Search Results (514)

Rapid identification of fish disease lesions is essential for disease monitoring and early intervention in aquaculture, yet existing detection methods rely heavily on extensive lesion annotations and fixed category definitions. To address the challenges of limited annotated data and heterogeneous supervision, this study proposes PaliGemma2-FishGrounding, a generative vision-language grounding framework for few-shot fish disease lesion localization. The framework reformulates lesion detection as an open-vocabulary grounding task and unifies lesion localization, disease recognition, health-status classification, and symptom understanding within a single instruction-learning paradigm. By integrating heterogeneous supervision from multiple fish disease datasets, the proposed method enables lesion localization through structured vision-language generation rather than conventional closed-set detection. Experimental results on an Epizootic Ulcerative Syndrome (EUS) lesion dataset demonstrate that the proposed framework outperforms YOLOv8-based baselines, achieving an AP50 of 0.3659 and an AR@10 of 0.5378 while maintaining a zero invalid-box rate. Ablation studies further confirm the effectiveness of the instruction-learning strategy and grounding-based design. The results indicate that generative vision-language models can effectively leverage limited lesion annotations and auxiliary disease knowledge for fish disease analysis. This framework provides a practical solution for low-annotation disease monitoring and offers a promising direction for intelligent aquaculture applications under data-scarce conditions. Full article

The Joint Clinical Assessment (JCA) evaluates the relative effectiveness (RE) of interventions over comparators. While randomised control trials (RCTs) are considered the gold standard, single-arm trials (SATs) require an external control for accurate RE estimation. This study reviewed Health Technology Assessment (HTA) outcomes for medicinal products supported by SATs in France, Germany, Poland, and Spain, and simulated the JCA for these products based on evidence submitted in France. Among HTA evaluations published in France in 2019–2024, 16% were SAT-driven, and 5.6% of them included external controls. SAT-supported drugs had a high reimbursement approval rate (74%) and showed better HTA outcomes when controls were used. In Germany, 64% of SAT-based HTA outcomes indicated no added benefit and 30% a non-quantifiable benefit. In Poland and Spain, 63% and 72% HTA evaluations recommend reimbursement, respectively. Despite wide acceptance by Member States, experts determined that 94% of SAT-supported products would not qualify for JCA review due to insufficient evidence. Only 6% would qualify for JCA for a likely limited number of PICOs (Population–Intervention–Comparator–Outcome), but the certainty rating would be low. These findings suggest that SATs, as primary evidence, may not be suitable for JCA, potentially undermining HTA in EU Member States. Full article

Surface mining represents a significant intervention into the natural environment, negatively affecting air, water, soil and local ecosystems. In cement production, these impacts are closely connected to occupational health and safety risks, particularly in processes involving blasting operations. The aim of the article is to design, implement, and empirically verify an integrated model for assessing occupational and environmental risks in the cement production process, with an emphasis on the surface mining of raw materials stage, which will enable a comprehensive assessment of the interrelationships between risks, increase the accuracy of their evaluation, and support effective decision-making in OSH management and the environmental performance of the enterprise. The research was conducted as a case study using a combination of scientific quantitative methods focused on designing and verifying the integrated IMORM model in the cement industry. The methodological approach included an analysis of the requirements of ISO standards, methodological recommendations of EU-OSHA, comparison of approaches, expert interviews, observation in practice, application of a checklist, point-based method, risk catalogue, synthesis of knowledge, modelling, and verification. The application of an integrated approach to risk management demonstrated higher effectiveness compared to traditional approaches, whereby all unacceptable OSH risks were reduced to an acceptable level after the implementation of measures. In the environmental area, the risk score decreased significantly by 52.9%, and in the OSH area, the risk index decreased by 31%. At the same time, the model’s ability to effectively prioritize measures and identify cross-cutting solutions with a high impact was confirmed. The contribution of the article lies primarily in expanding knowledge in the field of integrated risk management and in proposing a practically applicable model that reflects the requirements of management systems according to the standards ISO 14001, ISO 45001 and ISO 31000. The IMORM model represents a tool applicable to enterprises with a high level of occupational and environmental risks, particularly in the mining and processing industries. The model also supports more comprehensive decision-making in the field of OSH and environmental management and contributes to improving the safety and environmental performance of the enterprise. Full article

