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The fracture behavior of polymeric materials has been widely studied in recent years, both experimentally and numerically. Different numerical approaches have been considered in the study of crack propagation processes, from continuum-based numerical formulations to discrete models, many of the latter being limited in the selection of the Poisson’s coefficient of the considered material. In this work, we present a numerical and experimental analysis of the crack propagation process of polymethylmethacrylate beams with central and eccentric notches subjected to quasi-static three-point bending tests. The developed discrete numerical model consists of a regular triangular lattice model based on axial and normal interaction springs, accounting for nearest-neighbor interactions. The proposed model allows solving the above mentioned limitation in the selection of Poisson’s coefficient, incorporating a fracture criterion defined by a bilinear law with softening that includes the fracture energy in the formulation and allows considering a progressive damage. One of the main objectives of this work is to show the capacity of this lattice to simulate quasi-static fracture problems. The obtained results show that the proposed lattice model is capable of providing results close to the experimental ones in terms of crack pattern, peak load and initial stiffening.

There is a growing interest in studies involving carbohydrate (CHO) manipulation and subsequent adaptations to endurance training. This study aimed to analyze whether a periodized carbohydrate feeding strategy based on a daily training session has any advantages compared to a high-carbohydrate diet in well-trained cyclists. Seventeen trained cyclists (VO2peak = 70.8 ± 6.5 mL·kg−1·min−1) were divided into two groups, a periodized (PCHO) group and a high-carbohydrate (HCHO) group. Both groups performed the same training sessions for five weeks. In the PCHO group, 13 training sessions were performed with low carbohydrate availability. In the HCHO group, all sessions were completed following previous carbohydrate intake to ensure high pre-exercise glycogen levels. In both groups, there was an increase in the maximal lactate steady state (MLSS) (PCHO: 244.1 ± 29.9 W to 253.2 ± 28.4 W; p = 0.008; HCHO: 235.8 ± 21.4 W to 246.9 ± 16.7 W; p = 0.012) but not in the time to exhaustion at MLSS intensity. Both groups increased the percentage of muscle mass (PCHO: p = 0.021; HCHO: p = 0.042) and decreased the percent body fat (PCHO: p = 0.021; HCHO: p = 0.012). We found no differences in carbohydrate or lipid oxidation, heart rate, and post-exercise lactate concentration. Periodizing the CHO intake in well-trained cyclists during a 5-week intervention did not elicit superior results to an energy intake-matched high-carbohydrate diet in any of the measured outcomes.

To date, the performance in triathlon has been measured through time or position. Although this is what defines the medals and the goal of the competition, it can have some limitations. As an alternative, the purpose of this study is to assess the degree of concordance of performance between each of the triathlon disciplines with overall performance through the triathlon performance indicator for the Olympic distance event. The official results from the World Triathlon Series for Olympic distance events from 2000 to 2019 were examined. A total of 11,263 entries were analysed, 6273 corresponding to elite men and 4990 to elite women. Moderate agreement was found between the running performance and overall performance in both elite men ICCa = 0.538 and elite women ICCa = 0.581. Moreover, moderate agreement was found between swimming performance and overall performance in both elite men ICCa = 0.640 and elite women ICCa = 0.613. Finally, good agreement was found between cycling performance and overall performance also in both elite men ICCa = 0.777 and elite women ICCa = 0.816. The main results of the present study show that the cycling performance indicator could be an alternative to anticipate the overall performance in the competition for the Olympic distance event.

When looking at life expectancy (LE) by sex, women live longer than men in all countries. Biological factors alone do not explain gender differences in LE, and examining structural differences may help illuminate other explanatory factors. The aim of this research is to analyse the influence of gender inequality on the gender gap in LE globally. We have carried out a regression analysis between the gender gap in relativised LE and the UN Gender Inequality Index (GII), with a sensitivity analysis conducted for its three dimensions, stratified by the six World Health Organization (WHO) regions. We adjusted the model by taking into consideration gross national income (GNI), democratic status and rural population. The results indicated a positive association for the European region (ß=0.184) and the Americas (ß=0.136) in our adjusted model. Conversely, for the African region, the relations between gender equality and the LE gender gap were found to be negative (ß=-0.125). The findings suggest that in the WHO European region and the Americas, greater gender equality leads to a narrowing of the gender LE gap, while it has a contrary relationship in Africa. We suggest that this could be because only higher scores in the GII between men and women show health benefits.

