Bàrbara Micó-Vicent

Selected low-impact extracts from red cabbage, spent coffee grounds, Pisolithus sp., orange peel, Iris germanica petals, dragon fruit peel and pine bark were immobilized on halloysite (HA), hydrotalcite (HT) and laponite (LAP) and evaluated as hybrid pigments for cotton printing. A four-run 2⁽³⁻¹⁾ fractional factorial screening design examined acidification, surfactant and silane additions. Diffuse reflectance, CIELAB coordinates and K/Smax within 400–700 nm characterized powders and prints; HA and LAP formulations with the most useful colors were additionally evaluated for light, washing and rubbing fastness. The clay host strongly influenced the optical response. LAP generally produced the darkest powders and highest color strength, whereas HT gave paler, more yellow and less saturated prints and was not advanced to the fastness stage. HA offered the best balance between color development and durability. HA-based coffee, red cabbage and Pisolithus prints reached light-fastness ratings of 5–7, washing ratings around 4–5 and dry/wet rubbing ratings up to 5/4–5. The combined HCl/surfactant/silane formulation (run 4) consistently provided the best fastness among tested HA and LAP systems. The results extend a companion extraction-screening study and demonstrate a mostly aqueous route from plant and biowaste residues to printable hybrid pigments with potential for sustainable and multifunctional textile coloration.

Textile wet processing generates dye‐containing effluents that require effective recovery and valorisation strategies. Halloysite nanoclay was used to capture Reactive Red 195 from a model aqueous solution, and the resulting dye‐loaded solid (REDHA7) was subsequently applied once to cotton by exhaustion dyeing and pigment‐type printing. Reactive Red 195 was quantified in the filtrate by UV–Vis spectrophotometry at 542 nm using A542 = 34.357C − 0.0148 (C in g/L; R ² = 0.9991). For C ₀ = 200 mg/L, V = 0.500 L and m = 12.0 g, C _e was 1.56 mg/L, corresponding to 99.22% removal and an adsorption capacity of 8.27 mg/g. Fourier transform infrared (FTIR), X‐ray diffraction (XRD) and X‐ray photoelectron spectroscopy (XPS) supported the formation of an organic–inorganic dye‐halloysite hybrid through non‐covalent association involving electrostatic interactions, hydrogen bonding and surface deposition. REDHA7 was evaluated in printing pastes at 40–100 g/kg and compared with a Reactive Red 195‐only printed control at 80 g/kg, while exhaustion dyeing was benchmarked against conventional reactive dyeing. Increasing REDHA7 concentration in printing decreased L * and increased chroma and K / S . Scanning electron microscopy (SEM) showed halloysite‐rich surface particles on REDHA7‐printed cotton, whereas pristine, conventionally dyed and REDHA7‐dyed fibres had comparable morphologies. REDHA7‐dyed samples showed washing fastness of 4–4/5 and rubbing fastness generally around grade 4. Printed samples showed moderate washing resistance, while the highest hybrid loading achieved grade 4 for dry and wet rubbing. Light fastness reached blue‐wool grades 6–7 for printed samples. These results demonstrate the feasibility of coupling dye capture with direct textile application, although industrial wastewater validation and life‐cycle assessment remain necessary before industrial implementation.

Mechanically recycled cotton is heterogeneous, and nep counts obtained from different analytical platforms may not be numerically interchangeable. This study provides a preliminary cross-platform comparison of five industrial batches selected in the original industrial work to span the available production range of total nep count (TotNep). The batches differed in product category, color, supplier/feedstock designation, and production line; Batch was therefore treated as a composite material identity rather than an isolated structural-severity factor. USTER^® Neptester 720 measurements comprised three bales per batch and two technical determinations per bale; USTER^® LVI 920 used the same three bales and three determinations per bale; USTER^® AFIS Pro 2 used one of those bales per batch and ten determinations. Descriptive variability was reported as mean, standard deviation, and coefficient of variation. The primary inferential analysis compared Neptester 720 and LVI 920 on the 15 matched bales. Although the overall mean paired difference was +45.5 neps/g (95% CI: 14.0–76.9; p = 0.0078), batch-specific mean differences ranged from −13.6 to +101.4 neps/g and differed significantly among batches (p = 0.025), showing that +45.5 neps/g is not a transferable correction factor. A secondary exploratory analysis was restricted to the five bales measured by all platforms (one bale per batch). These deliberately range-spanning bales retained the Neptester-defined order (Spearman ρ = 1.00), but the coefficient is descriptive and does not constitute independent validation of cross-platform ranking. Exploratory Bland−Altman mean differences were +32.0, +99.3, and +67.2 neps/g for LVI 920-AFIS Pro 2, Neptester 720-AFIS Pro 2, and Neptester 720-LVI 920, respectively, with wide limits of agreement. Because no reference method was available and each platform was confounded with laboratory, operator, measurement date, and procedural conditions, these values describe cross-platform disagreement rather than instrument-specific measurement bias. The results support ordinal recognition of the selected batches but do not establish validated severity classes, numerical interchangeability, or formal interlaboratory reproducibility. Larger balanced studies using matched bales, documented conditioning, harmonized procedures, and fuller fiber characterization are required.