LIFE REVIVE aims to restore ecological status and ecosystem services in the Lima and Vouga river basins (NW Iberian Peninsula), where hydromorphological alteration and hydropower-driven flow regulation are major causes of water bodies failing to reach Good Ecological Status under the EU WFD. The project targets key pressures such as longitudinal fragmentation by weirs and dams, artificial flow regimes, degradation of spawning substrates, and the spread of invasive aquatic plants, which strongly affect fish communities, including sea lamprey, salmonids, and other diadromous species. Technically, the project combines barrier removal or eco-adaptation, nature-like fish passes, and spawning-habitat renaturalisation with optimized environmental flow regimes (EFR) downstream of important hydropower systems, explicitly accounting for present and future hydroclimatic scenarios. Multi-scale ecohydrological modelling (species distribution models, habitat suitability models, GLM/GAM approaches) will quantify fish–flow–habitat relationships and support the definition of operational EFR guidelines that balance ecological requirements with hydropower and agricultural constraints through joint work with the main Portuguese hydropower operator, EDP. Impact evaluation is structured around a rigorous BACI monitoring design in intervention and control tributaries, using standard WFD biological indices for fish and aquatic/riparian vegetation, hydromorphological indices (HQA, HMS, RHS), and project-specific Key Performance Indicators for water quality, biodiversity, and habitat. Expected outcomes include the restoration of at least 51 km of rivers towards free-flowing conditions, reduced hydromorphological pressure in more than 20 km of heavily modified river stretches, and measurable increases in the distribution and abundance of fish species and native vegetation. A strong communication and capacity-building programme underpins public engagement, while a decision matrix for barrier prioritization, technical workshops, and pilot replications in additional basins (e.g., Alva, Mouro, Deva, and Tea in Galicia) are designed to maximize transferability, policy uptake, and long-term sustainability of the solutions beyond the project lifetime. Full article

Pigment implantation (semi-permanent make-up, microblading and cosmetic tattooing) introduces complex pigment mixtures into the dermis, resulting in direct exposure of keratinocytes, fibroblasts and resident immune cells to metals, organic dyes and nanoparticles. Within Somatology and Somatic therapy practice, an allied health discipline concerned with evidence-based care of the skin and body, Somatic Therapists operate at the interface of dermal intervention, molecular exposure and occupational health, underscoring the relevance of mechanistic toxicology for risk-informed professional practice. This PRISMA-guided systematic review synthesises molecular toxicology and omics-based evidence, emphasising oxidative stress generation, inflammatory signalling via NF-κB/MAPK pathways, apoptosis and genotoxicity, T-cell-mediated type IV hypersensitivity reactions associated with modern red azo pigments, and dermal-to-lymphatic transport of particulate matter. Transcriptomic and metabolomic studies consistently demonstrate pigment-specific inflammatory responses and wound-healing gene signatures, supporting mechanism-driven biocompatibility profiling. Regulatory frameworks, including EU REACH Annex XVII Entry 75 and recent FDA guidance on microbial contamination, have strengthened compliance requirements; however, surveillance continues to identify mislabelling, restricted pigments and microbial contamination in some inks. For Somatology and Somatic therapy practice, these findings highlight the importance of evidence-based pigment selection, traceable sourcing, aseptic technique, ventilation, personal protective equipment and informed consent addressing pigment migration and delayed adverse reactions. The integration of molecular outcomes with omics technologies and regulatory oversight provides a next-generation risk assessment framework to advance safe cosmetic practice and public health. Full article

