Search Results (5,914)

This article examines how grassroots civic mobilization can drive the transition from solid fuel combustion to low-emission urban heating systems, using the Kraków Smog Alert (KSA) as a case study. Employing the Multi-Level Perspective (MLP) framework alongside sociological theories of resource mobilization, frame analysis, and political opportunity structures, the study analyses the mechanisms through which civil society actors can shape energy policy and accelerate emission reduction at the urban scale. The empirical focus is the city of Kraków, Poland, historically one of Europe’s most severely air-polluted cities due to widespread domestic coal and wood combustion for heating. The study draws on documentary analysis, legislative records, stakeholder mapping, and expert interviews conducted within the CO-SUSTAIN research project (Horizon Europe, 2024–2026). The investigation traces KSA’s trajectory from a social media initiative founded in 2012 to the Polish Smog Alert, a national coalition encompassing nearly fifty local groups, culminating in a binding municipal ban on solid fuel combustion in 2019 and a subsequent reduction in PM2.5 concentrations exceeding 60% by 2023. Key strategic mechanisms identified include reactive scaling, health-based reframing of air quality as a public health issue, media amplification, and cooperative institutional engagement with regulatory bodies. An MLP chronological analysis spanning 1945 to 2024 maps landscape, regime, and niche dynamics that enabled the anti-smog energy transition; stakeholder mapping spans actors across NGOs, public institutions, media, and civil society. Findings demonstrate that landscape-level pressure from EU air quality and environmental protection directives alone was insufficient to drive regime change in domestic fuel use without credible, evidence-based niche actors capable of building alliances with institutional stakeholders. The findings offer transferable insights for coal-dependent cities across Central and Eastern Europe seeking to replace solid fuel heating with low-emission alternatives through integrated approaches combining environmental monitoring, energy policy reform, and civic governance. These findings matter for cities across Central and Eastern Europe still reliant on solid-fuel domestic heating, offering evidence-based guidance for civil society organizations and municipal policymakers seeking to accelerate the low-emission transition while protecting public health. Full article

Groundwater is essential for drinking and irrigation to ensure a stable life and economic development, especially in semi-arid to arid rural areas such as the Lagnadiz district in central Morocco. However, its occurrence is highly variable in discontinuous media because of its uneven circulation along fractures, making it difficult to locate productive drilling sites. This study aimed to identify suitable locations for the establishment of productive wells by combining Sentinel-1 and Sentinel-2 imagery, a DEM, and geological data. Lineaments were automatically extracted and validated using Google Earth imagery, slope and hillshade maps, and field observations. Six thematic layers (lithology, drainage density, distance to faults, slope, lineament density, and lineament intersection density) were weighted using the Analytic Hierarchy Process and integrated through Weighted Linear Combination. The resulting groundwater potential map shows that high potential areas cover 38.53% of the study area, followed by moderate potential areas (34.84%) and low potential areas (26.63%). A ±10% weight sensitivity analysis showed strong map stability, with r values of 0.9949–0.9999 and class agreement rates of 93.31–99.61%. The map was independently validated using exploitation-yield data from 22 boreholes that were not involved in its construction. Using a productivity threshold of 5 m³/h, the ROC analysis produced an AUC of 0.795, with a 95% confidence interval ranging from 0.581 to 0.949, indicating an acceptable ability of the GWPI map to distinguish between the two productivity groups. Full article

Shearer trailing cable faults are difficult to distinguish from terminal measurements because their signatures coexist with changes in load, source imbalance, cable temperature, and sensor error. This study presents a physics-guided categorical Mamdani framework supported by a distributed-parameter source, cable, and load model. A total of 180 simulations cover normal operation, phase-to-ground faults, A–B inter-phase short circuits, conductor-resistance degradation, and insulation-path deterioration over multiple severities, locations, motor loads, source imbalance levels, and temperatures. Paired pre-fault and post-fault changes in load-terminal voltage unbalance, source-terminal zero-sequence current ratio, and source-to-load voltage attenuation are mapped to fault path-based membership functions and diagnostic rules. Twenty repeated 70/30 holdouts grouped by base operating condition compare the proposed method with a deterministic threshold tree, radial-basis-function support vector machine, and k-nearest-neighbor classifier. Across these repeated grouped holdouts, the proposed method achieves 99.80% mean accuracy with a standard deviation of 0.63 percentage points on noise-free test cases. Accuracy remains 81.12% and 74.71% under 1% and 2% RMS waveform noise, respectively. These results demonstrate the effectiveness of the proposed framework for interpretable diagnosis of shearer power-core cable faults across the investigated simulated operating conditions and waveform-noise levels. Full article

