Search Results (504)

The FLEX-S3 mission by ESA will deliver key Level 2 products such as sun-induced chlorophyll fluorescence (SIF) and vegetation-reflected radiance. To validate these, the SpaFLEX project, funded by the Spanish Ministry of Science and Innovation, is developing a robust calibration and validation strategy in Spain. This includes test site setup, instrument characterization, and sampling protocols. A field campaign was conducted in two Holm Oak forests in Teruel, analyzing Sentinel-2 spatial heterogeneity and collecting ground, UAV, and airborne data. The results support scaling procedures to match the 300 m pixel resolution of FLEX-S3, ensuring product accuracy and compliance with ESA standards. Full article

This paper presents the implementation of a language model–based strategy for the automatic codification of crime narratives for the production of official statistics. To address the high workload and inconsistencies associated with manual coding, we developed and evaluated three models: an XGBoost classifier with bag-of-words features and word embeddings features, an LSTM network using pretrained Spanish word embeddings as a language model, and a fine-tuned BERT language model (BETO). Deep learning models outperformed the traditional baseline, with BETO achieving the highest accuracy. The new ENUSC (Encuesta Nacional Urbana de Seguridad Ciudadana) workflow integrates the selected model into an API for automated classification, incorporating a certainty threshold to distinguish between cases suitable for automation and those requiring expert review. This hybrid strategy led to a 68.4% reduction in manual review workload while preserving high-quality standards. This study represents the first documented application of deep learning for the automated classification of victimization narratives in official statistics, demonstrating its feasibility and impact in a real-world production environment. Our results demonstrate that deep learning can significantly improve the efficiency and consistency of crime statistics coding, offering a scalable solution for other national statistical offices. Full article

Background and Objectives: A provegetarian (PVG) food pattern, also known as a plant-based food pattern, which prioritizes the consumption of plant-based foods without completely excluding animal-based foods has been associated with health benefits. However, not all plant-based foods are healthy. We prospectively evaluated the association between different PVG food patterns and the risk of total mortality in the “Seguimiento Universidad de Navarra” (SUN) cohort. Methods: The SUN Project is a Mediterranean cohort study involving Spanish university graduates. A validated 136-item semi-quantitative food frequency questionnaire was used. A PVG food pattern, as previously proposed, was calculated assigning positive scores to plant-based foods and inverse scores to animal-based foods. Participants were categorized into quintiles based on their adherence to this pattern. Additionally, healthy and unhealthy PVG food patterns were derived. Results: Data from 17,989 participants with a mean baseline age (standard deviation) 38 (±12) years were analyzed. Over a mean follow-up period of 12 years, 460 deaths (2.6%) were recorded. Participants with higher adherence to the PVG food pattern (Q5) exhibited a 32% lower risk of total mortality [hazard ratio (HR): 0.68 (95% CI: (0.50–0.93); p for trend = 0.020] as compared to those with lower adherence (Q1), after adjusting for multiple confounders. This inverse association persisted for the healthy PVG food pattern [HR: 0.65 (95% CI: 0.47–0.90); p for trend = 0.016]. In contrast, the unhealthy PVG food pattern did not show any significant association with mortality [HR: 1.31 (95% CI: 0.94–1.83)]. Conclusions: Higher adherence to a PVG food pattern, which emphasizes the consumption of plant-based foods, reduces the risk of total mortality in the SUN cohort. Full article

