Abstract: Background: Musculoskeletal disorders (MSDs) are highly prevalent among healthcare workers, particularly in nursing staff, where reported prevalence rates range from 57% to 93%. Perfusionists are highly specialized healthcare professionals responsible for operating heart-lung machines during cardiac surgery. To date, the prevalence of MSDs in this professional group has not been systematically investigated. To address this gap, perfusionists in Germany were surveyed about MSDs. Methods: The German version of the Nordic Musculoskeletal Questionnaire (NMQ) was used. Pearson correlation and chi-squared tests were applied. Results: 287 perfusionists (72 female, 215 male; age 42.6 ± 11.9 years, professional experience 13.5 ± 10.9 years) from 45 German cardiac centers participated. 86% reported MSDs, with the lower back (65.5%) and neck (58.9%) being most frequently affected, with 4.5% to 36.6% in the other body regions. Increasing age was significantly associated with higher prevalence in six body regions, more professional experience was connected in five regions. Occupational risk factors previously identified in nursing were found to be applicable in perfusion. Conclusion: This study demonstrates a high prevalence of MSDs among perfusion staff in Germany. The findings underscore the need for preventive measures, coping strategies, and further research to reduce work related musculoskeletal strain in perfusion staff.

Abstract: This is quantitative research that explored cause-and-effect predictions of mental health of college students based on advanced causal inference and machine learning classification methods. The study conducted a cross-sectional analysis of 101 university students, identifying depression, anxiety, and panic attacks prevalence based on the Student Mental Health dataset (Shariful07, 2020). This study used a two-fold analytic literature, wherein five causal inference approaches were used to predict the gender impacts on mental health outcomes adjusting for confounding factors, and three supervised learning algorithms were used to build predictive models. Findings indicated a prevalence rate of 34.7, 33.7, 32.7, and a high degree of comorbidity of mental conditions prevalence of depression, anxiety, and panic attacks respectively. Regression adjustment, Mantel-Haenszel stratification, direct standardization, propensity score, and instrumental variables all provided convergent estimates, and E-values showed that they were robust to unmeasured confounding. Machine learning models had a range of AUC-ROC of 0.52-0.71 with best results by XGBoost. The analysis of the importance of the feature revealed that marital status, age, and academic variables were the important predictors. This paper has shown that causal inference and machine learning are complementary in risk factor knowledge and prediction, respectively, and have implications in terms of early detection and intervention in university mental health services.

Abstract: This paper explores how Location-Based Games (LBGs), especially those with Augmented Reality (AR), can help people move more and spend less time just looking at screens. LBGs make walking or being active a part of the game, which could be useful for public health. I use three main sources: recent research, my own experience with LBGs, and informal interviews with adult players. I look at how well LBGs get people to move, what keeps them interested, and what problems they face. Results show that LBGs can increase motivation and activity at first, but people often lose interest over time. Safety and access are also issues. The paper ends with practical ideas to help LBGs work better and last longer.

Abstract: Background: Paramedics routinely operate in high-stress environments and endure long working hours, contributing to elevated occupational fatigue and increased injury risk. The study aimed to compare fatigue levels between injured and non-injured paramedics and examine associations between self-reported fatigue and self-reported injury among paramedics. Methods: An online survey of paramedics (n=22) assessed self-reported fatigue and injury history using the Occupational Fatigue Exhaustion Recovery Scale (OFERS) and targeted Likert-based questions, with scores transformed to quantify chronic fatigue, acute fatigue, and inter-shift recovery to identify point prevalence. Data were analysed to compare acute and chronic fatigue scores with injury status. Results: Higher chronic fatigue scores were significantly associated with self-reported injuries within the past six months. No significant differences were found in levels of acute fatigue, inter-shift recovery, or perceived fatigue on rest days between those who were and were not injured. Beliefs about fatigue-related injury risk were consistent across injured and non-injured groups. Conclusion: Chronic fatigue may be a key indicator of injury risk among paramedics. These findings highlight the need for proactive, system-level fatigue management strategies that extend beyond subjective measures and address chronic fatigue as a quantifiable operational risk.