Background: Endometrial intraepithelial neoplasia/atypical endometrial hyperplasia (EIN/AEH) carries a substantial risk of concurrent endometrial carcinoma at hysterectomy. Sentinel lymph node (SLN) mapping requires cervical injection into an intact uterus, so the decision to map must be made before uterine pathology is known. A strategy that defers that decision to intraoperative frozen section therefore does not choose between mapping and no mapping; it forecloses mapping altogether. We evaluated the technical feasibility and diagnostic yield of SLN mapping performed without frozen section in patients with preoperative EIN/AEH and estimated how much of the nodal disease identified might not have been detected under a frozen-section-guided pathway. Methods: In this retrospective single-center study, 86 patients with a preoperative diagnosis of EIN/AEH underwent hysterectomy, bilateral salpingo-oophorectomy, and SLN mapping with methylene blue between November 2021 and May 2026. No patient underwent intraoperative frozen section, and all SLNs underwent ultrastaging. Patients were grouped by final histopathology, and carcinomas were staged according to FIGO 2023. A counterfactual analysis applied the Mayo intraoperative triage criteria to the final uterine pathology and considered two mechanisms separately: patients who would not have undergone nodal assessment at all, and patients who would have undergone lymphadenectomy but whose disease volume might not have been detected by conventional nodal pathology. Results: Final pathology showed persistent EIN/AEH in 37 patients (43.0%) and endometrial carcinoma in 49 (57.0%). Patients upgraded to carcinoma were older (60.3 ± 9.5 vs. 53.1 ± 10.4 years, p = 0.001), more often postmenopausal (87.8% vs. 54.1%, p = 0.001), and had greater endometrial thickness (18.6 ± 8.7 vs. 13.5 ± 5.4 mm, p = 0.004). At least one SLN was retrieved in 82 of 86 patients (95.3%) and bilaterally in 76 (88.4%); bilateral detection did not differ significantly between groups (94.6% vs. 83.7%, p = 0.177). SLNs lay in the obturator region in 62.2% of hemipelves and in the external iliac region in 26.3%, together accounting for 88.5%. Nodal involvement was identified in 11 patients (12.8% of the cohort; 22.4% of carcinomas): isolated tumor cells in two, micrometastasis in six, and macrometastasis in three. Among the patients who underwent additional non-sentinel nodal assessment, no metastatic non-SLN was identified in the presence of negative SLNs; no reference standard was applied to the remaining SLN-negative patients, so a false-negative rate cannot be estimated. No patient with EIN/AEH-only pathology had nodal involvement. Under simulated frozen-section triage, 2 of the 11 node-positive patients (18.2%) would not have undergone nodal assessment at all; a further 6 had low-volume disease that might not have been identified by conventional nodal pathology. Taken together, up to 8 of 11 (72.7%), and up to 6 of the 9 with micro- or macrometastasis (66.7%), might have remained undetected under the specified hypothetical pathway. Conclusions: SLN mapping performed before hysterectomy and without intraoperative frozen section was technically feasible with methylene blue alone and identified occult nodal disease, a substantial part of which might not have been detected under a frozen-section-guided pathway. These findings establish feasibility and diagnostic yield only: the study has no comparison group and supports no conclusion about survival, morbidity, or cost-effectiveness. Because 43.0% of patients had EIN/AEH-only pathology, mapping should form part of individualized preoperative counseling rather than be applied universally. Full article