Objective: The objective of this study was to analyze the prevalence and key sociodemographic and lifestyle determinants of metabolic syndrome (MetS) and the hypertriglyceridemic waist (HTGW) phenotype in a large occupational cohort. Background: Metabolic syndrome (MetS) and the hypertriglyceridemic waist (HTGW) phenotype, defined as the simultaneous presence of elevated waist circumference and high triglyceride levels, are major predictors of cardiometabolic morbidity and mortality. Despite their clinical relevance, data on their distribution and determinants in large occupational populations remain limited. Methods: A cross-sectional analysis was conducted on 139,634 employed adults (56,352 women and 83,282 men) across Spain, based on standardized clinical evaluations and validated questionnaires assessing physical activity, diet, smoking, alcohol consumption, education, and occupational class. Logistic regression models were used to estimate associations with MetS and HTGW. A longitudinal subsample of 40,431 individuals was followed over a 10-year period (2009–2019) to assess trends in metabolic risk phenotypes. Results: Male sex, older age, lower educational attainment, and unhealthy lifestyle behaviors were associated with a higher prevalence of both MetS and the HTGW phenotype. Physical inactivity, low adherence to the Mediterranean diet, and alcohol consumption were significantly associated with increased risk. The HTGW phenotype proved useful in identifying high-risk individuals, with a steadily increasing prevalence over time. Conclusions: Sociodemographic disparities and modifiable lifestyle factors significantly influence the prevalence and progression of MetS and HTGW in the Spanish workforce. Preventive strategies should emphasize early workplace screening, promotion of healthy behaviors, and reduction in educational and socioeconomic inequalities to mitigate cardiometabolic risk. Full article

Climate change and global warming are causing growing environmental concerns, prompting many countries to increase investments in renewable energies. The high growth rate of renewables in the energy systems brings significant intermittency challenges. Demand-side flexibility is presented as a viable solution to address this phenomenon. In this framework, this research study proposes a novel methodology to evaluate the flexibility potential that residential consumers can offer to the Distribution System Operator (DSO). Moreover, it pretends to provide guidelines and design of standardized parameters to disaggregate the aggregated energy consumption data of end-users. This step is essential to identify and characterize the primary energy consumption processes in the residential sector, laying the groundwork for future flexibility evaluation. Furthermore, the modeling of the energy consumption curves will enhance residential sector demand-side flexibility enabling end-users to modify their usual consumption patterns. The implemented methodology has been applied to real consumer data provided by the DSO of a Spanish municipality of about 29,000 habitants in the Alicante Province (Spain). Results achieved allowed the validation of the proposed methodology enabling the disaggregation of residential energy profiles and facilitating the subsequent dynamic assessment of residential end-user’s demand flexibility. Moreover, this work will provide valuable guidelines to carry out short-term energy resource planning and solve operational problems of the energy systems. Full article

The accelerated growth of the transport sector has increased oil consumption and greenhouse gas (GHG) emissions, intensifying global environmental challenges. The electrification of transportation has emerged as a key strategy to achieve sustainability targets, with electric vehicles (EVs) expected to account for 50% of global car sales by 2035. However, widespread adoption requires smart infrastructure capable of enabling dynamic in-motion charging. In this context, Electric Road Systems (ERSs), particularly those based on Wireless Power Transfer (WPT) technologies, offer a promising solution by transferring energy between road-embedded transmitters and vehicle-mounted receivers. This study assesses the structural response and service life of conventional and electrified asphalt pavement sections representative of the Spanish road network. Several standard pavement configurations were analyzed under heavy traffic (dual axles, 13 tons) using a hybrid approach combining mechanistic–empirical multilayer modeling and three-dimensional Finite Element Method (FEM) simulations. The electrified designs integrate prefabricated charging units (CUs) placed at a 9 cm depth, disrupting the structural continuity of the pavement. The results reveal stress concentrations at the CU–asphalt interface and service life reductions of up to 50% in semiflexible pavements. Semirigid sections performed better, with average reductions close to 40%. These findings are based on numerical simulations of standard Spanish sections and do not include experimental validation. Full article

Background/Objectives: The objective of this study was to validate the Spanish version of the European Evaluation of Vertigo (EEV) and analyse its test–retest reliability, standard error of measurement (SEM), minimum detectable change (MDC), concurrent validity, and discriminant validity. Methods: A cross-sectional validation study was designed. Subjects were recruited from the Otolaryngology Service of the University Hospital of Jaen. Psychometric properties of the EEV were analysed, including the concurrent validity, the SEM, and the MDC. Discriminant validity was calculated using the receiver operating characteristic (ROC) curve. Results: The EEV test–retest reliability was nearly perfect (Kappa index = 0.97). The SEM and the MDC were set at 0.56 and 1.10, respectively. Regarding the discriminant validity, the area under the curve (AUC) was 0.831 (95% CI; 0.743–0.899) for the BPPV prediction, the AUC = 0.731 (95% CI; 0.633–0.815) for the disability prediction from the ABC-16 score, and the AUC = 0.846 (95% CI; 0.760–0.911) for the disability prediction from the ABC-6 score. Furthermore, a cut-off point greater than 12 was a good predictor of disability and the fall risk measured with the ABC scale, whereas a value of 11 points was a good predictor for discriminating BPPV patients. Conclusions: The Spanish version of the EEV is a valid and reliable instrument for evaluating the clinical symptoms of vestibular syndrome. This instrument demonstrated a nearly perfect test-retest reliability, a low measurement error, and good accuracy in discriminating between patients with vestibular disorders and those with BPPV. Full article

