Manuel Adolfo Pérez-Priego

Stretching is commonly recommended to improve flexibility and reduce injury risk; however, its practical implementation among recreational snowboarders and alpine skiers remains inconsistent. A cross-sectional online survey was conducted during the 2024–2025 winter season. Of 403 collected responses, 391 valid questionnaires were included after data screening. The survey assessed sociodemographic characteristics, stretching perceptions, practices, perceived barriers, information sources, and supervision. Descriptive statistics and chi-square tests were used to explore associations between sport modality and generational cohorts. Although 91.3% of participants considered stretching necessary, only 39.7% reported performing stretching exercises in the previous six months. The most frequently reported barriers were lack of time (76.1%) and low motivation (54.2%). Alpine skiers attributed greater importance to stretching than snowboarders. Significant generational differences were observed in sport modality, practice volume, and information-seeking behaviour (p < 0.05), but not in stretching frequency or duration; therefore, Hypothesis 1 was not supported. Only 22.7% of participants reported receiving professional supervision. In recreational winter sports, stretching is widely valued but inconsistently practiced. Behaviour appears to be driven more by motivational and contextual factors than by generational differences in practice frequency, highlighting the need for targeted educational strategies and evidence-informed guidance.

This study analyses the impact of the pandemic on the poor performance of stock markets in Latin America and the Caribbean (LAC) by examining the COLCAP, BOVESPA, IPSA, MERVAL and MEXBOL indices between January 2018 and March 2021, with a particular focus on the first half of 2020. The proposed methodology is relatively new and consists of a sequential combination of statistical tests designed to determine whether index returns follow a random walk, and if so, what type this is. Empirical evidence shows that sharp price declines and increased volatility associated with the pandemic generally favoured weak-form efficiency in these markets. This reduced short-term return predictability and reinforced the role of prices in processing available information quickly. Additionally, the results imply that the impact of the pandemic on LAC markets was not uniform, but it did lead to a faster and more consistent incorporation of global and local news into stock prices, with significant implications for investor risk management and policymakers responsible for financial stability

Tritordeum is a new cereal resistant to drought and high temperatures, and it is a very healthy crop. The aim of this study was to compare two different diets (tritordeum meadow vs. oat meadow) for grazing pregnant ewes to determine if there was any effect on the objective physiological indicators of animal welfare. A total of 150 pregnant Merino ewes (3–5 years) were randomly divided into two groups (n = 75 each) to be fed with two different meadows, being evaluated during the spring season. Red blood cells count, haemoglobin, packed cell volume, white blood cell count, neutrophiles/lymphocytes ratio, lactate dehydrogenase, creatinine phosphokinase, aspartate aminotransferase, glucose, cortisol, total plasma proteins, albumin, globulins, albumin/globulins ratio, alkaline phosphatase, glutamate dehydrogenase, IgA, and IgG were determined. Overall, the results of this study indicate that the welfare of pregnant ewes fed with tritordeum meadow was better than that of pregnant ewes fed with oat meadow. Tritordeum meadow had a positive influence on the physiological parameters of animal welfare studied in pregnant Merino ewes. Therefore, tritordeum meadow can be considered a functional feed, as it has a beneficial effect on health beyond its basic nutritional value. Farmers are recommended to feed a cereal such as tritordeum grassland to their sheep, as it not only ensures that the animals benefit from all the nutrients, but also prevents diseases and improves their quality of life. In addition, the cereal’s resistance to fungal diseases makes it suitable for use in sustainable production systems with a reduced environmental footprint.

The present work aims to analyze the properties of the working conditions recorded in the Sixth European Working Conditions Survey (EWCS); with it, it has being built seven independent indexes about different aspects of work’ quality in the health sector, and these constructs are used to evaluate their effects on work engagement (WE). In this sense, the originality of incorporating teamwork as a modulating variable is included. To analyze the effects of the job quality index (JQI) on the WE, a logistic regression model is proposed for a total of 3044 workers within the health sector, differentiating between those who work or not in a team; in a first stage and these estimates are compared with those obtained using an artificial neural network model, and both are used for the consideration of the research hypotheses about several causal factor. An important contributions of the study, it is related to how work commitment is mainly influenced by prospects, social environment, intensity and earnings, all of them related to job performance. Therefore, knowledge of the determinants of work commitment and the ability to modulate its effects in teamwork environments is necessary for the development of truly sustainable Human Resources policies.

Long-term ratings of companies are obtained from public data plus some additional nondisclosed information. A model based on data from firms’ public accounts is proposed to directly obtain these ratings, showing fairly close similitude with published results from Credit Rating Agencies. The rating models used to assess the creditworthiness of a firm may involve some possible conflicts of interest, as companies pay for most of the rating process and are, thus, clients of the rating firms. Such loss of faith among investors and criticism toward the rating agencies were especially severe during the financial crisis in 2008. To overcome this issue, several alternatives are addressed; in particular, the focus is on elaborating a rating model for Moody’s long-term companies’ ratings for industrial and retailing firms that could be useful as an external check of published rates. Statistical and artificial intelligence methods are used to obtain direct prediction of awarded rates in these sectors, without aggregating adjacent classes, which is usual in previous literature. This approach achieves an easy-to-replicate methodology for real rating forecasts based only on public available data, without incurring the costs associated with the rating process, while achieving a higher accuracy. With additional sampling information, these models can be extended to other sectors.

The cultural and historical heritage of a city is a major resource for attracting tourists. Therefore, determining how to perceive and identify the characteristics of persons visiting a locality attracted by its heritage is relevant for the purpose of better meeting their expectations and needs. This research focuses on understanding the perceptions, motivations, and satisfaction of women visiting Cordoba (Spain). Thus, on the basis of a questionnaire completed by women visiting Cordoba between the months of June and November 2019, statistical analysis was conducted. Using various multivalent case-grouping techniques, segments of tourists holding similar perceptions of cultural heritage were detected. Moreover, non-parametric statistical techniques highlighted significant differences between the valuations obtained in the various segments. This analysis exposed a segment of women who, known as absorptive tourists, are characterized by a high cultural motivation to visit the city of Cordoba linked to the heritage sites they have visited. The conclusions obtained herein should be useful for adjusting the city’s provision of tourism services to satisfy the demand of female tourists visiting the city.

The cultural and historical heritage of a city is a major resource to attract tourists. Therefore, reaching out to perceive and identify the characteristics of persons visiting a locality attracted by their property is relevant for the purpose of better meeting their expectations and needs. This research focuses on knowing the perceptions, motivations and satisfaction of women visiting Cordoba (Spain). Thus, on the basis of the questionnaire carried out on women visiting Cordoba during the months of June and November 2019, a statistical analysis has been made. Using various multivalent case-grouping techniques, tourist segments with similar perceptions of cultural heritage have been detected. Moreover, non-parametric statistical techniques have showed up significant differences between the valuations obtained in the various segments. This analysis has exposed a segment of women who, known as absorbent tourists, are characterized by the high cultural motivation to visit the city of Cordoba linked to the heritage they have visited. The conclusions obtained should be useful in adjusting the city's tourist supply to the specific demand of a population sector such as women visiting the city.