Labeled clinical text is scarce in many non-English healthcare settings, limiting the development of robust clinical NLP systems. We tested whether supervision from Spanish mammography reports improved the classification of Russian-language reports from Kazakhstan. The study included 4279 Spanish and 495 Russian reports mapped to three BI-RADS-derived operational classes (routine, follow-up, and suspicious). Explicit BI-RADS identifiers were removed from the input, and Russian performance was assessed using grouped five-fold out-of-fold evaluation. We compared Russian-only XLM-R fine-tuning, Spanish zero-shot transfer, sequential Spanish-to-Russian XLM-R fine-tuning, and a matched word/character TF–IDF logistic-regression baseline. Under the fixed split, label budget, and four-epoch schedule tested here, sequential transfer exceeded Russian-only XLM-R in all three paired training seeds, increasing the mean macro-F1 from 0.2178 to 0.3239; zero-shot performance was less stable (mean 0.1898). However, the matched TF–IDF model achieved the highest macro-F1 (0.5214) and better performance on the rare suspicious class (F1 0.3306 versus 0.1139 for transferred XLM-R). Thus, Spanish initialization was compatible with subsequent low-resource Russian adaptation in this experiment, while the target-language lexical model remained stronger. These findings are limited to the two datasets, grouped split, XLM-R configuration, and small, imbalanced target-data regime evaluated here. Full article

Reliable magnetic-materials screening requires more than a model that performs well within one computational catalogue. We develop and audit a composition-anchored library residual (CALR) protocol for transferring density-functional-theory (DFT) magnetic-moment information across heterogeneous databases. CALR harmonizes moment percentiles within each library, fits a composition-only ridge anchor, and admits a bounded moment residual only when a nested, composition-disjoint bridge test supports improved rank correlation. AFLOW and JARVIS moments are evaluated against experimental Curie temperatures from NEMAD, with a frozen Materials Project snapshot as a third source. On 484 AFLOW-JARVIS bridge compositions, neither directional gate opens: cross-fitted changes in Spearman correlation are +0.0079 (95% interval −0.0027 to 0.0187) and +0.0060 (−0.0125 to 0.0238). The Materials Project-to-JARVIS bridge gives Δrho = 0.0101 (−0.0036 to 0.0250), also returning the composition anchor. Ungated transfer improves one direction but produces negative transfer in the reverse; CORAL and density-ratio weighting underperform the anchor. A fixed-hash semi-synthetic control shows that CALR can activate for a known transferable residual and close for zero, non-transferable, or reversed residuals, although finite-sample false openings remain. CALR is therefore an auditable diagnostic for cross-library magnetic screening and negative-transfer risk, not formal risk control or validated permanent-magnet discovery. We re-ran the Materials Project analysis with current cell atom counts (nsites), traced every aligned key to a selected DFT identifier and experimental DOI, froze a percentile map on common compounds before gating, held out chemical families from training, resampled element-set groups through the full fit/select pipeline, and compared CALR with same-budget target-domain models. The MP gate remains closed after the nsites correction. We state a single protected deployment estimand: Spearman ρ of the frozen ranking versus experimental Tc on composition-disjoint target-library keys. Structure-resolved and aggregation sensitivities leave the headline |M|–Tc Spearman near 0.43. Family-grouped cross-validation lowers the composition-ridge OOF ρ from 0.697 to 0.461. The 484-key bridge is underpowered for the observed residual (forward 80% power requires Δρ ≈ 0.015–0.020). Materials Project reuses 100% of the NEMAD labels already seen in the AFLOW/JARVIS workflow. CALR still equals the composition ridge on every real direction; we state quantitative conditions under which its extra cost would be justified, and the independent library experiment that would be required to claim a practical benefit. Full article