Heart failure (HF) is a major contributor to morbidity, mortality, and healthcare costs, particularly among older adults. Effective outpatient risk stratification remains a clinical challenge, especially following hospital discharge or episodes of acute decompensation. Although both lung ultrasound (LUS) and the HEFESTOS score have shown individual prognostic value, their combined use in primary care settings has not been extensively explored. This prospective cohort study included 107 patients with confirmed HF followed at a primary care center in southern Catalonia. At baseline, all patients underwent LUS and HEFESTOS assessment. The primary outcome was HF decompensation, defined as worsening symptoms requiring medical attention, emergency care, hospitalization, or death. Over a mean follow-up of 72 days, 25 patients (23.3%) experienced decompensation. In multivariate analysis, only the HEFESTOS score was independently associated with decompensation. LUS and HEFESTOS showed moderate agreement (Kappa = 0.456), and LUS demonstrated moderate discriminative capacity (AUC = 0.677) with high sensitivity (81.7%) and positive predictive value (81.7%). These findings support the routine use of the HEFESTOS score in primary care and suggest that LUS may serve as a complementary tool, particularly for identifying subclinical pulmonary congestion. Their combined use could enhance outpatient risk stratification and guide individualized follow-up strategies in HF management.

Background Clinical placements are essential for nursing students’ competence development but represent one of the most stressful components of their training. High levels of perceived stress may hinder learning, undermine confidence, and negatively affect clinical performance. Evidence on pedagogical strategies to mitigate these stressors remains inconsistent, and the potential of blended-learning models during placements is not well established. This study evaluated the effect of a tutored blended-learning model (i-MHA) on perceived stressors among final-year nursing students. Methods A prospective quasi-experimental pre–post study with a control group was conducted across three campuses of the Rovira i Virgili University (Spain) during the 2021–2022 academic year. The intervention group received a structured blended-learning model incorporating moderated online forums, guided reflection, and weekly tutor-led supervision. The control group followed the traditional supervision approach. Perceived stress was assessed before and after placements using the Kezkak questionnaire. Between-group differences were analysed using the Mann–Whitney U test, and within-group changes using the Wilcoxon test. Effect sizes (Cohen’s d) and attrition analyses were performed to validate internal consistency. Results A total of 126 students participated (86.89% women; mean age 23.64 years). No significant baseline differences were found between groups across any Kezkak dimensions. After the intervention, the only significant between-group difference emerged in Factor 3 (Relationship with tutors and peers), with lower stress scores in the intervention group (p = 0.030). In the paired intragroup analysis (n = 61), the intervention group showed a significant improvement in the same dimension (p = 0.032), while no significant changes were detected in the control group. No sex-related differences emerged, and baseline comparisons between paired and unpaired participants indicated no systematic attrition bias. Conclusions The tutored b-learning model improved students’ perceived relationship with tutors and peers during clinical placements, reducing stress associated with supervisory interactions. Although other stress dimensions did not change, the model strengthened communication and academic support, offering a promising strategy to enhance student well-being and learning during clinical practice. Further research with larger and diverse samples is warranted to explore its long-term impact on academic performance, psychological well-being, and transition to professional practice. Clinical trial number Not applicable.

Fibromyalgia syndrome (FMS) is characterized by generalized chronic musculoskeletal pain, fatigue, and sleep disturbance, as well as cognitive, somatic, and other symptoms. Most people affected by FMS are women, and studies analyzing this condition in men are scarce. In this study, we discuss the physical and psychological symptoms of FMS in men, analyze the possible side effects of pharmacological therapies, and explore the impact of the illness comparing these results between the different classification groups according to sociodemographic variables (marital status, level of education, employment situation and number of people living at home). We used a sequential exploratory mixed method (MM). Qualitative information was obtained from two focus groups (n = 10). Structured questionnaires were administered to 23 men affected by FMS. The mean age of the participants was 51.7 years (SD = 9.64). The most common drugs used were antidepressants and anxiolytics (86.9%), followed by non-steroidal anti-inflammatory drugs (82.6%) and opioids (60.9%). Current level of pain was high (8.2; SD = 1.1), while perceived health and satisfaction with pharmacological treatments were low (4.6; SD = 2.6 and 3.5; SD = 3.2, respectively). The impact of FMS measured using the Fibromyalgia Impact Questionnaire (FIQ) was very high at 88.7 (SD = 8.2). Six categories related with symptoms and side effects of the medication were observed in the qualitative data: (1) main physical symptoms, (2) mood disorders, (3) insomnia and non-restorative sleep, (4) cognitive disturbance, (5) hypersensitivity, and (6) symptoms secondary to opioids. Pain and fatigue were the symptoms most often mentioned by the participants (70% and 80%, respectively). Other important symptoms were anxiety, depression, and memory and sleep disorders. The consumption of opioids causes further unwanted symptoms such as drowsiness and dependence, which makes it difficult for patients to perform basic everyday activities. We believe it is vitally important to continue investigating this symptomatology in order to improve diagnosis and treatment for these patients.