Abstract: Neighborhood variations in depression, an important aspect of the overall mental health burden, have been linked both to environmental context (e.g. area crime, neighborhood cohesion), and to area socio-demographic composition. Previous models seeking to explain such spatial variations in mental health, such as those based on Bayesian disease mapping, follow a standard approach defined by: spatially stationary effects of area predictors; predictor effects neglecting potential spatial spillover; and a spatially structured residual to account for unmodelled spatial dependencies. In a study of depression incidence in England neighborhoods, we consider the gains from an alternative strategy, allowing nonstationary environmental impacts; spillover effects of environmental factors, and a non-stationary spatial intensity. We focus particularly on impacts of socio-behavioral environments, namely neighborhood cohesion and crime. We find these to be major influences on neighborhood depression incidence, and also find major gains in model performance by explicitly considering non-stationarity and spillovers. Allowing context heterogeneity, varying spatial intensity and spillover are shown to enhance the impacts of socio-behavioral environments on depression incidence, and such findings have broader relevance to disease mapping regression.

Abstract: Background/Objectives: Low physical activity (PA) is becoming an increasingly serious health problem among overweight school-age children. This study aimed to evaluate the influence of elevated PA during school hours on the nutritional behavior and fat mass of overweight and obese children. Methods: The study involved 11-year-old children (n=148) who were overweight and obese. In the control group, children received physical education lessons in the standard dimension (4 hours a week while the intervention group received 10 hours. Body mass index (BMI), fat mass (FM), and nutritional behavior were analyzed. Results: Compared to baseline, at the end of the intervention, the proportion of obese children increased in the control group and decreased in the intervention group. Regarding nutritional behavior, low consumption of vegetables, fruits, whole grains, poultry, and fish was observed. After a 12-month, the intervention group showed a slight decrease in the consumption of fruits, vegetables, cold cuts, fried dishes, sweets, and fast food, and an increase in the consumption of white bread, whole-grain bread, poultry, red meat, and dairy products (milk, yogurt). In the control group, children exhibited an average increase in the consumption of fruits, vegetables, poultry, red meat, sweets, and fast food Conclusions: An increase in physical activity during school hours was associated with a reduction in the number of obese children and improvements in BMI and FM. However, the intervention group demonstrated only a slight improvement in nutritional behavior.

Abstract: Volcanic eruptions can mobilize naturally occurring toxic elements such as arsenic into surrounding ecosystems, contaminating soil, water, and food webs. Despite increasing evidence of arsenic enrichment in volcanic regions, comprehensive exposure assessments that integrate dietary and drinking water pathways remain limited, particularly in post-eruption contexts where baseline data are scarce. Following the 2020 Taal Volcano eruption, this study conducted a probabilistic risk assessment to quantify aggregate exposure to inorganic arsenic (iAs) among residents of Batangas, Philippines. A Monte Carlo simulation framework (10,000 iterations) integrated post-eruption environmental data on total arsenic in soil, lake water, drinking water and clam tissues with modeled bioaccumulation and transfer factors for fish and major terrestrial crops. Two exposure scenarios, lower bound (50% iAs fraction) and upper bound (90% iAs fraction), were applied to capture uncertainty in arsenic speciation and bioavailability. Simulated iAs concentrations followed the order rice > corn > vegetables > root crops. Aggregate daily iAs doses averaged 3.0 ± 1.4 µg/kg bw/day (lower bound) and 4.0 ± 2.0 µg/kg bw/day (upper bound), with females showing slightly higher exposures and pregnant women exhibiting lower doses, likely reflecting cultural restrictions on seafood consumption during pregnancy. Sensitivity analysis identified clam intake, rice intake, and iAs in rice, clams, and drinking water as dominant determinants of total exposure. All simulated individuals exceeded the U.S. EPA non-cancer reference dose (HQ > 1) and cancer risk benchmark (10⁻⁶–10⁻⁴), indicating substantial health concern. These findings highlight the urgent need for sustained environmental monitoring, arsenic speciation analyses, biomonitoring, and public health programs to guide evidence-based management in arsenic-affected volcanic regions.