This study evaluates the current Spanish insurance framework for catastrophic flood risk, administered by the Consorcio de Compensación de Seguros (CCS), based on nationwide loss data reported by the CCS for the period 1996–2020. The analysis of historical claims data enables a clear differentiation between frequent, low-cost events and infrequent, high-impact catastrophes. While the CCS has fulfilled a critical role in post-disaster compensation, the findings highlight the parallel need for ex ante risk mitigation strategies. The study proposes a more efficient, two-tier risk coverage model. Events whose impacts can be managed through standard insurance mechanisms should be underwritten by private insurers using actuarially fair premiums. In contrast, events with catastrophic implications—due to their scale or financial impact—should be addressed through general solidarity mechanisms, centrally managed by the CCS. Such a risk segmentation would improve the financial sustainability of the system and create fiscal space for prevention-oriented incentives. The current design of the CCS scheme may generate moral hazard, as flood exposure is not explicitly priced into the premium structure. Empirical findings support a shift towards a more transparent, incentive-aligned model that combines collective risk sharing with individual risk responsibility—an essential balance for effective climate adaptation and long-term resilience. Full article

Background/Objective: Shift work has been increasingly associated with adverse metabolic outcomes, including insulin resistance (IR), a key contributor to cardiometabolic diseases. However, few large-scale studies have explored the association between shift work and validated IR indices across sociodemographic and lifestyle variables, stratified by sex. To investigate the relationship between shift work and four surrogate markers of insulin resistance—TyG índex, TyG-BMI, METS-IR (Metabolic score for insulin resistance), and SPISE-IR (Single-Point insulin Sensitivity estimator)—in a large Spanish working population and to assess how sociodemographic and behavioral factors modify these associations. Methods: This cross-sectional study included 53,053 employed adults (31,753 men and 21,300 women) across various regions and labor sectors in Spain. Participants were classified as shift or non-shift workers based on their work schedules. Data were collected during routine occupational health assessments and included anthropometric, clinical, biochemical, and behavioral variables. IR indices were calculated using standard formulas. Statistical analyses included t-tests, chi-square tests, and multivariable logistic regression, with stratification by sex. Results: Shift workers exhibited significantly higher levels of TyG, TyG-BMI, and METS-IR, and lower SPISE values compared to non-shift workers (all p < 0.001). These differences persisted after stratification by sex, age, education, and lifestyle factors. Logistic regression analyses confirmed that shift work independently predicted high IR risk across all indices, with adjusted ORs ranging from 1.49 to 1.89. Physical inactivity, low adherence to the Mediterranean diet, and alcohol consumption were the strongest modifiable predictors. Men exhibited a higher burden of IR than women across all indices. Conclusions: Shift work is independently associated with elevated insulin resistance in both men and women. These findings emphasize the importance of workplace health interventions targeting physical activity, diet, and substance use, particularly in populations engaged in non-standard work schedules. Full article

Readability formulas are mathematical functions that assess the ‘difficulty’ level of a given text. They play a crucial role in aligning educational texts with student reading abilities; however, existing models are often not tailored to specific linguistic or regional contexts. This study aims to develop and evaluate two novel readability formulas specifically designed for the Mexican Spanish language, targeting elementary education levels. The formulas were trained on a corpus of 540 texts drawn from official elementary-level textbooks issued by the Mexican public education system. The first formula was constructed using multiple linear regression, emulating the structure of traditional readability models. The second was derived through genetic programming (GP), a machine learning technique that evolves symbolic expressions based on training data. Both approaches prioritize interpretability and use standard textual features, such as sentence length, word length, and lexical and syntactic complexity. Experimental results show that the proposed formulas outperform several well-established Spanish and non-Spanish readability formulas in distinguishing between grade levels, particularly for early and intermediate stages of elementary education. The GP-based formula achieved the highest alignment with target grade levels while maintaining a clear analytical form. These findings underscore the potential of combining machine learning with interpretable modeling techniques and highlight the importance of linguistic and curricular adaptation in readability assessment tools. Full article