Education on natural hazards is a non-structural component of Disaster Risk Reduction (DRR), but the evidence base spans curriculum studies, risk-perception research, educational interventions, geospatial approaches and analyses of education-system continuity. This systematic narrative review synthesizes 27 outcome-bearing studies published between 2013 and the partial year 2026. PRISMA 2020 was used as a reporting framework, while PRISMA-S informed a retrospective audit of the search documentation. A structured design-sensitive appraisal recorded evidence family, comparison or temporal structure, outcome directness, permitted inference and principal limitation. The studies were coded into six mutually exclusive primary axes: reviews and frameworks; curriculum and policy; knowledge and risk perception; educational interventions and active methodologies; GIS and geospatial technologies; and educational continuity and system resilience. The included literature suggests that locally situated problems, maps, simulations and inquiry can support knowledge, risk appraisal and preparedness intentions, although demonstrated effects on sustained performance or actual preparedness behavior remain limited. Cross-cutting gaps include weak longitudinal assessment, sparse attention to teacher professional development, limited treatment of indigenous or local knowledge, and no core study centered on learners with disabilities or special educational needs. The review defines critical territorial risk literacy as the capacity to interpret hazard, exposure, vulnerability, capacity and uncertainty through spatial evidence; evaluate their unequal territorial distribution; and translate that understanding into inclusive, proportionate preparedness and collective action.

Replacing synthetic colorants with natural alternatives requires source-specific extraction strategies because pigment classes differ in polarity, pH response and thermal stability. This first-pass screening focused on six plant and agro-food matrices: red cabbage, Iris germanica petals, dragon fruit, orange peel, spent coffee grounds and pine bark. Each matrix was subjected to twelve extraction treatments combining water, ethanol, acetone 30%, acid/base modifiers, boiling water, freezing and ultrasound assistance. Extracts were evaluated by visible transmittance spectroscopy from 360 to 740 nm, operationally transformed to apparent optical attenuation according to Aapp (λ) = −log10 [%T (λ)/100] only where measured %T exceeded 0.01; this signal may include both absorption and light scattering, and converted to CIELAB coordinates under D65/10° conditions. The combined spectral and colorimetric approach separated the extracts into red-purple and yellow-brown groups. Red cabbage and Iris showed anthocyanin-like behaviour, dragon fruit showed a betalain-compatible magenta response, orange peel showed carotenoid-compatible short-wavelength attenuation, and coffee grounds and pine bark generated broad brown-yellow profiles. Pigment-family assignments remain putative because chromatographic identification was not performed. This study is explicitly intended as a proof-of-concept descriptive mapping step rather than as a statistically validated extraction optimisation. Because every matrix–treatment combination was prepared once, all comparisons in this article describe the observed screening preparations only; they do not estimate reproducible treatment effects, confidence intervals or statistical significance. The previous equal-weight low-L*/high-C*ab intensity score has been removed from the revised analysis. No extraction yield, recovery percentage, mass balance, purity, pigment concentration or application performance was measured; accordingly, this study describes the optical appearance of the obtained extracts and does not quantify colorant recovery. Visible transmittance, apparent optical attenuation and CIELAB coordinates support only literature-informed class-level hypotheses and cannot identify a pigment family or individual compound.

We study prediction-to-decision certification for inverse design with vector-valued response surfaces. An unknown response map is estimated from data, a target response is prescribed, and a decision is obtained by minimizing a target-loss function. The main question is how statistical prediction error and approximate global optimization error propagate to the true decision quality. We prove an end-to-end certificate showing that a high-probability uniform response bound and a certified global-search tolerance imply a high-probability bound on the true excess risk of the selected decision. Under a growth condition, the same event also yields an explicit distance-to-argmin bound. We provide finite-sample ordinary least squares response certificates, conditional ridge certificates with explicit bias decomposition, certified Lipschitz branch-and-bound, and polynomial sum-of-squares formulations. The formal certificate is demonstrated on a controlled synthetic benchmark. A clay-coloration example illustrates the workflow, while the pilot measurements are treated only as local forward-color checks.