This study maps the development, intellectual roots, and conceptual transformation of early childhood science education between 1990 and July of 2026 through performance analysis and science mapping of 1147 English-language research articles indexed in the Scopus Social Sciences subject area. Analyses conducted in R with bibliometrix/Biblioshiny examined performance indicators, collaboration, direct citation paths, co-citation patterns, and author-keyword structure. Publication output increased sharply after 2019: 635 articles (55.4%) appeared between 2019 and July 2026, including 537 (46.8%) in the completed years 2019–2025 and 98 in the partial 2026 period. Research in Science Education and the International Journal of Science Education were the most productive sources, while Fleer ranked first in both publication count and local citations. Internationally co-authored articles represented 12.57% of the corpus according to bibliometrix’s Multiple Country Publications ratio. The historiograph retained a connected sequence of influential works. Under the baseline settings, the displayed co-citation network was partitioned into four Louvain groups concerned with cultural-historical theory, empirical science pedagogy, nature of science and standards, and cognitive development. Modularity was low (Q = 0.13), and the number of groups was parameter-sensitive, while author keywords indicate that inquiry, play, and teacher pedagogy remain prominent alongside the more recent visibility of STEM, computational thinking, and computer science education. Together, these patterns suggest continuity in established research traditions alongside an expanding thematic vocabulary. They also motivate a hypothesis about core–periphery organization, although no core–periphery model was fitted. An expanded query (n = 2739) reproduced the post-2019 rise in publication counts and was not used for the primary maps. The findings are limited to the retrieved corpus and do not estimate the prevalence of these themes across the wider STEM, robotics, coding, computational thinking, or artificial intelligence studies. Full article

Traditional high-precision star trackers rely on long-focal-length optical configurations, which suffer from bulky volume and heavy weight, which restricts their application to small satellite platforms. Meanwhile, lightweight optical architectures inevitably introduce residual optical aberrations that distort star spot energy distribution and degrade centroid extraction accuracy. Targeting Petzval-type star trackers, this paper proposes an optical-algorithm collaborative lightweight design scheme. First, a coupling mathematical model between centroid positioning error and four asymmetric optical aberrations is established to quantify the error contribution hierarchy of coma, astigmatism, distortion, and lateral chromatic aberration. Second, an aberration dimensionality-reduction optimization method is proposed to selectively constrain precision-sensitive asymmetric aberrations; the conventional six-element Petzval lens group is simplified to a four-element lightweight configuration, reducing lens count by 30% and total system length from 27 mm to 21 mm. Finally, a three-stage joint compensation framework consisting of aberration residual identification, iterative centroid offset correction, and regularized Richardson–Lucy image restoration is constructed for on-orbit low-computation platforms. Ground star-map tests and on-orbit measurements demonstrate that the star centroid error is reduced from 0.098 pixels to 0.014 pixels after compensation, corresponding to an 85.7% improvement in localization precision. The 16 μm in-spot energy concentration rises from 76.2% to 86.5%, with full-field energy uniformity improved by 19.2%. Attitude measurement accuracy better than 3″ ($3\sigma$) is achieved for the X- and Y-axes (roll/pitch). The system exhibits favorable robustness under stray-light and multi-scene observation conditions. This integrated optical-algorithm solution realizes arcsecond-level attitude measurement for roll and pitch axes under strict lightweight constraints. Full article

Urban functional zone (UFZ) identification supports refined territorial spatial governance and urban remote sensing. It faces the dual challenges of spectral confusion and functional mixing, which single-source remote sensing cannot resolve at high accuracy. Taking central Kunming as a study case, this paper integrates high-resolution remote-sensing imagery (HRI), points of interest (POIs), building footprints, and a digital elevation model (DEM) into a multi-dimensional feature system that combines spectral–textural features, POI functional semantics, building-morphology constraints, and topographic indicators. Mean shift object-based segmentation and a random forest are used for supervised UFZ classification, while an independent test set and ablation experiments quantify model performance and each feature group’s contribution. The optimal model reaches an overall accuracy (OA) of 82.22% and a Kappa of 0.7721, indicating reliable performance. Leave-one-out ablation shows that POI kernel density contributes most to identifying commercial and public zones, building morphology mainly improves industrial-zone accuracy, and terrain plays an auxiliary role in delineating ecological green-space boundaries. Landscape metrics and the standard deviational ellipse (SDE) are then applied to the classification results to examine functional spatial differentiation. Bounded by terrain and the Dianchi ecological barrier, central Kunming forms a composite pattern of one primary core, two secondary clusters, and interwoven ecological corridors, with clear differences among classes in extension direction, centroid location, and inter-district composition. The proposed multi-source fusion framework offers reliable methodological support for fine-scale UFZ mapping and refined territorial governance. Full article

