Search Results (4,878)

Electricity spot prices jointly encode network physics and strategic bidding outcomes. In a well-functioning market, nodal and temporal price patterns tend to remain approximately invariant under mild perturbations-exhibiting symmetry-preserving regularities in distribution shape, spatial gradients, and temporal variation. Conversely, congestion binding, net-load stress, and abnormal bidding can induce symmetry breaking, manifested as heavy tails, mean shifts, and localized price discontinuities. This study develops a symmetry-guided and explainable diagnostic framework to identify price anomalies and attribute their dominant drivers. First, representative anomaly types (spike and mean shift) are defined using statistically and operationally motivated criteria, together with robustness checks across alternative thresholds. Second, principal component analysis is applied to construct compact, anomaly-specific feature sets, filtering weakly related variables while retaining system stress, congestion proxies, and renewable-induced variability indicators. Third, leveraging the optimization structure of market clearing and the associated KKT conditions, we characterize the price–feature linkage as a piecewise mapping and quantify each feature’s contribution via a sampling-based influence scoring procedure, yielding a ranked causal attribution. Case studies on a regional day-ahead spot market dataset demonstrate that the proposed framework achieves high consistency with expert assessments, with traceability accuracy exceeding 85% overall and particularly strong performance for spike-type anomalies. The method reduces reliance on purely manual diagnosis and black-box learning, and provides symmetry-oriented, actionable evidence for market surveillance and renewable-friendly flexibility and congestion management design. The proposed framework enables transparent identification of dominant structural drivers underlying different types of electricity price anomalies, linking observed price signals to market-clearing mechanisms. The results provide actionable diagnostic insights for market monitoring and regulatory assessment in electricity markets with high renewable penetration. Full article

Background: Climate change and air pollution are major threats to cardiopulmonary health, yet their population-level impacts in alpine regions remain insufficiently documented. Methods: This pilot study aimed to generate preliminary evidence and assess the feasibility of a larger investigation by examining associations between meteorological and air pollution variables and adult cardiopulmonary emergency department admissions in the canton of Valais, Switzerland. Results: Weekly admissions averaged 4.2 cases (range: 1–14), with peaks in late January and early February. Mean weekly temperature was inversely associated with admissions (IRR = 0.92), indicating higher demand during colder weeks. Ozone exposure showed a positive but non-statistically significant association with weekly cardiopulmonary admissions (IRR = 1.014), suggesting a potential signal that warrants confirmation in larger studies. A demographic–clinical risk index (age, sex, diabetes) was the strongest predictor of care demand (IRR = 1.52), exceeding the influence of individual environmental variables. Place of residence, municipality, and altitude were not significant predictors. Recruitment feasibility was high, with three refusals among 204 screened patients. Conclusions: These preliminary findings highlight the need for longitudinal, high-resolution studies and support integrating climate resilience into healthcare preparedness, early-warning systems, and sustainable health planning. Full article

This paper presents new techniques for electric machine diagnostics that combine advanced signal processing and artificial intelligence (AI)-based techniques using magnetic flux measurements acquired under various operating conditions. Developing an effective electric machine diagnostics tool is paramount for increased industrial productivity and extending the service life of the machine. The existing diagnostic tools face issues, including false indication of faults using classical methods, and the proposed data-driven methods based on machine learning lack transferability of model knowledge on an unseen dataset from different motor types or power ratings due to structural differences. To overcome these diagnostic drawbacks of statistical ML classifiers and classical approaches, innovative feature selection methods were employed in this work to preprocess the measured magnetic flux into a spectrogram image, and the transfer learning (TL) technique was applied to fine-tune convolution neural networks (CNNs) ImageNet pretrained models. The experimental results show the trained statistical ML classifiers and traditional CNN performance on unseen BU data and on the external data, and the performance demonstrated a lack of generalization on external datasets of different power ratings or structures. Models with such drawbacks cannot be used for developing effective diagnostic systems. The TL technique was employed on different deep CNN ImageNet pretrained models with spectrogram images as inputs to the deep CN network. This approach demonstrated an advanced and improved electric machine diagnostic system that addresses the drawbacks of the current ML-based diagnostic systems. The generalized model developed using CNN ResNet50 outperformed other deep CNN ImageNet models in correctly diagnosing faults on both the dataset generated from the authors’ lab and on an external dataset of a different machine from another research lab. Full article