This research develops a theoretical framework for understanding water-risk education as an essential civic competence in the context of climate change, hydrological extremes and socio-environmental vulnerability. Through a narrative conceptual synthesis of the recent literature on water governance, climate and disaster-risk education, sustainability competences and social representations of risk, the study examines how schools and universities can move from a general awareness of water problems to situated, anticipatory and action-oriented learning. The analysis identifies three mutually reinforcing dimensions of water-risk competence: cognitive understanding of water as a complex socio-environmental system; procedural capacity to analyze exposure, vulnerability, preparedness and adaptation; and attitudinal and ethical orientation toward responsibility, care, equity and collective decision-making. The research proposes a curricular model that connects hydrological-cycle education, flood and drought risk, territorial literacy, governance and the Sustainable Development Goals, especially SDGs 6, 11 and 13. The model is intended as a theoretical basis for future empirical studies, teacher-training designs and didactic proposals. It argues that water-risk education should not be restricted to emergency information or isolated scientific content, but should become a cross-curricular competence for forming citizens capable of interpreting uncertain climate scenarios and participating in resilient water governance.

Climate change education has expanded in curricular, institutional and media arenas, yet it still faces a central challenge: turning scientific knowledge into educational practices that transform perceptions, decisions and participation. This article argues that the challenge cannot be addressed by merely adding content about the climate system, because the climate crisis is experienced in specific territories, affects communities unequally and activates emotions that can either enable or inhibit action. Through a critical integrative review and research-reflection approach, the article connects three bodies of scholarship that are commonly developed in parallel: territorial and place-based learning, climate justice, and emotional literacy. Its conceptual novelty lies not in claiming that these components are individually new, but in specifying territorial memory as the mediating mechanism through which scientific evidence, unequal vulnerability, affective experience and collective action are combined in teacher education. On this basis, it presents the TEJA Model—territorialization, experience, justice and action—as a heuristic framework for designing, analyzing and evaluating teacher-education sequences. Its practical contribution is a five-phase process and an operational matrix that translate nearby risks such as floods, droughts and wildfires into inquiry, deliberation, emotional care and feasible collective action. The model is presented as a testable conceptual proposal rather than a validated intervention. The article concludes that relevant climate education must be scientific, human, territorial and political: it should recognize vulnerability, begin from lived places and address unequal responsibilities and collective capacities for action.

The floods triggered by the 29 October 2024 cut-off low in Valencia (Spain) expose a persistent challenge in disaster risk reduction: extensive meteorological and territorial data do not automatically become timely, trusted or actionable public guidance. This conceptual synthesis uses the Valencia event as a diagnostic case and reconstructs selected evidence on rainfall, hydrological escalation and alert timing to develop a data-driven framework spanning observation, modelling, impact assessment, communication, decision-making and post-event learning. Here, “data-driven” denotes an end-to-end governance and translation process, not the development of a new forecasting model. The framework integrates four dimensions: data governance, user-centred visualization, uncertainty communication and school-based education. It also introduces territorial translation as the link between impact forecasts and place-specific infrastructures, routines, vulnerabilities and responsibilities. Its novelty lies in connecting the Early Warnings for All pillars and impact-based, people-centred warning approaches with an explicit educational and territorial learning loop. Its practical contribution is a responsibility matrix, a minimum governance package and an implementation roadmap with indicators for latency, reach, comprehension and protective action. The framework is intended for adaptation, rather than statistical generalization, across Mediterranean and other fast-onset flood contexts. Improved forecasts remain necessary but insufficient: loss reduction requires interoperable records, accessible impact-based messages and inclusive educational programmes that convert scientific information into situated collective competence.

This study analyses the Master Plan for Analysis, Anticipation and Reaction to Natural Disasters of the Valencian Community (Spain) from the perspective of geographical risk literacy. The research adopts a qualitative methodology based on documentary analysis and conceptual assessment of public policy. The corpus includes Valencian institutional documents, Spanish civil protection and education regulations, international disaster risk reduction frameworks and the scientific literature on geography education, risk perception, social vulnerability and school preparedness. The findings show that the plan can strengthen institutional coordination, public communication and preventive culture through its preventive orientation, phased structure, official sources, attention to vulnerable groups, updated cartography and promotion of drills. However, its social effectiveness will depend on transforming protocols and guides into verifiable citizen capacities: identifying hazards, recognizing local exposure, interpreting warnings and maps, selecting safe routes, preparing households and rehearsing decisions in realistic contexts. The article proposes complementing the plan with a geographical literacy programme for territorial resilience based on local risk sheets, school atlases, evaluated drills, community mediation, accessible viewers and public monitoring indicators. The discussion places the Valencian case within international debates on disaster risk reduction, anticipatory governance, people-centred early warning systems and school safety. Because no empirical implementation data are yet available, the contribution is framed as an analytical and design-oriented framework requiring subsequent validation through pilots, surveys, interviews and evaluated drills.