Abstract: Background: Obesity remains a major clinical and public-health challenge in the United States, contributing to rising cardiometabolic disease and long-term healthcare burden. The COVID-19 pandemic substantially altered physical activity, diet, and access to care, yet nationally representative anthropometric data from the post-pandemic period remain limited. Updated estimates are needed to characterize the current distribution of BMI and to quantify associated metabolic risk. Methods: This study analyzed NHANES 2021-2023 data using survey-weighted methods to generate nationally representative estimates of BMI, obesity prevalence, and demographic disparities. Measured height and weight were used to calculate BMI. Subgroup analyses were conducted by age, sex, and race/ethnicity. To assess clinical relevance, survey-weighted logistic regression evaluated the association between BMI category and diabetes (self-report or HbA1c ≥6.5%), adjusting for demographic and socioeconomic covariates. Results: The analytic sample included 6,337 adults. The nationally weighted mean BMI was 29.1 kg/m2, and obesity prevalence was 39.2%. Obesity was highest among adults aged 40–59 years and among non-Hispanic Black adults. In adjusted clinical models, obesity was strongly associated with diabetes (aOR 5.58; 95% CI 4.31-7.22), and overweight showed a modest elevation in odds (aOR 2.17; 95% CI 1.67-2.86). A multipanel survey-weighted BMI distribution figure illustrates overall and subgroup patterns. Conclusions: This work provides the first nationally representative post-pandemic assessment of BMI and obesity using the resumed NHANES 2021-2023 cycle, demonstrating substantial demographic disparities and clinically meaningful associations with diabetes. These findings emphasize continued population-level surveillance and highlight the need for targeted public health and clinical interventions.

Abstract: Background. Survival after childhood and adolescent and young adult (AYA) cancer has improved substantially; however, dominant survivorship models remain reac-tive—activated post-treatment and anchored to static, exposure- and organ-based screening. This design underuses the anticipatory window at diagnosis and overlooks environmental and social determinants that modulate outcomes across the life course. Methods. We narratively reviewed international frameworks (COG, IGHG, PanCare, NCCN) and synthesized evidence on environmental determinants, exposomics, toxi-cogenomics, and implementation. Building on two decades of real-world practice, we describe the evolution from the Pediatric Environmental History (PEHis) to the Ambiomic Health Compass (AHC), integrating genomic, exposomic, geospatial, clinical, and bio-monitoring layers into routine care. In this framework, survivorship is conceptualized as beginning at the time of cancer diagnosis (“day 0”). Results. PEHis operationalizes guideline-based care with structured environmental and social assessment, personalized plans, and community integration, contributing to improved survival, healthier be-haviors, reduced treatment-related mortality and stronger oncology–primary-care coor-dination. AHC extends PEHis with dynamic risk recalibration, contextual alerts, targeted biomonitoring, and toxicogenomic interpretation, enabling anticipatory decisions from day 0. The manuscript summarizes the paradigm shift (current vs. Ambiomic models), the domain-specific expansion over existing guidelines, the core clinical/system tools, and time-bound metrics (12, 24, 60 months) to support implementation and evaluation. Conclusions. Survivorship should move upstream—from late surveillance to ambiomic, exposure-aware care beginning at diagnosis. Integrating advanced exposomics, muta-tional epidemiology, and explainable analytics can reduce preventable events and chronicity, enhance equity, and align pediatric oncology with planetary health. The PEHis–AHC continuum offers a scalable blueprint for next-generation survivorship programs in Europe and beyond. Ambiomic medicine does not replace precision medi-cine—it completes and extends it by integrating exposomics, social context, and antici-patory analytics from day 0.

Abstract: Objectives: The investigators examined the prevalence of autism spectrum disorder (ASD) as related to the US military and as collected by the US Census Bureau’s National Survey of Children’s Health. Methods: Five questions asked of respondents allow for the inspection of ASD as it pertains to military insurance and active duty status (either past or present) of the parents. Results: Contemporary to the survey, Tricare (or other military insurance) covered children were 30.73% more likely to have an ASD diagnosis than their civilian counterparts. Children of mothers with any military service were 46.19% more likely to be diagnosed with ASD than children of non-military service mothers, with with the greatest portion diagnosed with severe autism (46.33% for mild ASD, 39.62% for moderate ASD, and 60.50% for severe ASD). Similarly, children of fathers with any military service were 42.74% more likely to be diagnosed with ASD than children of non-military service fathers, with increasing severity (37.37% for mild ASD, 45.64% for moderate ASD, and 82.73% for severe ASD). Conclusion: The severity of the results warrant an investigation, with all due haste, with domain-specific US military data that link mother-child and father-child medical records and include suspected or shared toxic exposure of either mother or father and their children.