Pesticide-residue risk perceptions among agricultural professionals are shaped by factors that extend beyond knowledge gaps. This study examines how trust in regulatory systems and information sources jointly shape residue-related attitudes among Greek agronomists. We used principal components analysis (PCA) to identify coherent domains and then latent profile analysis (LPA) to derive person-centered profiles based on standardized component scores. Two dominant profiles emerged, differing in regulatory confidence, reliance on institutional/scientific information channels, and comparative risk framing. Residue-Concerned Skeptics expressed lower confidence in enforcement capacity (implementation and staffing) and in the system’s alignment with other EU Member States, together with concerns about chronic pesticide exposure. The System-Confident profile reported higher regulatory confidence and greater reliance on official and scientific channels, as well as stronger endorsement of IPM effectiveness and comparative risk rankings. External validation supported profile differences in perceived training adequacy, IPM beliefs, and organic avoidance behavior. Professional involvement in plant protection and older age were associated with membership in the System-Confident profile. These findings suggest that interventions should emphasize clear communication, capacity building, and address concerns about chronic exposure, beyond information provision alone. Full article

Background/Objectives: In Croatia, national data on adolescents’ dietary habits are limited, resulting in a lack of evidence-based food-based dietary guidelines and public health interventions. This study aims to conduct an in-depth evaluation of dietary habits in a national sample of Croatian adolescents stratified by region, sex and age, from the National food consumption survey on adolescents and adults (NIPNOD 2018–2023). Methods: This cross-sectional study included 258 adolescents (50.4% boys; aged 10 to < 18) from the NIPNOD 2018–2023 survey (OC/EFSA/DATA/2017/01), conducted according to the EU Menu methodology. For analysis, the sample was divided into two age groups (10–13 and 14–17 years). To assess dietary intake, two 24 h recalls were analyzed using NutriCro^® v. 3.0 software. Dietary intake was compared with European Food Safety Authority dietary reference values (DRV). The contribution of 14 food groups to daily energy intake was analyzed. Diet quality was assessed using the Diet Quality Index for Adolescents (DQI-A). Results: The mean daily energy intake was 1820 ± 529 kcal, consisting of 45.5 ± 7.0% carbohydrates, 37.8 ± 6.3% fats, and 15.1 ± 3.1% protein. The observed two-day mean intake suggested that 51.6% of adolescents had carbohydrate intake within the EFSA DRV range, while 5.4% and 32.2% had protein and fat intake within the EFSA DRVs, respectively. The main contributors to daily energy intake were grains and grain products (31.5%), meat, poultry, fish, and eggs (18.1%), and cakes, confectionery, sweets, and sugar (14.9%). Frequent breakfast skipping and snack consumption were common, particularly among older adolescents. Adolescents had moderate overall diet quality (57.4 ± 11.6% DQI-A), with no differences between age groups. Conclusions: Analysis of the dietary habits of adolescents in Croatia indicates that most have inadequate macronutrient intake, irregular meal frequency, and moderate overall diet quality. These results highlight the need to develop public health strategies and interventions to improve dietary habits among adolescents in Croatia. Full article

The transition to a circular economy (CE) represents a complex socio-technical evolution, requiring synchronized policy frameworks and strategic capital reallocation. Adopting a systems-thinking lens, this study combines bibliometric network mapping with exploratory econometric modelling, to examine the associations between five core policy instruments and tangible circular investments (INV_CE) across the EU-27. Bibliometric analysis identifies the “firm” and “supply chain” as central functional hubs within the CE knowledge system, acting as primary mediators for capital flows. Econometric results indicate that Tradable Permits (TPOs) and an integrated Policy Integration Index (PII), comprising subsidies and energy-based taxes, show the strongest statistical association with circular investment patterns (p ≤ 0.001). However, patterns of structural disparity emerge between OECD and non-OECD Member States (p = 0.014), where the latter often exhibit a more rigid, tax-centric approach. Spearman correlations point toward institutional maturity, specifically government effectiveness (r_s = 0.48) and eco-innovation capacity, as a potential systemic gateway for investment absorption. Furthermore, a structural decoupling appears between voluntary approaches (VAs) and governance capacity in emerging systems, suggesting that such instruments may be less effective without “institutional readiness.” The findings suggest that circular transition is path-dependent and congruent with the co-evolution of policy and institutional regimes. To bridge the investment gap, the study highlights the need for systemic interventions that move beyond “one-size-fits-all” regulations toward targeted strategies that strengthen the institutional and data reporting infrastructures of circular systems. Full article

