Search Results (236)

This study investigates how temporal fluency cues shape human ratings of L2 English pronunciation in Korean learners, using a large read-speech corpus annotated with five-point pronunciation scores. We focus on two timing-derived measures—articulation rate (AR) and mean silence duration (SilMean)—and examine whether these cues predict (i) articulation-accuracy ratings and (ii) prosody/fluency ratings. To account for dependencies in corpus data and to control for key learner- and task-level covariates, we fitted cumulative link mixed models with random intercepts for speakers and scripts, including proficiency band (ability), age, gender, and test type as fixed effects. Across models, faster articulation and shorter silent intervals were associated with higher articulation ratings, and a combined model including both AR and SilMean provided the best fit (lowest AIC). Temporal cues were even more strongly associated with prosody ratings, supporting construct alignment between timing measures and the prosody dimension of the rubric. Marginal predicted probabilities illustrate how the likelihood of receiving high ratings (score ≥ 4) increases with AR across proficiency and linguistic-complexity strata (with SilMean held constant), and how long silent intervals reduce these probabilities when AR is held constant. These findings indicate that temporal organization provides robust information about perceived pronunciation quality in read L2 speech and underscore the importance of construct-aware modeling when developing AI-based scoring and feedback systems trained on human-labeled data. Full article

This study proposes a hybrid forecast-enabled adaptive crowbar coordination strategy to enhance low-voltage ride-through (LVRT) performance of doubly fed induction generator (DFIG) wind turbines. A unified electro-mechanical model in the αβ/dq frames with dual closed-loop control for rotor- and grid-side converters is built in MATLAB/Simulink (R2018b), and LVRT constraints on current safety and DC-link energy are explicitly formulated, yielding an engineering crowbar-resistance range of 0.4–0.8 p.u. On the forecasting side, a CEEMDAN-based decomposition–modeling–reconstruction pipeline is adopted: high- and mid-frequency components are predicted by a dual-stream Informer–LSTM, while low-frequency components are modeled by XGBoost. Using six months of wind-farm data, the hybrid forecaster achieves best or tied-best MSE, RMSE, MAE, and R² compared with five representative baselines. Forecasted power, ramp rate, and residual-based uncertainty are mapped to overcurrent and DC-link overvoltage risk indices, which adapt crowbar triggering, holding, and release in coordination with converter control. In a 9 MW three-phase deep-sag scenario, the strategy confines DC-link voltage within ±3% of nominal, shortens re-synchronization from ≈0.35 s to ≈0.15 s, reduces rotor-current peaks by ≈5.1%, and raises the reactive-support peak to 1.7 Mvar, thereby improving LVRT safety margins and grid-friendliness without hardware modification. Full article

Interactions between surface water and groundwater in arid regions regulate their response to climate and human impacts. In the salar systems of the Altiplano-Puna plateau (Bolivia, Chile, Argentina), understanding how surface waters connect to groundwater is crucial for accurate modeling and assessment. This study introduces new data and analysis using subsurface thermal profiles and modeling to identify flow patterns and possible surface water links. We document, to our knowledge, for the first time in the literature, deep-seated cooling of the subsurface caused by extreme evaporation rates. The subsurface is cooled by 4–5 degrees Celsius below the mean annual air temperature to depths greater than 50 m, even though groundwater inflow waters are elevated by 10 degrees °C due to geothermal heating. Three thermal zones are observed along the southern edge of Salar de Atacama, with temperature dropping from 28 °C to about 12 °C over 2.5 km. A 2D numerical model of groundwater and heat flow was developed to test various hydrological scenarios and understand the factors controlling the thermal regime. Two flow scenarios at the southern margin were examined: a diffuse flow model with uniform flow and flux to the surface and a focused flow model with preferential discharge at a topographic slope break. Results indicate that the focused flow scenario matches thermal data, with warm inflow water discharging into a transition zone between freshwater and brine, cooling through evaporation, re-infiltration, and surface flow, then re-emerging near lagoons at the halite nucleus margin. This research offers valuable insights into the groundwater hydraulics in the Salar de Atacama and can aid in monitoring environmental changes causally linked to lithium mining and upgradient freshwater extraction. Full article