Successfully engaging and retaining underrepresented individuals in science, technology, engineering, and mathematics (STEM) offers benefits not only economically but also from an equity perspective, as increasing participation reduces structural barriers and stereotypes and provides access to high-paying jobs. However, traditionally underrepresented groups, such as women, ethnic minorities (especially Black, Hispanic, and Latinx), or students with special educational needs (e.g., learning disabilities or mathematics difficulties), still constitute only a small percentage in STEM, especially in technology-intensive fields like physics, engineering, or computer science. There is significant potential to close gaps among groups hindered from pursuing STEM by structural barriers, stereotypes, or gender roles. STEM participation initiatives vary widely and include curriculum reforms, extracurricular programs, and structural changes to teaching and learning environments. This scoping review mapped diversity-oriented intervention approaches and reported outcomes. Following a systematic literature search, we identified and analyzed 104 relevant articles to map intervention types, target groups, educational contexts, and reported outcomes. The included studies showed a broad range of approaches across educational levels, with a clear focus on ages 15 and older. Most studies were from the U.S., indicating a lopsided representation of educational systems in this review. Reported interventions include mentoring programs, summer schools, hands-on activities, and curriculum-integrated lessons designed to increase STEM engagement and performance, foster belonging, and build self-efficacy among underrepresented populations. The review also highlights gaps in the literature. It thus provides a vital foundation and starting point for future research. Full article

Classical level constructions extract an ordinary topology from a fuzzy topology at one threshold, but a single level does not measure how the cardinal complexity of dense sets changes as the threshold varies. Motivated by this loss of inter-level information, we associate with every Lowen fuzzy topological space $(X,\mathcal{S})$ the level-density function ${\delta }_{(X,\mathcal{S})}\left(a\right)=\omega +d\left(X,{\iota }_a\left(\mathcal{S}\right)\right)$, $a\in [0,1)$, together with its range and supremum. This threshold-sensitive profile distinguishes fuzzy structures having the same zero-level topology. We prove that strict-level formation commutes exactly with finite fuzzy products and, under a natural openness hypothesis, with quotient formation; orbit quotients automatically satisfy this hypothesis. We also show that the profile need not be monotone, that arbitrary finite and countable sequences of infinite cardinals can be realized on prescribed half-open partitions of $[0,1)$, and that the supremum of the spectrum need not be attained. All realization results are proved in ZFC and require neither CH nor GCH. As an application of the product and quotient identities, finite fuzzy symmetric powers preserve the entire level-density function. Thus the invariant exhibits substantial inter-level flexibility while remaining rigid under several natural fuzzy-topological constructions. Full article

Retailers managing large stock-keeping unit (SKU) catalogues need a compact, auditable view of how individual products behave in order to plan replenishment, assortment and promotions. We present an interpretable analytics pipeline that derives SKU-level recency, frequency and monetary (RFM) features from one year of fashion-retail transactions (40,760 SKUs; 101,144 orders), segments the catalogue with prototype-based clustering under explicit internal validation, reads the segments alongside a co-purchase layer obtained by closed-itemset mining, and delivers the result to category managers through a deployed web application. Model selection is made explicit rather than assumed: K-Means and K-Medoids are compared at matched cluster counts on the Silhouette coefficient and the Davies–Bouldin Index (DBI). The two methods perform comparably at $k=2$, and K-Means is clearly superior at every larger cluster count; the selected configuration (K-Means, $k=4$) attains a Silhouette of 0.577 and a DBI of 0.624, against 0.522 and 0.762 for the best K-Medoids configuration. The resulting segments separate a small group of fast-moving items from a long tail of low-frequency products, and profiling them on the monetary axis shows that the separation tracks value contribution: 7.1 per cent of the clustered SKUs account for 28.8 per cent of monetary contribution, and the 19 fast-movers contribute roughly eleven times the per-SKU average. We set out how each segment maps to replenishment, assortment and promotion decisions, together with the validation each mapping would require before adoption. Two scope conditions should be read with the results: clustering uses the recency and frequency axes, with monetary value reported as a descriptive attribute of the segments rather than as a clustering input, and the co-purchase layer rests on very low support because baskets in this catalogue average 1.16 SKUs, so the itemsets are exploratory anchors rather than association rules. Full article