Endoscopic ultrasound-guided gallbladder drainage (EUS-GBD) is an emerging intervention that provides a minimally invasive approach to drainage of the gallbladder, showing promising results in treating acute cholecystitis (AC) and malignant biliary obstruction (MBO). This review summarizes the current applications of EUS-GBD and compares its clinical effectiveness with traditional methods such as percutaneous transhepatic gallbladder drainage (PT-GBD) and endoscopic transpapillary gallbladder drainage (ET-GBD). Available evidence suggests that EUS-GBD may offer potential advantages in terms of success rates and complication profiles, particularly in patients who are not candidates for surgery or those at high surgical risk. The method is effective in reducing inflammation, alleviating symptoms from obstruction, and improving patient quality of life. This article also discusses the technical evolution of EUS-GBD, its indications, complications, and its comparative advantages over other drainage techniques. These observations suggest that EUS-GBD may represent a valuable addition to the therapeutic armamentarium for selected high-risk patients. Full article

Background/Objectives: Treatment-resistant depression (TRD) remains one of the most urgent unmet needs in psychiatry, while its therapeutic pipeline is evolving rapidly. To characterize current development trajectories, we conducted a registry-anchored mapping of interventional trials in adults with major depressive disorder and treatment resistance (MDD-TRD), with the aim of defining the distribution of intervention types, endpoint choices, and key design features across the active trial landscape. Methods: We systematically searched ClinicalTrials.gov, the EU Clinical Trials Information System, and ISRCTN for interventional MDD-TRD trials registered up to 18 September 2025. After data cleaning and cross-registry deduplication, 237 unique trials were retained. Interventions were categorized through a taxonomy distinguishing device-based neuromodulation, pharmacological strategies, biologic/novel agents, multimodal non-digital combinations, digital–hybrid programs, psychotherapy, and lifestyle interventions, with classification anchored on structured registry intervention tags and whole-word matching across title and intervention text. Primary endpoints were flagged as standard when they explicitly referenced the Montgomery–Åsberg Depression Rating Scale or Hamilton Depression Rating Scale. We also examined developmental phase, sample size, and recurrent methodological features. Results: Device-based neuromodulation accounted for the largest share of the active pipeline (114/237, 48.1%), followed by pharmacological strategies (86/237, 36.3%), biologic/novel agents (16/237, 6.8%), and multimodal non-digital combinations (11/237, 4.6%). Digital–hybrid programs represented a small but distinctive stratum (5/237, 2.1%), with the remaining records comprising lifestyle interventions (3/237, 1.3%) and psychotherapy (2/237, 0.8%). Standard clinician-rated primary endpoints were used in 63.3% of studies. Trial development was concentrated in mid-phase designs, whereas sample sizes were generally modest (median 49; interquartile range, 19–87). Across modalities, increasing attention was directed to durability of response, functioning, and patient-reported outcomes, with adaptive and enrichment-based designs appearing with greater frequency. Conclusions: The contemporary TRD trial ecosystem is structured around two co-active developmental tracks—device-based neuromodulation and pharmacology with novel mechanisms—accompanied by a smaller but measurably expanding biologic/novel stratum and a still-marginal digital–hybrid presence. This registry-based mapping provides a near-real-time overview of the field and may support future harmonization of trial endpoints and design standards. Full article