Background: Mechanical loading is a fundamental regulator of bone remodelling; however, the mechanotransduction mechanisms governing alveolar bone adaptation under tensile-dominant orthodontic loading remain insufficiently defined. In particular, the molecular pathways associated with tension-driven cortical modelling in the periodontal ligament (PDL)–bone complex have not been systematically interpreted in the context of advanced biomechanical simulations. Methods: A nonlinear finite element model of the alveolar bone–PDL–tooth complex was developed using patient-specific CBCT data. Three loading configurations were analysed: (i) conventional orthodontic loading, (ii) loading combined with corticotomy alone, and (iii) a translation-dominant configuration generated by the Bone Protection System (BPS). Pressure distribution, displacement vectors, and stress polarity within the PDL and cortical plate were quantified across different bone density conditions. The mechanical outputs were subsequently interpreted in relation to established mechanotransductive molecular pathways involved in osteogenesis and angiogenesis. Results: Conventional loading generated compression-dominant stress fields within the marginal PDL, frequently exceeding physiological thresholds and producing moment-driven root displacement. Corticotomy alone reduced local stiffness but did not substantially alter stress polarity. The BPS configuration redirected loads toward a tensile-favourable mechanical environment characterised by reduced peak compressive pressures and parallel (translation-dominant) displacement vectors. The predicted tensile stress distribution is compatible with activation profiles of key mechanosensitive pathways, including integrin–FAK signalling, Wnt/β-catenin–mediated osteogenic differentiation and HIF-1α/VEGF-driven angiogenic coupling, suggesting a microenvironment that may be more conducive to cortical apposition than to resorption. Conclusions: This study presents a computational–molecular framework linking finite element–derived tensile stress patterns with osteogenic and angiogenic signalling pathways relevant to alveolar bone remodelling. The findings suggestthat controlled redirection of orthodontic loading toward tensile domains may shift the mechanical environment of the PDL–bone complex toward conditions associated with osteogenic than resorptive responses providing a mechanistic basis for tension-induced cortical modelling. This mechanobiological paradigm advances the understanding of load-guided alveolar bone adaptation at both the tissue and molecular levels. Full article

This study pioneers an examination of the moderating role of supply chain management in the relationships between globalisation (financial, social and trade) and energy transition (implicit and explicit) for the BRICS nations using data from 2005 to 2022. In doing so, we employ a series of second-generation panel regression techniques. The results show that stronger supply chain management acts as a central engine of transition, particularly boosting explicit deployment when combined with supportive financial openness, while trade-linked interactions also enhance implicit efficiency. At the same time, rapid economic growth and deeper urbanisation tend to erode implicit gains and provide only limited support for explicit capacity build-out. Knowledge management and financial development emerge as short-run double-edged mechanisms as they support process-oriented improvements. The differentiated roles of globalisation are crucial, with financial globalisation consistently supporting explicit transition, social globalisation correlating with weaker explicit progress, and trade openness becoming strongly beneficial only when aligned with robust supply chain capabilities, while both social and trade integration dampen the marginal effectiveness of supply chain improvements. The study proposed policies based on these findings. Full article