Coal continues to play a significant role in Poland’s electricity generation system, making the sustainable management of environmental impacts from hard coal mining a critical challenge during the ongoing energy transition. In line with the European Green Deal and circular economy principles, reducing and managing mining-related waste emissions is an important component of sustainable development in regions undergoing a gradual phase-out of fossil fuel extraction. This study analyzes rock mass and dust emissions associated with underground hard coal mining in Poland over the period 2017–2025 using the most recent statistical data, including estimates for 2025 based on the first three quarters of the year. The scale, structure, and trends of emissions are examined to assess their implications for environmental sustainability, resource efficiency, and long-term land use. Particular attention is paid to the relationship between declining coal production and the relatively slower reduction in waste rock emissions, which indicates increasing contamination of extracted material and poses challenges for sustainable mining practices. The results show that while total coal output has decreased substantially, reductions in rock mass emissions have been less dynamic, highlighting the need for improved waste management strategies from a sustainability perspective. The study demonstrates that increasing the utilization of mining waste, through underground use and circular economy applications, can reduce environmental pressure, support compliance with sustainability policies, and mitigate long-term impacts on post-mining regions. Although the analysis focuses on Poland, the findings provide transferable insights for other countries seeking to balance energy security, mining sector restructuring, and sustainable development objectives during the transition away from fossil fuels. Full article

The Albufera of Valencia is a shallow, hypertrophic Mediterranean coastal lagoon. Since the 1970s, the lagoon has undergone substantial ecological deterioration, marked by the decline of macrophyte beds and the predominance of phytoplankton. The objective of this study was to monitor key water quality variables over a 10-year period (2015–2025) to assess the persistence of eutrophication and the current ecological status of the lagoon. For this purpose, a remote sensing approach was applied using the Sentinel-2 constellation, complemented by newly developed algorithms specifically calibrated with ten years of in situ field data (2016–2025). This approach was employed to estimate variables such as the chlorophyll-a (Chl-a) concentration as an indicator of phytoplankton biomass, suspended solids (S.S.), and Secchi disk depth (Z_SD). An analysis of temporal trends from 2017 to 2025 revealed a progressive system deterioration. The concentrations of both chlorophyll-a and suspended solids exhibited a statistically significant increasing trend (p < 0.01). Moreover, in line with these findings, water transparency (Z_SD) decreased significantly (p < 0.001). Thus, there has been a progressive deterioration in the trophic status and ecological quality of the lagoon over the last decade, despite prior management interventions. The results from this research highlight the need to implement more effective conservation strategies, such as regulating nutrient inputs and increasing the water renewal time in the lagoon. Full article

Closed-basin lakes are highly sensitive to climatic variability, yet for the Lake Van Basin (Türkiye), the dynamic and spatially heterogeneous linkages among atmospheric drivers and lake-level changes (particularly their lag structure and predictive directionality) remain insufficiently quantified in a unified multivariate setting. This study examines how temperature and precipitation jointly influence hydrological behavior in the Lake Van Basin using a multi-station Vector Autoregression (VAR) framework. By integrating long-term observations from multiple meteorological stations, the analysis explicitly captures the spatial heterogeneity that characterizes this complex endorheic system and provides a consistent basis for comparing station-specific dynamics. The results show strong persistence in lake-level dynamics across specifications, with lagged lake-level coefficients of 0.2595 to 0.3685 (p < 0.01), indicating a buffered endorheic response. Temperature exhibits a highly consistent seasonal dependence across stations, reflected by a uniformly negative and significant four-month temperature lag in the temperature equations (−0.34 to −0.42, p < 0.01). Granger-causality tests further indicate robust bidirectional coupling between temperature and precipitation in all station specifications (p < 0.01 and typically p ≤ 0.05), while climate-to-lake-level linkages remain spatially heterogeneous but are statistically supported across both Tatvan-based and Gevas-based specifications (Tatvan-Tatvan: p < 0.01 for both climate variables; Tatvan-Ahlat: temperature p = 0.000; Gevas-Van, Gevas-Ercis, and Gevas-Muradiye: temperature p = 0.000 and precipitation p = 0.013, 0.008, and 0.015, respectively). Distinct station-level patterns further demonstrate that topographical differences modulate the strength and direction of climate–hydrology linkages across the basin. By providing a coherent, causally consistent understanding of these interactions and explicitly incorporating season-specific VAR and Granger-causality evidence, this study offers a transferable methodological framework for analyzing climate-sensitive lake systems and highlights the need to incorporate temperature-driven processes into water-management and climate-adaptation strategies in endorheic basins. Full article

