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Aviation industry is extremely vulnerable to economic turbulence or a pandemic. Over the past decade, a number of well-known European airline brands have gone into bankruptcy, with consequences such as leaving thousands of passengers stranded abroad. The present research assesses the predictive power of the updated Altman Z-score model (1983 and 2017) using data on European airline bankruptcies over the period 2009–2020. The results indicate that the Z″-score (2017) for private non-manufacturing companies shows satisfactory predictive power when applied on European aviation industry. In this study, we analyze in depth the performance of the updated Altman Z′- and Z″-scores (1983, 2017), connecting airline's financial and non-financial information, and provide a comprehensive interpretation of Z-score predictive power. We aim to contribute to the literature by offering a unique and novel perspective on the Altman model's accuracy for the European air transport industry.

The performance of diagnostic Computer-Aided Design (CAD) systems for retinal diseases depends on the quality of the retinal images being screened. Thus, many studies have been developed to evaluate and assess the quality of such retinal images. However, most of them did not investigate the relationship between the accuracy of the developed models and the quality of the visualization of interpretability methods for distinguishing between gradable and non-gradable retinal images. Consequently, this paper presents a novel framework called “FGR-Net” to automatically assess and interpret underlying fundus image quality by merging an autoencoder network with a classifier network. The FGR-Net model also provides an interpretable quality assessment through visualizations. In particular, FGR-Net uses a deep autoencoder to reconstruct the input image in order to extract the visual characteristics of the input fundus images based on self-supervised learning. The extracted features by the autoencoder are then fed into a deep classifier network to distinguish between gradable and ungradable fundus images. FGR-Net is evaluated with different interpretability methods, which indicates that the autoencoder is a key factor in forcing the classifier to focus on the relevant structures of the fundus images, such as the fovea, optic disk, and prominent blood vessels. Additionally, the interpretability methods can provide visual feedback for ophthalmologists to understand how our model evaluates the quality of fundus images. The experimental results showed the superiority of FGR-Net over the state-of-the-art quality assessment methods, with an accuracy of >89% and an F1-score of >87%. The code is publicly available at https://github.com/saifalkh/FGR-Net.

Introduction: Labor pain is one of the most worrying things for future mothers. Nurses ensure the wellbeing of patients in all these aspects and it should be noted that there are various complementary options to epidural analgesia. Objective: To identify the complementary therapies that could be applied effectively and safely in pregnant women, to analyse the contributing factors of greater well-being for the parturient and to evaluate their utility. Method: This integrative review was carried out in online databases: PubMed, Scopus and Dialnet. Articles whose publication date was not more than ten years ago, written in English, Spanish or Portuguese and open access were included. Results: 16 studies about the application of different complementary therapies used safely in pregnant were included and analysed. The obtained results of the application of complementary techniques in previous studies were considered and grouped according to typology: body-mind interventions, alternative medical practice, manual healing methods, immersion in water and swiss ball, aromatherapy and auriculotherapy and transcutaneous electrical nerve stimulation. Conclusion: The variety of effective and safe complementary therapies on labour is evidenced, as well as their usefulness to reduce the possible inconveniences that may appear during this process, increasing the positive experience of labour.

This research proposes: (i) analyze push and pull motivations in insular marine protected areas, and (ii) determine their effects on tourists' satisfaction, positive recommendations and loyalty in terms of returning. The study was conducted in the Galápagos Islands in Ecuador; a renowned marine protected area with a National Park being a Natural Heritage Site of Humanity by UNESCO. An exploratory (EFA) and confirmatory factor analysis (CFA), followed by a stepwise multiple regression analysis applied on a sample of 407 tourists in the Galápagos Islands showed four push and pull motivational factors in this destination: "passive marine," "active marine," "novelty and escape," and "social relations". "Passive marine" and "social relations" were the most prominent factors influencing tourist satisfaction and return intentions. Moreover, "passive marine" and "novelty and escape " highly influenced visitors' intention to recommend and give positive feedback about this place. These findings constitute action guides for the adequate management of marine protected areas.Copyright: © 2023 Carvache-Franco et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Several studies have shown an independent relationship between body mass index (BMI) and the incidence of atrial fibrillation (AF). However, little is known about the influence of BMI on AF recurrence after electrical cardioversion (ECV).We selected 1121 patients who reverted to sinus rhythm after scheduled ECV and were included in three prospective Spanish registries of ECV in persistent AF. The patients were classified according to baseline BMI into three categories (normal weight, overweight, obesity). We assessed the influence of BMI on the rate of AF recurrence at 3 months.We identified 538 patients (48%) who had AF recurrence in the first 3 months after successful ECV. The patients who suffered AF recurrence had a higher BMI than those who remained in sinus rhythm (29.66±4.57 vs. 28.87±4.64 Kg/m2, respectively; p = 0.004). We observed a higher incidence of AF recurrence in the overweight and obese patients (BMI ≥25 kg/m2) than in those classified as normal weight (50.5% vs. 35.6%, respectively; p<0,001). BMI≥25 Kg/m2 was shown to be independently related to of AF recurrence in the multivariate analysis (OR = 1.75, 95% confidence interval = 1.20-2.58; p = 0.004).Increased BMI is independently related to AF recurrence after ECV. BMI should also be taken into account when making decisions about the indication for ECV in persistent AF.Copyright: © 2023 Ligero et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