This study examines the relationship between national open educational resource (OER) policies and Sustainable Development Goal 4 (SDG4) outcomes across 187 countries between 2015 and 2024, with particular attention to the moderating role of artificial intelligence (AI) readiness. Despite widespread optimism about digital technologies as catalysts for universal education, systematic evidence linking formal OER policy frameworks to measurable improvements in educational access and completion remains limited. The analysis employs fixed effects and difference-in-differences estimation strategies using an unbalanced panel dataset comprising 435 country-year observations. The research investigates how OER policies associate with primary completion rates and out-of-school rates while testing whether these relationships depend on countries’ technological and institutional capacity for advanced technology deployment. The findings reveal that AI readiness demonstrates consistent positive associations with educational outcomes, with a ten-point increase in the readiness index corresponding to approximately 0.46 percentage point improvements in primary completion rates and 0.31 percentage point reductions in out-of-school rates across fixed effects specifications. The difference-in-differences analysis indicates that OER-adopting countries experienced completion rate increases averaging 0.52 percentage points relative to non-adopting countries in the post-2020 period, though this estimate remains statistically imprecise (p equals 0.440), preventing definitive causal conclusions. Interaction effects between policies and readiness yield consistently positive coefficients across specifications, but these associations similarly fail to achieve conventional significance thresholds given sample size constraints and limited within-country variation. While the directional patterns align with theoretical expectations that policy effectiveness depends on digital capacity, the evidence should be characterized as suggestive rather than conclusive. These findings represent preliminary assessment of policies in early implementation stages. Most frameworks were adopted between 2019 and 2022, providing observation windows of two to five years before data collection ended in 2024. This timeline proves insufficient for educational system transformations to fully materialize in aggregate indicators, as primary education cycles span six to eight years and implementation processes operate gradually through sequential stages of content development, teacher training, and institutional adaptation. The analysis captures policy impacts during formation rather than at equilibrium, establishing baseline patterns that require extended longitudinal observation for definitive evaluation. High-income countries demonstrate interaction coefficients between policies and readiness that approach marginal statistical significance (p less than 0.10), while low-income subsamples show coefficients near zero with wide confidence intervals. These patterns suggest that OER frameworks function as complementary interventions whose effectiveness depends critically on enabling infrastructure including digital connectivity, governance quality, technical workforce capacity, and innovation ecosystems. The results carry important implications for how countries sequence educational technology reforms and how international development organizations design technical assistance programs. The evidence cautions against uniform policy recommendations across diverse contexts, indicating that countries at different stages of digital development require fundamentally different strategies that coordinate policy adoption with foundational capacity building. However, the modest short-term effects and statistical imprecision observed here should not be interpreted as evidence of policy ineffectiveness, but rather as confirmation that immediate transformation is unlikely given implementation complexities and temporal constraints. The study contributes systematic cross-national evidence on aggregate policy associations while highlighting the conditional nature of educational technology effectiveness and establishing the need for continued longitudinal research as policies mature beyond the early implementation phase captured in this analysis. Full article

Hydrological behavior plays a critical role in seasonally dry forest ecosystems, as it underpins water availability for multiple productive activities, including forestry, agriculture, grazing, and urban supply. This study evaluated the hydrological effects of thinning treatments in a semi-arid oak–pine forest of Chihuahua, Mexico, using a Before–After–Control–Impact (BACI) design. Three Micro-catchments (MC) with initially comparable tree density and canopy cover were monitored during the rainy seasons of 2018 (pre-thinning) and 2019 (post-thinning). Thinning treatments were applied at 20% and 60% canopy cover in two MC, while a third remained unthinned as a 100% control. Precipitation and surface runoff were recorded at the event scale, and data were analyzed using Weibull probability models with a log link to capture the frequency and magnitude of runoff events. Precipitation patterns were broadly comparable across years, although 2018 included an extreme storm event (59 mm). In contrast, runoff volumes in 2019 were lower despite marginally higher seasonal rainfall, reflecting the absence of large storms. Statistical modeling indicated that for each additional millimeter of precipitation, mean runoff increased by approximately 12%, although thinning significantly altered baseline conditions. Relative to 2018, mean runoff ratios were 0.087 in the 100% canopy catchment, 0.296 in the 60% treatment, and 0.348 in the 20% treatment, suggesting that reduced canopy cover retained proportionally more runoff than the control. BACI contrasts confirmed that thinned catchments maintained higher proportions of runoff than the unthinned control, although statistical significance was marginal for the 20% canopy treatment. Overall, the study provides ecohydrological insights relevant to the management of semi-arid forest ecosystems. Full article

