to diagnostic and treatment needs. This study aimed to estimate healthcare expenses related to IPF diagnosis, treatment, and follow-up, including factors affecting overall expenditure. Methods: This retrospective cohort study included 276 IPF patients from a tertiary hospital (2013–2022). Diagnostic and treatment costs were analyzed, including antifibrotic medications (pirfenidone and nintedanib), diagnostic tests (pulmonary function tests and performance evaluation tests), and interventions (fiberoptic bronchoscopy, imaging modalities). Costs in Turkish Lira were converted to United States dollars. Statistical analysis was performed using non-parametric tests to evaluate expenditure correlations with demographic, clinical, and treatment parameters, which included the Mann–Whitney and Spearman Rank Correlation tests when appropriate. Results: The median healthcare expenditure was USD 429.1 (9.13–21,024.57). Inpatient costs (USD 582.67; USD 250.22 to USD 1751, 25th and 75th percentile, respectively) were higher than outpatient costs (USD 192.36; USD 85.75 to USD 407.47, 25th and 75th percentile, respectively). Antifibrotic regimens did not differ significantly in cost or duration (Z = 0.657; p = 0.511) (mean pirfenidone duration: 1.1 ± 1.0 years; mean nintedanib duration: 0.6 ± 0.9 years). Diagnostic tests, particularly pulmonary function tests (PFT) (p: 0.001, Rho: 0.337), diffusing capacity of the lungs for carbon monoxide (DLCO) (p: 0.001, Rho: 0.516), and high-resolution computed tomography (HRCT) (p: 0.001, Rho: 0.327), were the primary drivers of costs. Longer treatment duration was positively correlated with expenditure (Rho: 0.264, p: 0.001 and Rho: 0.247, p: 0.006 for pirfenidone and nintedanib, respectively) while age showed a weak negative correlation (Rho = −0.184, p = 0.002). Gender and type of antifibrotic regimen did not show any significant effect on costs. Discussion: Diagnostic and follow-up testing were the main contributors to costs, driven by reimbursement requirements and the progressive nature of IPF. Antifibrotic medications, although expensive, provided clinical stability, potentially reducing hospitalization needs but increasing long-term care expenses. Variations in healthcare systems affect expenditures, with Turkey’s universal coverage lowering costs compared to Western countries. The study’s main limitations include being a single-center, retrospective study and its inability to include comorbidities and disease severity in the statistical analysis. Conclusions: IPF management is resource-intensive, with diagnostic tests and follow-up driving costs independent of demographics and treatment modality. Anticipating higher expenditures with prolonged survival and evolving treatment options is crucial for healthcare budget planning. Preparation of healthcare policies accordingly to these observations, which must include an overall increase in cost due to treatment duration and survival, remains a crucial aspect of budget control. Full article

Methane (CH₄) emissions from the wetlands of the Tibetan Plateau (TP) remain poorly quantified, particularly regarding their historical dynamics, spatial heterogeneity, and response to climate change. This study provides the high-resolution, observation-driven reconstruction of TP wetland CH₄ emissions over the past four decades, integrating a machine learning model with 108 flux measurements from 67 sites. This unique combination of field-based data and fine-scale mapping enables unprecedented accuracy in quantifying both emission intensity and long-term trends. We show that current TP wetlands emit 5.87 ± 1.43 g CH₄ m⁻² yr⁻¹, totaling 97.3 Gg CH₄ yr⁻¹, equivalent to 7.8% of East Asia’s annual wetland emissions. Despite a climate-driven increase in per-unit-area CH₄ fluxes, a 19.8% (8432.9 km²) loss of wetland area since the 1980s has reduced total emissions by 15%, counteracting the enhancement from warming and moisture increases. Our comparative analysis demonstrates that existing land surface models (LSMs) substantially underestimate TP wetland CH₄ emissions, largely due to the inadequate representation of TP wetlands and their dynamics. Projections under future climate scenarios indicate a potential 8.5–21.2% increase in emissions by 2100, underscoring the importance of integrating high-quality, region-specific observational datasets into Earth system models. By bridging the gap between field observations and large-scale modeling, this work advances understanding of alpine wetland–climate feedback, and provides a robust foundation for improving regional carbon budget assessments in one of the most climate-sensitive regions on Earth. Full article