Health and hygiene are critical components of sustainable travel and tourism development, particularly in the post-emergency phase of the COVID-19 pandemic when traveler confidence is closely tied to the resilience of the destination. This paper examines global health and hygiene conditions using data from the Travel & Tourism Development Index (TTDI) 2024, with a focus on disparities across regions and income groups. Five key indicators—physician density, basic sanitation, basic drinking water, hospital bed density, and communicable disease incidence—are analyzed to assess healthcare infrastructure, accessibility, and public health resilience. By comparing data from 2021 and 2024, the study evaluates changes during and after the peak period of the COVID-19 crisis, highlighting progress and persistent inequalities relevant to sustainable travel and tourism development. Using descriptive statistics and Spearman’s rank correlation analysis, the study also investigates the associations between key health and hygiene indicators, specifically (i) basic sanitation and basic drinking water coverage and (ii) physician density and hospital bed density, at the global, regional, and income group levels. The results reveal pronounced regional and income-related disparities. Europe and Eurasia consistently outperform other regions, with high healthcare capacity and near-universal sanitation and water access, while Sub-Saharan Africa continues to face systemic deficits in all indicators. High-income countries have well-developed healthcare systems, whereas low-income countries struggle with limited physician availability, poor sanitation coverage, and high communicable disease incidence. Associations between key indicators are also evident: countries with strong sanitation infrastructure almost always achieve high drinking water coverage, and those with higher physician density typically maintain higher hospital bed capacity. These findings highlight the uneven pace of global recovery and emphasize that health and hygiene are not only public health priorities but also fundamental drivers of tourism competitiveness. Full article

Magnetite-rich iron ores present analytical challenges due to mineralogical complexity, including titanium–vanadium (Ti-V) substitution within magnetite and variable silicate gangue contributions. Reliable iron (Fe) quantification in such systems is essential for accurate resource evaluation and beneficiation planning, particularly in layered intrusion-hosted deposits. This study compares fusion-based inductively coupled plasma optical emission spectroscopy (ICP-OES) and fused-bead X-ray fluorescence (XRF) methods for the determination of Fe and associated major elements in magnetite-bearing Fe ores from the Bushveld Igneous Complex, South Africa. Four representative ore samples and certified reference materials were analysed using both techniques. Comparative statistical parameters like the t-test and F-test exhibit no significant differences in either precision and mean concentration between fused-based ICP-OES and fused-based XRF methods for the determination of Fe and other elements. The results indicate that, despite the existence of titanomagnetite and lithologies that are rich in silicates, both fusion-based methods provide consistent and reliable bulk chemical analysis datasets. While both approaches show suitability for routine chemical analysis, fusion-based ICP-OES offers a practical advantage in terms of throughput and operational efficiency. This work emphasises the importance of matching analytical methods with mineral ore characterisation in order to ensure reliable Fe grade determination in complicated oxide deposits. Full article

Metabolomics and lipidomics enable comprehensive profiling of metabolic states across diverse diseases and have generated a vast number of candidate biomarkers. Despite this progress, only a small fraction of metabolite-based biomarkers have achieved durable clinical translation. While this gap is often attributed to biological complexity or limited cohort size, increasing evidence suggests that failure more commonly reflects systematic misalignment between analytical measurement, biological interpretation, and clinical decision-making requirements. In this review, we argue that metabolites are not intrinsically unreliable biomarkers but are frequently overinterpreted as disease-specific indicators despite being highly context-dependent reporters of physiological state. We synthesize recurrent failure modes across the translational pipeline—including pre-analytical instability, ionization bias and semi-quantitative measurement, structural and annotation ambiguity, statistical overfitting, loss of disease specificity under systemic stress, and cohort-dependent performance collapse. Building on these insights, we propose a structured roadmap for the clinical translation of metabolite and lipid biomarkers. Rather than emphasizing further discovery, this framework prioritizes decision-oriented eligibility criteria encompassing pre-analytical robustness, analytical validity, molecular definition, biological interpretability, validation under real-world heterogeneity, and alignment with clinical utility and regulatory expectations. By reframing metabolic biomarkers as context-sensitive measurements embedded within clinical decision systems, this review provides practical guidance for investigators, clinicians, and regulators seeking to translate metabolomics and lipidomics into reliable tools for clinical practice. Full article