Abstract: Allergic rhinitis (AR) is a widespread allergic reaction that has been shown to be impacted by the function of the immune system as well as environment and socioeconomic factors. This research is to explore the best predictive model among penalized logistic regression, random forest classifier, and XGBoost classifier, to gain insight into subjects who are susceptible to allergic rhinitis by taking advantage of the integrated data NHANES provides. The random forest model demonstrated the most stable performance. SHAP analysis provided interpretable insights at both group and individual levels, revealing that immune-related markers, including total IgE, eosinophil percentage, and the neutrophil-to-lymphocyte ratio were the strongest predictors of AR susceptibility. Environmental and socioeconomic exposures, such as cotinine levels, housing conditions, and income, also contributed substantially to the predicted risk. Overall, the findings highlighted that AR susceptibility arises from the combined influence of immunologic dysregulation and environmental stressors, underscoring the need for targeted preventive strategies.

Abstract: We present the Universal Suffering Unit (USU), a calibrated, additive unit of experienced suffering that scales with intensity, duration, and affected population, enabling aggregation across people, regions or countries, and time. We define USU as k * sum I^p * Δt, where I is a 0–10 intensity rating, p >= 1 is an exponent that modestly up-weights high intensities, and k is a calibration constant. We calibrate the unit so that a reference trajectory of renal colic (kidney-stone pain) equals 1.0 USU, propose a simple rule for co-occurring harms, and recommend reporting medians with 90% uncertainty intervals from Monte Carlo simulations. Using publicly available data, we illustrate the framework with two examples: dengue in Brazil (epidemiological weeks 1–23 of 2024) and flood-related displacement in Rio Grande do Sul, plus a year-over-year dengue comparison and a sensitivity analysis over p in {1.0, 1.25, 1.5}. These illustrations show how large numbers of moderate episodes and smaller numbers of longer, disruptive episodes can be expressed on a common experiential scale, while remaining interpretable via an anchor ladder. We discuss validation strategies, highlight ethical guardrails and misuse risks, and argue that USU is best used alongside DALY/QALY and routine operational indicators as a decision-support tool for comparing heterogeneous harms, rather than as a stand-alone welfare metric.

Abstract: Preliminary evidence suggests air pollution, particularly fine particulate matter 2.5 (PM2.5), poses a significant threat to maternal health and women of reproductive age. While emerging evidence suggests a link between air pollution and maternal anemia, the specific effect of PM2.5 exposure on hemoglobin levels among reproductive-aged women (15-49 years) remains insufficiently studied. Maternal hemoglobin decline is a known risk factor for adverse pregnancy outcomes with potentially long-term consequences. Understanding the impact of PM2.5 exposure is crucial in regions like Sub-Saharan Africa, where both anemia rates and air pollution levels are significantly elevated. This population-based study investigates the association between ambient PM2.5 concentrations and maternal hemoglobin levels across 43 Sub-Saharan African countries from 2000-2019. Using generalized linear regression models adjusted statistically significant negative association between PM2.5 exposure and hemoglobin levels were observed in Central Africa, while no significant associations were found in Eastern, Western, or Southern Africa. These results suggest that PM2.5 may be an environmental determinant of maternal anemia, with effects that vary by geography. Further research is needed in understudied regions to validate and expand on these findings.

Abstract: Anemia is a major public health concern in South Asia, a region where febrile illnesses and nutritional deficiencies are prevalent. While the environment is a key contributor to maternal anemia, there is limited availability of research on the association between ambient temperature and maternal anemia. This longitudinal population-based study with multiple covariates, utilizing population-level data, examines the relationship between climate change and maternal anemia over the period of 2010 to 2022. Using a negative binomial regression model adjusted for covariates, we modeled the region-specific (n = 8 nations) relationships between annual anemia prevalence in women of reproductive age (15-49 years old) and annual maximum temperatures. After adjustment, the statistical analysis revealed distinct regional differences, with an overall statistically significant but weak association between maternal anemia and maximum temperature. These findings underscore ambient temperature as a determinant of anemia risk in women of reproductive age in South Asia. Further research with larger datasets is needed to clarify causal mechanisms and strengthen evidence for developing climate-specific strategies to address the temperature-related anemia risk. Climate-centered approaches would reduce the large-scale impact of climate-related diseases and improve overall reproductive health.