In the effort to mitigate climate change, the Marine Hydrokinetic (MHK) energy from ocean currents emerges as an important renewable source due to its large potential, although it remains underexploited. In the Southwestern Tropical Atlantic, surface potentials linked to the North Brazil Current (NBC) are known, but the subsurface North Brazil Undercurrent (NBUC) remained unquantified. This study addressed this gap by applying a two-step approach using more than 20 years of high-resolution (1/12°) climatological and daily reanalysis data to estimate current power density (CPD) throughout the water column along the Brazilian shelf (4° N–12° S), with focus on energetic hotspots where maximum CPD exceeds 1000 W m⁻². The climatological analysis revealed 12 persistent hotspots (H1–H12). Daily analyses show highly energetic but seasonally variable surface hotspots north of 4° S linked to the NBC (H4–H12; >885 W·m⁻²) and weaker but more stable subsurface hotspots south of 4° S associated with the NBUC at depths of 130–266 m (H1–H3; 831–808 W·m⁻²). These patterns are likely influenced by flow–topography interactions along the continental margin. Overall, subsurface resources exhibit greater reliability than surface counterparts, highlighting the importance of incorporating subsurface dynamics in future MHK assessments and development along the Brazilian margin. Full article

District heating networks (DHNs) are a key technology in the transition toward sustainable heat supply, increasingly integrating renewable sources and thermal energy storage. High-temperature aquifer thermal energy storage (HT-ATES) can enhance DHN efficiency by shifting heat production over time, potentially reducing both costs and greenhouse gas emissions. However, most life cycle assessments (LCAs) remain static, rely on average data, and neglect temporal dispatch dynamics and marginal substitution among heat sources for environmental evaluation. This study introduces a dynamic life cycle inventory framework that explicitly links HT-ATES-operation scheduling in DHNs with marginal life cycle data. The framework expands system boundaries to capture time-varying changes in heat composition, combines a district heating merit-order representation (distinguishing must-run and flexible capacities) with linear programming to determine least-cost dispatch, and translates marginally displaced technologies into environmental and economic consequences. Foreground inputs are derived from an existing third-generation DHN (heat demand, generation assets, efficiencies) and publicly available energy carrier cost data and are linked to consequential background inventory datasets (ecoinvent). The framework is demonstrated for one year of operation for an HT-ATES concept with 50 GWh of injected heat. Hourly resolved results identify the marginally displaced technologies and indicate annual reductions of 5.86 kt CO₂e alongside cost savings of EUR 1.09 M. A comparison of alternative operation schedules shows strong sensitivity of both economic and environmental performance to operational strategy. Overall, the proposed framework provides a replicable and adaptable basis for consequential assessment of HT-ATES operation in DHNs and supports strategic decision-making on seasonal thermal storage deployment in low-carbon heat systems. Full article