This study assesses the diversity, distribution, and ecological interactions of freshwater gastropod communities across eight sites in southern Iraq, spanning marshes, rivers, and canal systems within the Tigris-Euphrates basin. Diversity indices (Shannon–Wiener H′ and Pielou’s evenness J) were calculated to evaluate community structure, and a revised stacked bar chart of relative abundances revealed widespread dominance by species such as Melanoides tuberculata and Physella acuta, which frequently exceeded 50% of local assemblages. While P. acuta is an established invasive species, M. tuberculata is now considered native or long-established in the region. Species interactions were examined using Pianka’s niche overlap index, and null model testing (999 permutations) revealed only a few statistically significant overlaps (p < 0.05), suggesting that species co-occurrence is shaped more by environmental filtering than direct competition. To directly examine the influence of environmental drivers on species composition, Multiple Factor Analysis (MFA) was performed. MFA revealed patterns of association between dissolved oxygen, salinity, and species assemblages, suggesting these abiotic factors may influence community structure. To our knowledge, this study is the first in Iraq to use null models, constrained ordination, and MFA to investigate community assembly of freshwater gastropods, ultimately producing novel insights regarding the interactions between environmental stressors and aquatic biodiversity patterns. The results of this study highlight the need for long-term ecological monitoring and conservation in marshland habitats important for the resiliency of native species. Full article

Learning environments are increasingly expected to enable students to develop competencies necessary for addressing complex social, environmental, and technological challenges in sustainable societies. Within this context, instructional approaches that are inclusive, flexible, and learner-centered have gained increasing importance. This study investigates the effects of project-based learning (PBL) informed by Universal Design for Learning (UDL) principles on secondary school students’ 21st-century skills. Employing a mixed-methods embedded design, the quantitative component utilized a quasi-experimental pretest–posttest control group model. The study was conducted with 60 eleventh-grade students enrolled in a public high school, with one group receiving UDL-informed PBL instruction and the other following the standard curriculum. Data were collected using the 21st Century Learner Skills Usage Scale and analyzed through paired-samples t-tests, independent-samples t-tests, and ANCOVA. The findings revealed statistically significant improvements in the experimental group’s overall 21st-century skills, particularly in cognitive skills and collaboration and flexibility, with medium to large effect sizes. In contrast, the control group showed no meaningful gains, and a decline was observed in innovation skills. The results indicate that project-based learning informed by UDL principles constitutes an effective pedagogical approach for fostering inclusive and sustainable learning environments that support the development of future-oriented learner competencies. These findings further suggest that integrating UDL principles into project-based instructional models may contribute to competency-oriented and inclusive secondary education systems aligned with sustainability frameworks. Full article

Despite the economic relevance of climate-transition risk, firm-level carbon exposure often fails to appear as a robustly priced factor when ESG measures and sustainability shocks are conflated. This study examines whether carbon exposure is conditionally priced in European equity returns using a strongly balanced quarterly panel of 238 firms from the MSCI Europe ESG Leaders universe (2018–2024). Total greenhouse gas emissions act as a proxy for carbon exposure, mapped to within-year percentiles and standardized by sector-year. Regressions control for ESG scores and controversies and include firm and quarter fixed effects with firm-clustered, dependence-robust standard errors. The linear carbon coefficient is small and statistically indistinguishable from zero, indicating no stable return premium from within-firm changes in carbon exposure. Functional-form tests reject linearity: quadratic and quintile specifications reveal curvature and a non-monotonic pattern, with return differences concentrated in the middle of the carbon distribution. Conditioning on macro-financial stress, measured by the ECB Composite Indicator of Systemic Stress, yields limited evidence of a uniform carbon penalty. However, high-controversy states are associated with lower returns, while ESG scores show negative associations under dependence-robust inference. Overall, carbon-related pricing appears to be nonlinear and state-dependent, whereas controversy risk is the most robust sustainability predictor of returns. Full article