This study underscores how perceived social support, loneliness, and mental well-being shape the emotional bonds that Spanish cat and dog owners form with their pets. A total of 298 participants completed an online survey, including 109 cat owners (36.5%) and 189 dog owners (63.4%). Standardized and validated instruments were used: the Medical Outcomes Study Social Support Survey (MOS-SSS), the UCLA Loneliness Scale, the Warwick–Edinburgh Mental Well-Being Scale (WEMWBS), and the Lexington Attachment to Pets Scale (LAPS). The results confirmed that the attachment to dogs tends to be stronger than to cats, with demographic factors such as gender and age also playing a significant role in the attachment levels. While psychosocial variables did not directly predict the overall attachment scores, lower perceived social support was significantly associated with higher scores on the person substitution subscale among dog owners, indicating that dogs may serve as emotional substitutes for human companionship in socially vulnerable individuals. No comparable association was found among cat owners. These findings highlight species-specific differences in the human–pet bond and emphasize the multifaceted nature of attachment. This study underscores the importance of considering both demographic and psychosocial factors to better understand how pets contribute to human emotional well-being. Full article

Background/Objectives: Preschool children from low-income, ethnically diverse communities face disproportionate rates of behavioral challenges and early expulsion from early care and education (ECE) programs. This study evaluated the efficacy, feasibility, and utility of Jump Start on the Go (JS Go), a bilingual, AI-enabled mobile application. JS Go is designed to deliver a 14-week early childhood mental health consultation model in under-resourced ECE settings. Methods: This mixed-methods study compared JS Go to the standard in-person Jump Start (JS) program. Participants included 28 teachers and 114 children from six centers (three JS Go, three JS). Quantitative measures assessed teacher classroom practices and child psychosocial outcomes at baseline and post-intervention. App usability and acceptability were only evaluated post-intervention. Seven semi-structured interviews were conducted post-intervention with JS Go directors/teachers to assess the app’s feasibility for implementing the four program pillars: safety, behavior support, self-care, and communication. Results: JS Go was more effective than JS in promoting teacher classroom practices related to behavior support and resiliency. Both programs were similar in improving children’s protective factors and reducing internalizing behaviors, with consistent effects across English and Spanish-speaking children. Teachers rated the JS Go app with high acceptability, though predicted future usage showed greater variability. Rapid qualitative analysis showed that participants found the app easy to use, frequently accessed its resources, and considered it helpful for reinforcing key strategies across the four program pillars. Conclusions: JS Go is a novel approach to providing mental health consultation. It represents a promising mobile adaptation of the established JS consultation model, with important implications for future practice and research. Full article

The present study addresses the need for valid and reliable tools to assess employability thinking among young people in training. In a labor market increasingly shaped by transversal skill demands, the objective was to construct and validate a scale adapted for secondary and post-secondary non-tertiary students. Grounded in strategic frameworks such as the Europe 2020 Strategy, the European Skills Agenda, and relevant Spanish legislation, an abbreviated version of the Graduate Skills and Attributes Scale (GSAS) was administered to a representative sample of 949 Andalusian students enrolled in compulsory secondary education, baccalaureate, or vocational training. A cross-sectional and exploratory research design was adopted, with all procedures conducted in accordance with ethical and legal standards and approved by the University of Granada’s ethics committee. Exploratory and confirmatory factor analyses were performed, leading to a refined 28-item version of the instrument. Items were grouped into four well-defined factors: ethical self-regulation and achievement orientation, effective communication and collaborative working, proactivity and commitment to learning, and analytical thinking and information handling. The factors demonstrated high internal consistency and structural validity. These findings indicate that the scale is a clear and effective tool for assessing employability-related competencies and may assist in the design of educational interventions aimed at improving students’ professional development. Full article