Writing is essential across disciplines, yet undergraduate programs must balance writing instruction with discipline-specific content. To support writing development, we piloted an embedded writing tutor (WT) in two core public health courses serving primarily first-generation, low-income students of color. In this model, a tutor familiar with course content is integrated into the classroom to supplement traditional writing center support. Our aims were to examine (1) students’ perceptions of the WT compared to the university’s writing center, (2) the WT’s experiences and effective tutoring strategies, and (3) the instructor’s perspective on implementing the program. Using qualitative methods, the WT recorded field observations, the instructor compared course progression to prior semesters without embedded support, and students completed end-of-semester evaluations. Thematic analysis indicated that students valued the tutor’s accessibility, patience, and direct feedback, though perceived usefulness varied by course, likely due to differences in assignment structure. Challenges included role confusion and inconsistent feedback. Suggested improvements included requiring draft submissions, clarifying the tutor’s role, and aligning tutor and instructor feedback. Quantitative ratings of satisfaction were higher for the WT than for the writing center. Although the sample size was moderate (N = 79), these findings suggest embedded tutoring is a promising, equity-focused strategy for discipline-specific writing instruction. In the context of budget constraints in higher education, exploring alternative tutoring and pedagogical support models remains essential, particularly for underserved populations. Full article

Railway transportation systems have high accuracy and high integrity demands for safe localization. In the future, railway signaling is expected to rely on onboard sensors like Global Navigation Satellite Systems (GNSSs) in order to reduce installation and maintenance costs. GNSS position determination can, however, be highly degraded because of the presence of multipath on the train and railway environment. This paper tackles the characterization of multipath in code measurements caused exclusively by the antenna installation and derives a conservative error model of the antenna-installation-induced multipath and noise. First, we isolate multipath and noise from other GNSS errors using the Code-Minus-Carrier method. Second, an overbounding error model is derived. The limitation of modeling with restricted set of real data typically found in practice is discussed and we review methods that ensure the independence of samples. A new approach that creates separate data sets is ultimately proposed to derive an overbounding sigma. The presented methodology is supported by real measurements collected in an open-sky railway scenario. The derived models can be used as a reference nominal error models to build the null hypothesis of fault detection algorithms that detects the presence of excessive multipath in dynamic scenarios or as a part of a total error budget consideration. Full article

This study analyzes how museums in Brașov County integrated digital technologies into their activities during the COVID-19 pandemic, with a focus on online communication and audience interaction. This research is based on a mixed-methods approach, including content analysis, semi-structured interviews with museum representatives, and a questionnaire applied to the visiting public. The aim is to identify the digital strategies used, the challenges encountered, and visitors’ perceptions regarding the usefulness of these tools. The results indicate an accelerated but uneven adoption of digital technologies, influenced by available resources, internal competencies, and institutional support. Frequent online interaction is positively correlated with the perceived quality of digital content, and openness to virtual activities is higher among younger and more educated audiences. Identified limitations include the lack of specialized personnel, reduced budgets, and administrative difficulties. This study emphasizes the need for institutional reforms and investments in digitalization to ensure the sustainability of the digital transition, without losing the value of the physical museum experience. Full article

Massive wildfires release enormous amounts of biomass-burning (BB) aerosols into the atmosphere, which might have a major impact on its thermal and radiative budget, as well as the environment and human health. This work presents the results of a study and characterization of a long-range transport episode of smoke aerosols from Canadian forest fires towards the entirety of Europe, as observed over Sofia, Bulgaria, in early October 2023. This study makes use of data from combined lidar, ceilometer, and sun-photometer measurements, supported by model and forecast data, meteorological radiosonde profiling, and (re)analyses, together with tracking and mapping of the aerosol air transport. A distinctive feature of the considered episode over Europe is the downward movement of the air masses, entraining smoke aerosols from the continental mid-troposphere down to the near-surface layers. The driving mechanism of the long-range transport of BB aerosols and their spread over Europe is revealed. Optical parameters of the registered aerosols are determined and vertically profiled with a high range resolution by lidar data analysis. A wide set of columnar optical and microphysical aerosol characteristics is also provided by sun-photometer measurements. The results show a dominance of relatively fine modes of dry smoke particles in the submicron size range, with a predominantly low degree of non-sphericity, indicating minimal up-size aging during the BB aerosol transport from Canada to the Sofia region. The average daily aerosol radiative forcing is determined by sun-photometer measurements and briefly discussed. Full article