Abstract: Childhood obesity is a growing global public health challenge, defined primarily by body mass index (BMI) and driven by a combination of reduced physical activity, unhealthy diets, and environmental factors. Overweight in early young age may continue into the adult stage and is associated with physical, psychological challenges, and lower school performances. Beyond increasing the risk of chronic physical conditions, obesity in children is strongly associated with mental health issues such as depression, anxiety, and low self-esteem, often exacerbated by social stigma and body dissatisfaction. Mental health conditions are also an important factor in children with obesity. This review summarizes the development of childhood obesity due to consumption of junk food regularly, lack of outdoor physical activities, and increased screen time, playing video games, inaccessibility of healthy foods, and environment. In addition, this review summarized how overweight children suffer from various mental health conditions such as anxiety, peer pressure, depression, low school performances, and stress creating a cycle that affects both physical and emotional well-being. Effective prevention and management require integrated strategies, including promoting physical exercise, improving nutrition, supporting mental health, and implementing comprehensive community and policy interventions.

Abstract: Background: A large number of guideline recommendations have been developed by local-, state- and national-level health organisations available to promote the healthy eating and physical activity of children attending early childhood education and care (ECEC) settings. However, the evidence supporting these recommendations is often not well-described. An examination of the current evidence is needed to support decision-makers to understand and prioritise practices for implementation.Aim: To describe a novel systematic evidence-mapping process which: i) examines the evidence-base underpinning ECEC-based healthy eating and physical activity practice elements; and ii) classifies practice elements according to the World Health Organization (WHO) Standards for Healthy Eating, Physical Activity, Sedentary Behaviour and Sleep in Early Childhood and Care Settings to examine alignment with current global guidelines. Methods: We undertook a two-stage, five-step systematic process. Stage 1 involved identifying the existing ECEC-based guideline recommendations and randomised controlled trial evidence which evaluated child diet and physical activity outcomes. Stage 2 involved conducting a secondary data analysis and synthesis of the evidence underpinning practice elements by: extracting practice elements of RCTs and mapping these to existing guideline recommendations, where possible, or included these as additional practices; using vote-counting approaches and a framework to assess the evidence underpinning each practice element; and, classifying practice elements according to the WHO Standards for Healthy Eating, Physical Activity, Sedentary Behaviour and Sleep in Early Childhood and Care Settings. Results: We found 16 healthy eating (e.g. Educators discuss the food served with children) and 19 physical activity (e.g. Educators embed physical activity into educational activities) practice elements were assessed as likely beneficial. Most of these mapped to WHO Standard 2: Creating supportive environments. Seven practice elements were assessed as possibly beneficial, two as possibly not beneficial and none as not beneficial. There was insufficient evidence to assess 39 practice elements. Conclusions: This study provides insights into the evidence underpinning practice elements included in ECEC-based healthy eating and physical activity guidelines, identifies evidence-based practice elements not included in existing guidelines and highlights opportunities where evidence can be strengthened.

Abstract: Background: Physical functioning is traditionally assessed and presented as self-reported measures, which have shown either improvement or stability during the last decades at population level. On the other hand, objectively measured, performance-based measures of physical functioning have indicated increased body weight and decreased physical fitness. Therefore, there is a need for objective, measured total physical functioning index (MePFIX). Methods: The MePFIX was developed from the data of 5238 working-aged adults (60% women) who took part in the FINFIT studies from years 2017 and 2021. The outcomes of measured body composition, cardiorespiratory fitness, muscular fitness, physical activity, stationary behavior, and time in bed were used to create the MePFIX. Results: The best performing index contained the fol-lowing measures: waist circumference, estimated maximal oxygen consumption, modified push-up, mean of daily 1-minute metabolic equivalent, high-movement time in bed, lying and reclining during waking hours >20-min bouts, standing, daily step count, moderate-to-vigorous physical activity in absolute terms, and light physical activity relative to fitness. Conclusions: The developed MePFIX is based on population-based data, containing measured outcomes of body composition, cardiorespiratory fitness, muscular fitness, physical activity, sedentary behavior and time in bed. The index could serve as an objective indicator of physical functioning among the target population. The MePFIX can be used as a figure of merit of measured physical functioning for research community and policy makers both at cross-sectional and at longitudinal analyses.