Background/Objectives: Evidence links children’s health-related quality of life (HRQoL) to overall diet, but data on specific, actionable habits are limited. We tested whether vegetable intake ≥2 portions/day and fish intake ≥2–3 times/week were associated with risk of low HRQoL (KIDSCREEN-10 Index score <40) and assessed their joint effect and robustness to overall diet quality. Methods: In three waves (2020–2023) in Madrid (Spain), 1127 observations from 771 children (8–12 years) were analysed. Logistic Generalised Estimating Equations (GEE) adjusted for age, sex, socioeconomic status (four levels), moderate-to-vigorous physical activity (MVPA), screen time, body mass index (BMI) z-score, wave and school ownership. Marginal predicted probabilities were computed for four exposure combinations (neither, vegetables only, fish only, both). Sensitivity models added school area and the Mediterranean Diet Quality Index (KIDMED; KIDMED_wo_FV and total); hybrid within–between GEE and a linear mixed model for continuous KIDSCREEN-10 were also fitted. Results: Vegetables ≥2/day and fish ≥2–3/week were inversely associated with low HRQoL (odds ratio (OR) 0.49 (95% confidence interval (CI) 0.30–0.82) and 0.61 (0.43–0.87)). The interaction was positive (OR 2.50 (1.39–4.53)). Adjusted probabilities were 40.1% (neither), 25.8% (vegetables only; −14.3 percentage points (p.p.)), 29.7% (fish only; −10.5 p.p.), and 34.0% (both; −6.1 p.p.). Findings persisted with KIDMED_wo_FV and attenuated with total KIDMED. MVPA related inversely and screen time directly to risk. Conclusions: Vegetables ≥2/day and fish ≥2–3/week were associated with lower odds of low HRQoL, with non-additive combined effects. These simple targets may complement physical-activity promotion and reduced screen time; longitudinal/experimental studies should test causality and dose–response. Full article

Buildings account for nearly 32% of global energy consumption and serve as key demand-side flexibility resources in power systems with high renewable penetration. However, their utilization is constrained by the lack of an integrated framework that can jointly quantify energy-adjustable margin (BAM) and response duration (RD) under realistic operational and thermal comfort constraints. This study presents a coupled data–physical simulation framework integrating a Particle Swarm Optimization–Long Short-Term Memory–Random Forest (PSO-LSTM-RF) hybrid load forecasting model with EnergyPlus(24.1.0)-based building simulation. The PSO-LSTM-RF model achieves high-accuracy short-term load prediction, with an average R² of 0.985 and mean absolute percentage errors of 1.92–5.75%. Predicted load profiles are mapped to physically consistent baseline and demand-response scenarios using a similar-day matching mechanism, enabling joint quantification of BAM and RD under explicit thermal comfort constraints. Case studies on offices, shopping malls, and hotels reveal significant heterogeneity: hotels exhibit the largest BAM (up to 579.27 kWh) and longest RD (up to 135 min), shopping malls maintain stable high flexibility, and offices show moderate BAM with minimal operational disruption. The framework establishes a closed-loop link between data-driven prediction and physics-based simulation, providing interpretable flexibility indicators to support demand-response planning, virtual power plant aggregation, and coordinated optimization of source–grid–load interactions. Full article

Transarterial radioembolization (TARE) is an established therapy for primary and secondary hepatic malignancies. Outcomes depend heavily on dosimetry, which has evolved from empirical and body-surface-area methods to partition and voxel-based approaches. This review summarizes current evidence for advanced (personalized) dosimetry across tumor types, highlights emerging dose–response concepts, and outlines practical barriers and implementation strategies. A narrative review of peer-reviewed clinical studies and trials evaluating dosimetry in TARE, with emphasis on hepatocellular carcinoma (HCC), intrahepatic cholangiocarcinoma (iCCA), metastatic colorectal cancer (mCRC), neuroendocrine tumor (NET), and breast cancer liver metastases, was performed with comparison of single-compartment medical internal radiation dosimetry method (MIRD), partition (multicompartment) methods, and voxel-based dosimetry methodologies. Personalized dosimetry improves outcomes in multiple tumor types. A randomized trial in HCC showed superior overall survival with partition-based dosing versus MIRD. In selective HCC treatments, voxel-derived metrics (e.g., D95) correlate with complete pathologic necrosis, suggesting benefit beyond mean dose targets. For iCCA, data associate higher tumor doses with better radiologic response, progression-free survival, and downstaging. In mCRC, voxel-based and threshold analyses link specific tumor and margin doses with metabolic/radiographic response and survival. Smaller series in NET and breast cancer indicate dose–response relationships using advanced dosimetry. Evidence supports broader adoption of advanced dosimetry in TARE. Emerging strategies that ensure adequate coverage of the “coldest” tumor regions and thoughtful particle-load planning may further optimize results. Standardized protocols, prospective validation, and scalable workflows are needed to accelerate implementation. Full article