Although it is generally accepted that economic freedom stimulates economic growth, its effects in transitional economies are still up for debate. More empirical research is needed to examine the long-term effects of economic freedom on growth in the Western Balkans, a region characterised by uneven reform trajectories, fiscal pressures, and institutional fragility. This study examines the effects of seven fundamental factors on real GDP per capita growth (annual percentage change) in six Western Balkan nations between 2013 and 2023. These factors include property rights, government spending, government integrity, business freedom, monetary freedom, trade openness, and education spending. Importantly, in order to better capture macroeconomic constraints, it takes into account two fiscal burden indicators: the public debt and the government budget deficit. A triangulated analytical framework is used: Random Forest regression identifies non-linear patterns and ranks the importance of variables; Bayesian Vector Autoregression (VAR) models dynamic interactions and inertia; and the Generalised Method of Moments (GMM) handles endogeneity and reveals causal relationships. The GMM results show that while government integrity (β = −0.0820, p = 0.0206), government spending (β = −0.0066, p = 0.0312), and public debt (β = −0.0172, p = 0.0456) have negative effects on growth, property rights (β = 0.0367, p = 0.0208), monetary freedom (β = 0.0413, p = 0.0221), and the government budget deficit (β = 0.0498, p = 0.0371) have positive and significant effects on growth. Although the majority of economic freedom indicators are statistically insignificant, Bayesian VAR confirms strong growth persistence (GDP(−1) = 0.7169, SE = 0.0373). On the other hand, the Random Forest model identifies the most significant variables as property rights (3.72), public debt (5.88), business freedom (4.65), and government spending (IncNodePurity = 9.80). These results show that the growth effects of economic freedom depend on the context and are mediated by the state of the economy. Market liberalisation and legal certainty promote growth, but their advantages could be offset by inadequate budgetary restraint and difficulties with transitional governance. A hybrid policy approach, one that blends strategic market reforms with improved institutional quality, prudent debt management, and efficient public spending, is necessary for the region to achieve sustainable development. Full article

Understanding the growth dynamics and ecological constraints of Porphyra spp. is essential for optimizing sustainable seaweed aquaculture. However, most existing models lack physiological detail and exhibit limited performance under variable environmental conditions. This study developed a mechanistic Dynamic Energy Budget (DEB) model to simulate structural biomass accumulation, carbon and nitrogen reserve dynamics, and blade area expansion of Porphyra under natural environmental conditions in Korean coastal waters. The model incorporates temperature, irradiance, and nutrient availability (NO₃⁻ and CO₂) as environmental drivers and was implemented using a forward difference numerical scheme. Field data from Beein Bay were used for model calibration and validation. Simulations showed good agreement with the observed biomass, reserve content, and blade area, with root-mean-square error (RMSE) typically within ±10%. Sensitivity analysis identified temperature-adjusted carbon assimilation and nitrogen uptake as the primary drivers of growth. The model was further used to estimate dynamic carrying capacity, revealing seasonal thresholds for sustainable biomass under current farming practices. Although limitations remain—such as the exclusion of reproductive allocation and tissue loss—the results demonstrate that DEB theory provides a robust framework for modeling Porphyra aquaculture. This approach supports scenario testing, spatial planning, and production forecasting, and it is adaptable for ecosystem-based management including integrated multi-trophic aquaculture (IMTA) and climate adaptation strategies. Full article

This study models a three-level supply chain (farmer–retailer–government) incorporating farmer risk aversion. Under land capacity and fiscal budget constraints, it analyzes two subsidy strategies: area-based subsidies to farmers (SF) and volume-based subsidies to retailers (SR). Key findings include that when farmer land capacity exceeds a critical threshold and the fiscal budget is constrained, SF yields superior performance to SR. Conversely, with sufficient budgets, SR outperforms SF under high land capacity. Under moderate land capacity and unlimited budgets, both strategies exhibit equivalent effects. When land capacity falls below a critical threshold, government subsidies become unnecessary. The SF strategy demonstrates greater resilience against output uncertainty compared to SR. Under constrained budgets, SF is preferable; SR becomes more advantageous with abundant budgets. Critically, increasing risk aversion significantly reduces social welfare under both SF and SR strategies. This indicates neither subsidy mechanism effectively mitigates the adverse effects of farmer risk aversion. Full article

Coastal erosion is a growing concern in the Mediterranean region, where the combined effects of anthropogenic pressure, reduced fluvial sediment supply, and climate change-driven sea level rise and extreme storm events threaten the stability of sandy shorelines. This study examines the geomorphological impacts of the exceptional storm surge of 3 November 2023, associated with Storm Ciaran, which affected a vulnerable coastal segment north of the Morto Nuovo River in northern Tuscany (Italy). Using UAV-based photogrammetric surveys and high-resolution morphological analysis, we quantified shoreline retreat, dune toe regression, beach slope changes, and sediment volume loss. The storm induced an average shoreline retreat of over 5 m, with local peaks reaching 30 m, and a dune toe setback of up to 7 m. A net sediment budget deficit of approximately 1800 m³ was recorded, over 50% of the total volume added during soft nourishment interventions performed in the previous decade. Our findings highlight how a single high-energy event can match or exceed the annual average erosion rate, emphasizing the limitations of traditional shoreline-based monitoring and hard defense structures. This study highlights the importance of frequent, high-resolution monitoring focused on individual storm events, which is crucial to better understand their specific geomorphological impacts. Such detailed analyses help clarify whether long-term erosion trends are primarily driven by the cumulative effect of high-energy events. This knowledge is essential for identifying the most effective coastal protection strategies and for improving the design of defense structures. This approach is particularly relevant in the context of climate change, which is expected to increase the frequency and intensity of extreme events, making it imperative to base future planning on accurate, event-driven data. Full article