The extension of the European Union Emissions Trading System to buildings and road transport (ETS2) raises important questions about the distribution of carbon pricing burdens across Member States. While existing research has primarily focused on income differences or household typologies, the structural heterogeneity of vulnerability across EU countries remains insufficiently explored. This study develops a dual-channel framework of household vulnerability to ETS2, distinguishing between structural carbon exposure and socio-economic sensitivity. Using a balanced panel of 27 EU Member States over 2010–2024, we construct composite indices based on Eurostat data and combine cluster analysis, sigma-convergence tests, and two-way fixed-effects models with Driscoll–Kraay standard errors. The results suggest that the two vulnerability channels are empirically distinct and geographically differentiated across Member States, with no country group simultaneously characterized by high exposure and high sensitivity. Energy productivity and renewable energy expansion are associated with lower structural exposure but higher socio-economic sensitivity, consistent with a transitional burden mechanism. Over time, composite vulnerability exhibits statistically significant divergence, despite partial and uneven convergence across the underlying vulnerability dimensions. These findings highlight the need for differentiated compensation mechanisms and structural policy interventions that address both structural exposure and socio-economic sensitivity, supporting a socially equitable and sustainable energy transition under ETS2. Full article

Soil compaction is a widespread yet insufficiently monitored form of agricultural land degradation, affecting approximately 25% of global soils and nearly 33% of European subsoils, with consequential reductions in soil physical functionality, crop performance, and long-term sustainability; however, approaches for national-scale compaction risk mapping remain limited. A geospatial decision support framework was developed to quantify and map susceptibility to compaction risk across Italy by integrating Earth observation products with multi-criteria decision analysis within a GIS-based Analytic Hierarchy Process. The model combined four indicators: (i) Soil Moisture Index derived from Sentinel 1 C band SAR time series (2018 to 2024), (ii) the Sentinel 2 Normalized Difference Tillage Index, (iii) clay fraction from SoilGrids 2.0, and (iv) an Intensity of Agricultural Practice Index derived from national census statistics. The approach was applied to 74,156 km² of bare soil surfaces across all 20 regions to generate 100 m seasonal and multi-year mean risk maps. Extreme risk (high plus very high) exhibited a bimodal seasonal behavior, occupying 53.6% in winter and 55.5% in autumn, while declining to 24.8% in spring and 26.5% in summer; Southern Italy showed the largest seasonal amplitude (40.7%), and Friuli Venezia Giulia persisted as a hotspot exceeding 50% in all seasons. Comparison with the independent bulk density observations yielded 31.24% accuracy, largely constrained by the temporal mismatch between dynamic processes and static reference data, which represents a constraint of this research. The framework provides an initial screening tool for mapping susceptibility to soil compaction aligned with the EU Soil Strategy 2023 to 2030, supporting targeted interventions by prioritizing spring (March to May) as a low-risk remediation window; however, local conditions must be checked because cultivated crop types are highly diverse, and cropping cycles vary significantly from one species to another. Full article

Patient safety remains a global priority, with surgical errors, including in-hospital infections, procedural mishaps, and delays in diagnosis or treatment, causing over 7 million adverse events and 1 million deaths annually. This study evaluates machine learning (ML) to predict the risk of medical errors in the general surgery department of a Greek tertiary university hospital. Medical error risk was operationalized using several proxy indicators derived from prolonged hospitalization and elevated treatment costs, validated against diagnosis-related complication codes. Using a 10-year dataset of 19,965 anonymized patient records (13.5% error cases, n = 2700), we applied ensemble ML algorithms via WEKA, achieving 94.3% accuracy (Random Forest) in detecting errors such as healthcare-associated infections (HAIs), medication errors, and equipment failures. Given the clinical importance of minimizing missed adverse events, model evaluation prioritized both sensitivity and AUC-ROC in addition to overall accuracy. Key predictors were hospitalization duration (ranked #1 via information gain) and initial diagnosis, enabling early risk flagging (e.g., post-op day 5). Further exploratory analyses excluding hospitalization duration from the predictor set demonstrated a moderate reduction in predictive performance while preserving clinically meaningful discriminative capability, suggesting that model performance was not exclusively dependent on hospitalization duration. Compared to US benchmarks like ACS NSQIP (90% accuracy), our model outperformed by 4.3%, filling a gap in EU/Greek studies amid data silos and resource constraints. Integration with tools like the WHO Surgical Safety Checklist could enable proactive interventions, such as enhanced monitoring for prolonged stays. However, the proposed framework should be interpreted as identifying high adverse-event risk patterns rather than directly detecting clinically adjudicated preventable medical errors. Limitations include retrospective biases and workflow integration challenges; ethical issues like data privacy and algorithmic fairness were addressed via anonymization and ethics approval. Future work will focus on multi-center validation, calibration analysis, longitudinal modeling, and integration of explainable artificial intelligence (XAI) techniques to improve transparency and clinical trust. By blending ML with clinician expertise, this approach shifts healthcare from reactive to proactive error mitigation, improving outcomes and reducing costs. Full article