Under China’s “dual carbon” targets and deepening global climate governance, this paper investigates whether and how corporate green transformation (GTF) improves carbon performance (CP). Using panel data on Chinese A-share listed firms from 2008 to 2023 and multiple causal identification strategies (fixed effects, RD, DID and PSM), we find that GTF significantly enhances CP, with stronger marginal effects for firms with poorer initial carbon performance. Mechanism analyses show that carbon disclosure (CD) acts as a positive mediator in the GTF–CP nexus, whereas executives’ green perception (EGP) exerts a short-term suppressing effect. Policy analyses further indicate that the 2012 pilot emissions trading schemes and the 2021 national carbon market amplify the positive impact of GTF on CP, but local “compliance traps” around industry medians suggest strategic use of allowance trading. The study integrates EGP and CD into a cognition–disclosure framework linking GTF and CP and provides evidence on the emission-reduction effects of GTF under evolving carbon policies, with implications for carbon market design and corporate low-carbon governance. Full article

Cement production in Africa remains carbon-intensive, primarily due to the use of coal-based thermal energy. This study conducts a comparative cradle-to-gate life cycle assessment (LCA) of cement production using 100% coal (Scenario A) against partial substitution with refuse-derived fuel (RDF) at a 20% thermal input rate (Scenario B), with case studies in South Africa and Ethiopia. The LCA, modeled in SimaPro 9.2.0.1 with Ecoinvent v3.7.1 and regional data, evaluates midpoint environmental impacts across the following five stages: raw materials, clinker production, electricity, fuel use, and transportation. The results show that Scenario B reduces the global warming potential (GWP) by 3.3–4.2% per kg of cement, with minimal increases in other impact categories. When avoided landfill methane is accounted for, GWP reduction improves to 6.7%. Fossil resource depletion drops by 10%, and toxicity and particulate emissions show marginal improvements. Economic analysis under South Africa’s 2025 carbon policy reveals a modest net cost increase of $2–3 per ton of cement and an abatement cost of $64–87 per ton of CO₂. The study provides new insights by harmonizing LCA models across national contexts, linking emissions reductions to economic instruments, and quantifying the co-benefits of RDF for waste management. The results support RDF co-processing as a scalable mitigation strategy for the African cement sector, recommending substitution rates of 15–30%, policy alignment, and enhancement of the RDF supply chain to maximize impact. Full article

This study introduces the Product Variety Costing Method (PVCM), a data-driven framework that addresses the limitations of existing costing approaches, which fail to accurately present the cost of product and part variety, thereby constraining cost-informed decision-making in modular product development. Traditional cost allocation methods often lack one or more of the following: a full life-cycle perspective, a lower level of granularity according to the product structure, or a combined integration of qualitative and quantitative data. The PVCM bridges these gaps by combining Time-Driven Activity-Based Costing (TDABC) with hierarchical product structures and empirical enterprise data, enabling the quantification of variety-induced resource consumption across components, subsystems, and complete products. An industrial application demonstrates that the PVCM enhances cost accuracy and transparency by linking resource use directly to specific product abstraction levels, thereby highlighting the true cost impact of product variety. In this case, results revealed deviations of up to 60% in the adjusted contribution margin ratio relative to traditional overhead-based methods, clearly indicating the influence of product variety on cost assessments. The method supports design and managerial decision-making by allowing evaluation of modularization based on detailed cost insights. While the study’s scope is limited to selected life-cycle phases and a single company case, the findings highlight the method’s future potential as a generalizable tool for evaluating economic benefits of modularization. Ultimately, the PVCM contributes to a more transparent and analytically grounded understanding of the cost of variety in complex product portfolios. Full article