Net ecosystem productivity (NEP) serves as a key indicator for assessing regional carbon sink potential, with its dynamics regulated by nonlinear interactions among multiple factors. However, its driving factors and their coupling processes remain insufficiently characterized. This study investigated terrestrial ecosystems in Yunnan Province, China, to elucidate the drivers of NEP using 14 environmental factors (including topography, meteorology, soil texture, and human activities) and 21 remote sensing features. We developed a research framework based on “Feature Selection–Machine Learning–Mechanism Interpretation.” The results demonstrated that the Variable Selection Using Random Forests (VSURF) feature selection method effectively reduced model complexity. The selected features achieved high estimation accuracy across three machine learning models, with the eXtreme Gradient Boosting Regression (XGBR) model performing optimally (R² = 0.94, RMSE = 76.82 gC/(m²·a), MAE = 55.11 gC/(m²·a)). Interpretation analysis using the SHAP (SHapley Additive exPlanations) method revealed the following: (1) The Enhanced Vegetation Index (EVI), soil pH, solar radiation, air temperature, clay content, precipitation, sand content, and vegetation type were the primary drivers of NEP in Yunnan. Notably, EVI’s importance exceeded that of other factors by approximately 3 to 10 times. (2) Significant interactions existed between soil texture and temperature: Under low-temperature conditions (−5 °C to 12.15 °C), moderate clay content (13–25%) combined with high sand content (40–55%) suppressed NEP. Conversely, within the medium to high temperature range (5 °C to 23.79 °C), high clay content (25–40%) coupled with low sand content (25–43%) enhanced NEP. These findings elucidate the complex driving mechanisms of NEP in subtropical ecosystems, confirming the dominant role of EVI in carbon sequestration and revealing nonlinear regulatory patterns in soil–temperature interactions. This study provides not only a robust “Feature Selection–Machine Learning–Mechanism Interpretation” modeling framework for assessing carbon budgets in mountainous regions but also a scientific basis for formulating regional carbon management policies. Full article

The rapid expansion of urbanization and inadequate planning have triggered a water balance crisis in many cities, manifesting as both the need for artificial lake supplementation and frequent urban flooding. Using the Xuanwu Lake watershed in Nanjing as a case study, this research aims to optimize the Blue–Green Infrastructure (BGI) network to maximize rainfall utilization within the watershed. The ultimate goal is to restore natural water balance processes and reduce reliance on artificial supplementation while mitigating urban flood risks. First, the Soil Conservation Service Curve Number (SCS–CN) model is employed to estimate the maximum potential of natural convergent flow within the watershed. Second, drawing on landscape connectivity theory, a multi-level BGI network optimization model is developed by integrating the Minimum Cumulative Resistance (MCR) model and the gravity model, incorporating both hydrological connectivity and flood safety considerations. Third, a water balance model based on the Storm Water Management Model (SWMM) framework and empirical formulas is constructed and coupled with the network optimization model to simulate and evaluate water budget performance under optimized scenarios. The results indicate that the optimized scheme can reduce artificial supplementation to Xuanwu Lake by 62.2% in June, while also ensuring effective supplementation throughout the year. Annual runoff entering the lake reaches 13.25 million cubic meters, meeting approximately 13% of the current annual supplementation demand. Moreover, under a 100-year return period flood scenario, the optimized network reduces total watershed flood volume by 35% compared to pre-optimization conditions, with flood-prone units experiencing reductions exceeding 50%. These findings underscore the optimized BGI network scheme’s capacity to reallocate rainwater resources efficiently, promoting a transition in urban water governance from an “engineering-dominated” approach to an “ecology-oriented and self-regulating” paradigm. Full article

Despite continued efforts to improve the construction industry’s performance in terms of productivity, budget adherence, and schedule reliability, the sector remains a laggard compared to others. Among the innovative project management approaches aimed at addressing these issues are Advanced Work Packaging (AWP) and Integrated Project Delivery (IPD). This study conducts a comparative literature-based analysis of AWP and IPD, focusing on their performance outcomes and implementation challenges. Through a systematic review of 47 publications and key institutional reports, this study evaluates both methods across criteria such as adaptability, risk sharing, collaboration, workflow granularity, and cost-effectiveness. The results indicate that AWP excels in workflow standardization, package-level planning, and field execution, particularly in industrial and modular projects, while IPD demonstrates superior adaptability, stakeholder integration, and collaborative risk management in complex building projects. However, both methods face barriers including legal constraints, change resistance, and high integration costs. This study proposes context-specific recommendations and highlights potential synergies between AWP and IPD. While the analysis is constrained by limited empirical studies—especially regarding AWP—it lays a foundation for future research and offers actionable insights for project managers selecting between or integrating the two methods. Full article