Few-shot learning (FSL) and zero-shot learning (ZSL) are usually studied as separate problems, yet both require prediction when class-specific evidence is absent or scarce. This review analyzes their shared difficulty from an optimization perspective. Instead of grouping studies only by architecture, it tracks four common coordinates: the information available to the learner, the variables estimated from that information, the objectives and constraints, and the numerical solvers. These coordinates support a unified comparison of attribute-based ZSL, episodic meta-learning, metric and prototype estimators, graph and optimal-transport inference, generative any-shot models, and adaptation of vision–language models. The synthesis exposes recurring trade-offs rather than a universally preferable family: flexible updates increase estimator variance; tractable task-time solvers inherit representation bias; query batches can improve inference while changing the protocol; and strong pretrained priors reduce target-data requirements while making the origin of task evidence harder to audit. Canonical objectives are distinguished from simplified review formulations and prospective research targets. The framework also clarifies the progression from explicit semantic mappings to local adaptation around pretrained image–text representations. Three priorities emerge: model selection without extra validation labels, safe use of uncertain pretrained knowledge, and stable parameter-efficient adaptation. Under this view, FSL and ZSL are connected structured-estimation problems rather than an inventory of unrelated algorithms. Full article

Greek olive groves are subject to multiple thermal, water, biotic, and extreme-weather pressures, yet national-scale maps of their combined historical exposure remain limited. The present study quantified climate risk for olive cultivation across Greece using twenty agroclimatic indicators grouped into four thematic categories. Using hourly ERA5-Land data (1995–2024) and quality-controlled ESWD reports (2014–2024), each indicator recorded how often predefined adverse thresholds were met at the grid-cell level during the reference period. We integrated the resulting layers using a weighted multi-criteria decision analysis, with lethal frost applied as a separate constraint, to produce a composite spatial distribution of climate risk and district-level summaries linked to CORINE Land Cover 2018, olive grove class (2.2.3). Composite risk was spatially heterogeneous: cold and frost recurrence predominated in northern and upland areas, whereas water-related indicators occurred most persistently in southern and island districts, including eastern Crete. Most of the mapped olive grove area fell into intermediate composite classes rather than at the extremes of the score range. Comparison with a recent nationwide olive suitability assessment showed agreement in major western and southern producing districts, but also contrasting patterns where high suitability coincided with elevated recurrence-based risk. The resulting products provide a national historical baseline for climate-risk recurrence in Greek olive groves, offer a spatial basis for regionally targeted adaptation planning, and demonstrate the applicability of an AI-assisted geospatial framework for reproducible national-scale climate-risk assessment of perennial crops. Full article

Background: Patient-centered care (PCC) is central to diabetes management; unfortunately, evidence concerning its relationship with patient-reported outcome measures (PROM) in primary healthcare facilities in Jeddah is limited. This study examined the association between validated PCC scores and patient-reported outcomes and explored how PCC domains could be interpreted through four ethical principles. Methods: A cross-sectional survey was conducted on 594 adults with diabetes recruited from 47 primary care facilities between July and August 2023. The primary exposure was the validated 36-item, eight-domain PCC total score, while the primary outcome was a study-specific core PROM composite. Satisfaction and patient-reported experience measure (PREM) scores were measured as secondary measures. Statistical analysis was completed through multivariable ordinary least-squares regression with HC3 heteroscedasticity-robust standard errors adjusted for sociodemographic and health characteristics, while the four author-defined ethical groupings were examined exploratorily. Results: Among 594 adults with diabetes who completed the study, the mean PCC was 76.91 (SD 17.01), core PROM was 63.51 (SD 16.85), satisfaction was 81.41 (SD 19.30), and PREM was 77.27 (SD 20.45). PCC correlated with core PROM (r = 0.437), satisfaction (r = 0.251), and PREM (r = 0.239). In the primary adjusted model (n = 591), PCC remained positively associated with core PROM (B = 0.433, 95% CI [0.359, 0.507], p < 0.001). Female sex and severe self-rated health were associated with lower PROM scores, whereas older age and type 2 diabetes were associated with higher scores. The model explained 27.0% of PROM variance. Conclusions: Higher PCC was independently associated with better PREM. The ethical mapping provides a potentially useful interpretive framework but requires independent psychometric validation. Full article