(1) Background: There is a lack of data on the long-term training characteristics and performance markers of elite young female endurance athletes. The aim of this study was to present the training load (ECOs), as well as the evolution of the anthropometric values and performance of three elite U23 female triathletes over a season. (2) Methods: General training data and performance data relating to the swimming, cycling, and running legs of the 2021 season were described. The training intensity distribution (TID) was presented using the triphasic model, while the training load was based on the ECO model. An anthropometric analysis was also conducted in accordance with the ISAK standards. (3) Results: Triathletes increased their VO2max in cycling (6.9–10%) and running (7.1–9.1%), as well as their power and speed associated with the VO2max (7.7–8.6% in cycling and 5.1–5.3% in running) and their swimming speed associated with the lactate thresholds (2.6–4.0% in LT2 and 1.2–2.5% in LT1). The triathletes completed more than 10 h of weekly average training time, with peak weeks exceeding 15 h. The average TID of the three triathletes was 82% in phase 1, 6% in phase 2, and 12% in phase 3. A decrease in the sum of skinfolds and fat mass percentage was observed during the season in the three triathletes, although the last measurement revealed a stagnation or slight rise in these parameters. (4) Conclusions: The triathletes performed a combination of two training periodization models (traditional and block periodization) with a polarized TID in most of the weeks of the season. Improvements in performance and physiological parameters were observed after the general preparatory period as well as a positive body composition evolution throughout the season, except at the end, where the last measurement revealed stagnation or a slight decline. This study can be useful as a general guide for endurance coaches to organize a training season with female U23 triathletes.

Influenza is a respiratory disease that causes annual epidemics during cold seasons. These epidemics increase pressure on healthcare systems, sometimes provoking their collapse. For this reason, a tool is needed to predict when an influenza epidemic will occur so that the healthcare system has time to prepare for it. This study therefore aims to develop a statistical model capable of predicting the onset of influenza epidemics in Catalonia, Spain. Influenza seasons from 2011 to 2017 were used for model training, and those from 2017 to 2018 were used for validation. Logistic regression, Support Vector Machine, and Random Forest models were used to predict the onset of the influenza epidemic. The logistic regression model was able to predict the start of influenza epidemics at least one week in advance, based on clinical diagnosis rates of various respiratory diseases and meteorological variables. This model achieved the best punctual estimates for two of three performance metrics. The most important variables in the model were the principal components of bronchiolitis rates and mean temperature. The onset of influenza epidemics can be predicted from clinical diagnosis rates of various respiratory diseases and meteorological variables. Future research should determine whether predictive models play a key role in preventing influenza.

Background: The COVID-19 pandemic has exacerbated mental health challenges across occupational sectors, disproportionately affecting workers in essential and public-facing roles. Objectives: This study ai to identify the occupational sectors in Spain most affected by mental health-related Temporary Work Incapacity due to Common Contingencies during the first COVID-19 lookdown (14 March–21 June 2020) to examine sex-based differences and to analyze the associate economic burden. Methods: A descriptive, retrospective cross-sectional study was conducted using data from salaried workers affiliated with Asepeyo, a major Social Security mutual insurance provider in Spain. The sample comprised 5135 workers granted Temporary Work Incapacity due to mental health diagnoses during the lockdown period. Variables analyzed included sex, age, ICD-10 diagnosis, occupational sector, duration of medically certified leave, and estimated direct economic cost. A focused subsample of 2123 workers from the ten most affected sectors was also examined. Results: Generalized Anxiety Disorder was the most prevalent diagnosis (69.17%), followed by adjustment disorders and depressive episodes. Women accounted for 63.5% of the total sample and 80.6% of the most affected sectors, which included elderly care, retail, education, cleaning, and healthcare. The average cost per episode was EUR 2465.7, with longer leave durations observed in sectors characterized by high emotional and social exposure. Conclusions: Mental health-related disorders during the COVID-19 lockdown revealed marked sex-based disparities and sectoral vulnerabilities. Public-facing and care-related occupations experienced a disproportionate burden. These findings support the need to recognize certain mental health conditions as occupational diseases to develop targeted, gender-informed workplace mental health strategies.