While Low Emission Zone (LEZ) enforcement cameras provide a constant stream of traffic data, such resources remain significantly underexploited for urban mobility planning, as their current application is restricted to enforcing vehicle access regulations and issuing fines. This paper presents MobiCugat, a framework demonstrating that Automatic Number Plate Recognition (ANPR) camera data from a municipal LEZ network can serve as the calibration backbone for high-fidelity, city-scale traffic simulations for a policy-testing Digital Twin. The case study is Sant Cugat del Vallès (Barcelona), where the local council sought to evaluate new scenarios for the area using an evidence-based, data-driven approach. Vehicle detection records from 102 LEZ ANPR cameras were processed into 15-min traffic intensity time series through a General Data Protection Regulation (GDPR)-compliant pipeline. The Realistic Urban Traffic Generator (RUTGe), a Deep Reinforcement Learning-based tool, was used to generate SUMO-compatible traffic demand whose simulated detector counts reproduce the observed camera-based intensities. The resulting simulations reproduced the observed detector-level traffic intensities with ${\mathrm{MARE}}_{\%}$ values between $2.29\%$ and $2.90\%$ across representative morning peak, midday off-peak, and evening peak traffic conditions. Additionally, camera analysis of over $470,000$ vehicle records revealed that resident traffic ($37.4\%$) dominates over through-traffic ($3.8\%$), significantly refining prior survey-based estimates. Our high-fidelity simulation tool based on SUMO, features realistic traffic patterns calibrated through AI-driven techniques, enabling the evaluation of diverse ’what-if’ scenarios—such as road closures, pedestrianization, changes in traffic direction, or relocation of bus stops. By quantifying the impact of these interventions, our tool facilitates informed decision-making prior to physical implementation. The proposed pipeline is cost-effective, privacy-preserving, and directly replicable for any municipality operating an LEZ camera network, offering a scalable template for evidence-based urban mobility planning, aligned with the European Strategy for Data and the EU Green Deal goals for sustainable mobility. Full article

Food markets represent a public good essential for urban supply and as intergenerational spaces supporting the small-scale economy, yet they face growing challenges in adapting to sustainability regulations and circular economy requirements. This study examines the current state of sustainability in Madrid’s municipal markets through interviews and questionnaires administered to market managers, analyzing building characteristics, renewable energy systems, passive savings strategies, and energy costs across different market typologies. Results reveal that in December 2025, only 9% of markets had solar thermal installations, while merely 11% were planning photovoltaic solar panel projects—figures insufficient to meet current EU energy efficiency mandates. The findings demonstrate a significant gap between existing infrastructure and the requirements of the Directive (EU) 2023/1791, which supersedes previous directives. These results indicate an urgent need for accelerated implementation of renewable energy systems in market buildings to achieve sustainability targets. The study contributes baseline data for developing intervention strategies that can reduce energy consumption and align Madrid’s market network with European decarbonization goals for 2030 and 2050. Full article