Background: Metabolic dysfunction-associated steatotic liver disease (MASLD) is the most prevalent chronic liver disorder worldwide and is closely linked to the components of metabolic syndrome. Shift work, through its disruption of circadian rhythms and the promotion of adverse behavioral patterns, has been proposed as a potential contributor to metabolic dysfunction and liver disease, yet evidence on its association with MASLD remains limited in large, heterogeneous occupational populations. Objectives: To investigate the association between shift work and MASLD risk using multiple validated non-invasive indices in a large sample of Spanish workers, and to explore the influence of sociodemographic characteristics, lifestyle behaviors, and sex on these associations. Methods: This cross-sectional study analyzed data from 53,053 employed adults across diverse sectors in Spain, including 31,753 men and 21,300 women. The participants underwent standardized occupational health assessments between 2019 and 2020. The MASLD risk was evaluated using seven indices: fatty liver index (FLI), hepatic steatosis index (HSI), ZJU index, fatty liver disease (FLD) index, Framingham steatosis index (FSI), lipid accumulation product (LAP), and BARD score. Sociodemographic, anthropometric, clinical, biochemical, and lifestyle data were collected. Multinomial logistic regression models were used to assess independent associations between shift work and high-risk MASLD scores. Results: Shift workers exhibited significantly higher mean values and prevalence of elevated MASLD scores across all indices compared to non-shift workers, in both sexes. In men, the prevalence of high BARD scores increased from 43.5% (non-shift) to 71.5% (shift), while in women it rose from 49.9% to 85.7%. Multivariate analysis confirmed that shift work was independently associated with an increased MASLD risk, particularly for HSI (OR: 7.83; 95% CI: 7.40–8.26) and ZJU (OR: 5.91; 95% CI: 5.60–6.22). Male sex, older age, smoking, and blue-collar status were also consistently associated with elevated risk scores. Conclusions: Shift work is significantly associated with an increased MASLD risk, independent of sociodemographic and lifestyle factors. Women and blue-collar workers may be especially vulnerable to the hepatic consequences of circadian disruption. These findings support the inclusion of liver health screening in occupational health programs and highlight the need for targeted interventions to reduce the MASLD risk among shift-working populations. Cross-sectional design limits causality; longitudinal studies are needed to confirm temporal relationships. Full article

Background/Objectives: Muscle tissues are a common source of symptoms related to low back pain (LBP), with myofascial trigger points (MTrPs) being a significant contributor. Since previous meta-analyses support interventions targeting MTrPs for reducing pain and improving functional disability in patients with LBP, this review aimed to synthesize current knowledge on the prevalence of MTrPs in LBP patients. Methods: To conduct this systematic review, data were collected from PubMed, Cochrane, and Web of Science. Published articles at any time up to February 2025 that comprised descriptive, observational, or experimental studies in English/Spanish language reporting the prevalence of active or latent MTrPs in patients with LBP were eligible. After assessing the methodological quality, a structured and qualitative synthesis was conducted using a standardized form that captured participant characteristics, evaluated muscles, the number or percentage of active and latent MTrPs in each group, clinical features, summarized results, and conclusions. Results: Nine articles with acceptable methodological quality were included. The prevalence of active MTrPs in patients with LBP was quadratus lumborum (ranging from 30% to 55%), gluteus medius (from 34% to 45%), piriformis (42%), psoas (from 5% to 10%), and lumbar iliocostalis (from 33% to 38%). Latent MTrPs were most common in the gluteus medius (74%) and quadratus lumborum (14–17%), with the piriformis, psoas, and lumbar iliocostalis also affected. Conclusions: Active and latent MTrPs are common in muscles such as the quadratus lumborum, gluteus medius, and iliocostalis in individuals with LBP, with prevalence varying by pain chronicity and etiology. MTrPs in the gluteal region are more frequent in lumbosacral radiculopathy, suggesting a neurogenic-like component. Since the subjectivity of manual palpation and study heterogeneity limit generalizability of the results, future research should standardize diagnostic criteria of MTrPs to ensure the consistency of results. Full article