Teacher shortages have become a global phenomenon, affecting educational systems across many countries. However, the strategies adopted to address it differ considerably. This study gives a first, detailed account of the reasons and effects of teacher shortages in Austria. For this purpose, a number of documents were analysed: 120 newspaper reports (to mirror the public debate), 43 parliamentary questions and ministerial responses (to mirror the policy debate), and relevant national statistics (to mirror the current situation and remedial measures by quantitative indicators). This allows a first comprehensive synthesis of public debate, policy developments, and research—comparable to country reports for other countries but currently missing for Austria. The findings of these multiple sources reveal that, following a period in the early 2000s with sufficient applicants for teaching positions, Austria gradually experienced an emerging teacher shortage. Initial responses were ad hoc, relying on measures such as increased overtime and the employment of underqualified teaching staff. More comprehensive strategies were introduced only in 2022, including a public image campaign for the teaching profession, reforms in teacher education, and new pathways for career changers. The study concludes by discussing implications for the teaching profession, school practice, and the teacher education system. Full article

Microbial bioprospecting in contaminated environments is a promising strategy for identifying biosurfactant-producing bacteria; however, translating environmentally adapted strains into predictable cultivation processes remains challenging. In this study, a microbial consortium subjected to long-term evolutionary laboratory adaptation in oily sludge was investigated to evaluate strain-specific phenotypic responses related to biosurfactant production. Phylogenetic analysis based on 16S rDNA sequencing identified three taxonomically distant isolates: Faucicola sp. strain BS5C, Pseudomonas sp. strain BS16B, and Enterobacter sp. BS14MR. Biosurfactant production was evaluated using a sequential Design of Experiments (DOE) approach, including fractional factorial and central composite rotatable designs, with the emulsification index (E24) used as a semi-quantitative response variable. Initial screening revealed a statistically significant negative effect (p < 0.10) of high dextrose concentrations for all isolates. Strain-specific differences in model adequacy were observed, with a statistically adequate quadratic model obtained for Pseudomonas sp. BS16B (R² = 0.8658, p = 0.0225), whereas the other isolates showed significant lack of fit (p < 0.05). ATR-FTIR analysis revealed spectral profiles consistent with lipopeptide-like compounds. Overall, these results indicate that isolates derived from the same long-term adapted system may differ substantially in process predictability, suggesting that productivity-based screening alone may be insufficient for selecting robust strains. Full article

Urban river degradation demands remediation strategies that are both environmentally sustainable and technically feasible. This study evaluated the performance of Floating Treatment Wetlands (FTWs) vegetated with Chrysopogon zizanioides (vetiver) and incorporating four substrate configurations: leaf litter (LL), red volcanic rock (RVR), corn cobs (CC), and a composite mixture of all three, for the rehabilitation of the “Paseo de Los Ahuehuetes” River in Veracruz, Mexico. Over a 182-day monitoring period, in situ water quality parameters and plant growth responses were systematically assessed. The results indicate that substrate selection is a decisive design factor governing the establishment and development of C. zizanioides in FTWs. Among the substrates tested, LL exhibited the most favorable performance, achieving the highest plant survival (82%), enhanced shoot elongation (71.5 ± 12.1 cm), greater root development (49.7 ± 10.0 cm), and the highest relative growth rate (0.028 g g⁻¹ d⁻¹), with statistically significant differences (p < 0.05) compared to CC. Additionally, localized improvements in water quality within the FTW zone were observed, including an increase in dissolved oxygen (2.07%) and a reduction in total dissolved solids (5.65%), likely associated with intensified rhizospheric processes. Overall, these findings identify leaf litter as a low-cost, locally available, and environmentally sustainable substrate that enhances vetiver establishment in FTWs. The study provides practical, evidence-based criteria for the design of nature-based phytoremediation systems aimed at the restoration of urban river ecosystems. Full article