Abstract: In Europe, the practice of swimming in surface water not officially designated as swimming water (wild swimming) appears to have increased in recent years. This prospective case study focuses on the watershed of the German-Dutch Vecht river. During the hot summers of 2018 to 2020, between 29,000 and 37,000 people a year sought cooling in the streams, rivers and canals of this catchment area, into which 52 sewage treatment plants discharge. As a result, 85% of the wild swimmers in the area swam in surface waters that do not comply with the European Bathing Water Directive. Between 2016 and 2020, at least eight outbreaks of gastroenteritis (GE) potentially linked to wild swimming occurred in the region. Most GE outbreaks have been associated with waters containing the highest concentrations of sewage effluent. A total of 1,201 people participated in activities associated with the outbreak of whom at least 107 (11%), mostly children who had been involved in intensive water-based activities, became infected. Considering the rising number of heat waves, it seems likely that the practice of wild swimming will gain in popularity. Because of the deterioration in water quality resulting from climate change, including higher temperatures, droughts and heavy rainfall, the risk of ingesting pathogens during wild swimming is set to increase. This could result in the emergence of further outbreaks. The key issue is to identify ways to mitigate the potential biological risks associated with wild swimming. Potential prevention strategies, including surveillance of outbreaks and pathogens, hazard warnings and improved sewage treatment, were assessed in terms of their effectiveness, cost and social acceptability. Targeted awareness raising, outbreak surveillance, adaptation of prevention manuals, and promoting safe alternatives for water recreation are expected to be relatively easy to apply, effective, socially acceptable and not very costly.

Abstract: Aquatic environments have been a critical source of nutrition for millennia, with wild capture fisheries supplying protein and essential nutrients to populations worldwide. In recent decades, however, a notable shift has occurred with the expansion of aqua-culture, which now represents one of the fastest-growing sectors in food production. Aquaculture plays a key role in mitigating the depletion of wild fish stocks and ad-dressing issues related to overfishing. Despite its potential benefits, the sustainability of both wild and farmed aquatic food systems is increasingly challenged by anthropogenic pollution. Contaminants originating from agricultural runoff, industrial discharges, and domestic effluents enter freshwater systems and eventually reach marine environ-ments, where they may be transported globally through ocean currents. Water is an indispensable input not only for the cultivation of aquatic organisms but also across the broader agri-food sector. Consequently, maintaining water quality is paramount to food safety, environmental integrity, and long-term food security. In ad-dition to conventional seafood products such as fish and shellfish, foods such as those derived from microalgae are gaining attention in Western markets for their high nutri-tional value and potential functional properties. These organisms have been consumed traditionally in Asia for generations and are now being explored as sustainable foods and ingredients as an alternative source of protein. Contaminants of concern in aquatic food products include residues of agrochemicals (e.g., pesticides, veterinary pharmaceuticals), persistent organic pollutants (POPs) such as dioxins, polychlorinated biphenyls (PCBs), and per- and polyfluoroalkyl substances (PFAS), as well as brominated flame retardants, heavy metals (e.g., mercury, cadmium, lead), and inorganic arsenic. In parallel, public and scientific attention has intensified around plastic pollution, particularly microplastics and nanoplastics, which are in-creasingly detected in aquatic organisms and are the subject of ongoing toxicological and ecological risk assessments. While the presence of these chemical hazards neces-sitates robust risk assessment and regulatory oversight, it is essential to balance these concerns against the documented health benefits of aquatic foods, which are rich in omega-3 fatty acids, high-quality proteins, vitamins, and trace elements. Furthermore, beyond direct human health implications, the environmental impact of pollutant sources must be addressed through integrated management approaches to ensure the long-term sustainability of aquatic ecosystems and the food systems they support.

Abstract: Wearable light loggers and optical radiation dosimeters are increasingly used to quantify personal light exposure in research and clinical contexts. However, the growing diversity of devices poses challenges for researchers selecting appropriate instruments. We present an open-access, web-based specification tool for wearable light loggers and optical radiation dosimeters that provides a structured framework for defining, comparing, and communicating device requirements. The tool integrates expert-informed parameters spanning usability, fidelity, and data requirements and generates exportable Word or PDF specifications suitable for procurement or documentation. By supporting transparent and consistent specification, the tool contributes to harmonisation in light exposure research and facilitates reproducibility and interoperability.