The usability of educational research continues to be a challenge in international policies and agendas, and scientific forums. In education, the perceived mismatch between the interests of the research community and the needs of the teaching practice is wide. We aim to understand how this dichotomy influences the uses, topics of interest and ways of accessing the results of educational research processes, and put forward proposals that facilitate the use of evidence to improve practice. This is a qualitative methodology typical of a comprehensive descriptive study. Semi-structured interviews were conducted with 10 key informants (2 education policy makers, 4 school managers and 4 teachers) in the province of Tarragona (Spain). The results show that the research evidence is mostly used in planning and process management. The topics of interest are heterogeneous (mainly methodologies and educational performance). Access to research results, although varied (journals, lifelong learning, on-line resources), is hampered by excessively technical language, lack of time and low perceived applicability. The conclusion is that policies to optimize the use of research involve initial and ongoing training, the promotion of collaborative dynamics involving teachers from the initial design of the research and the establishment of agreed values by the entire educational community.

This paper examines the dynamic connectedness between Gulf countries and BRICS stocks markets with a sample of cryptocurrencies, as well as two newly developed digital assets, namely NFT and DeFi, and Gold. The period under examination spans from January 2019 until September 2022. Our analysis is based on wavelet coherence, which is a suitable methodology considering the nonlinear dynamics present in data. Our empirical results clearly identify nontrivial time-varying connectedness between different assets and the stock markets. Asymmetric patterns in the interconnections of newly developed digital assets, cryptocurrencies, Gold and emerging market indices are well-documented, especially during the advent of the health and political events. Our empirical findings have relevant implications for portfolio managers, investors and researchers about portfolio allocation, investment strategies and potential diversification benefits of NFT and DeFi digital assets.

PurposeThis study introduces a comprehensive bibliometric analysis of the foreign direct investment (FDI) literature by multinational corporations (MNCs) focusing on emerging economies to identify the most influential authors, journals and articles in FDI research and reveals the fields' conceptual and intellectual structures. The purpose of this paper is to address these issues.Design/methodology/approachThe study analyzed 533 articles published between 1974 and 2020 in 226 academic journals indexed in the Web of Science (WoS) and Scopus databases. We used the R language for statistical computing to map author collaboration, co-word and develop a conceptual and intellectual map of the field.FindingsThe results show that, although the FDI literature has many authors, few dominate the field. The International Business Review (IBR) and International Journal of Emerging Markets (IJoEM) are the main sources of the publications. Moreover, bibliometric laws show that our dataset follows the Lotka law of scientific productivity and Bradford law of scattering, identifying the core journals. Finally, FDI by MNCs in emerging economies research is divided into four sub-research themes related to (1) FDI determinants, (2) entry mode, (3) MNCs and FDI performance and (4) the internationalization process.Originality/valueThe current article provides several starting points for practitioners and researchers investigating FDI. It contributes to broadening the vision of the field and offers recommendations for future studies.

Artificial intelligence (AI) is used for various purposes that are critical to human life. However, most state-of-the-art AI algorithms are black-box models, which means that humans cannot understand how such models make decisions. To forestall an algorithm-based authoritarian society, decisions based on machine learning ought to inspire trust by being explainable. For AI explainability to be practical, it must be feasible to obtain explanations systematically and automatically. A usual methodology to explain predictions made by a (black-box) deep learning model is to build a surrogate model based on a less difficult, more understandable decision algorithm. In this work, we focus on explaining by means of model surrogates the (mis)behavior of black-box models trained via federated learning. Federated learning is a decentralized machine learning technique that aggregates partial models trained by a set of peers on their own private data to obtain a global model. Due to its decentralized nature, federated learning offers some privacy protection to the participating peers. Nonetheless, it remains vulnerable to a variety of security attacks and even to sophisticated privacy attacks. To mitigate the effects of such attacks, we turn to the causes underlying misclassification by the federated model, which may indicate manipulations of the model. Our approach is to use random forests containing decision trees of restricted depth as surrogates of the federated black-box model. Then, we leverage decision trees in the forest to compute the importance of the features involved in the wrong predictions. We have applied our method to detect security and privacy attacks that malicious peers or the model manager may orchestrate in federated learning scenarios. Empirical results show tha

BackgroundUniversity students are often affected by food insecurity (FI) and this situation has been associated with low consumption of fruit/vegetables and high intake of added sugars and sweet drinks. However, there needs to be more evidence on the association between FI and dietary patterns (DPs), assessing the overall diet and allowing analysis of commonly consumed food combinations. We aimed to analyze the association between FI and DPs in university students' households.MethodsWe used data from 7659 university student households from the 2018 Mexican National Household Income and Expenditure Survey (ENIGH, for its acronym in Spanish). We obtained FI levels (mild, moderate, and severe) using the validated Mexican Food Security Scale (EMSA, Spanish acronym). Two DPs were identified by principal component analysis based on the weekly frequency of consumption of 12 food groups. Multivariate logistic regression adjusted by university student and household's characteristics was applied.ResultsCompared to food security, households with mild-FI (OR:0.34; 95%CI:0.30, 0.40), moderate-FI (OR:0.20; 95%CI:0.16, 0.24) or severe-FI (OR:0.14; 95%CI:0.11, 0.19) were less likely to adhere to the dietary pattern "Fruits, vegetables and foods rich in animal protein" (fruits, vegetables, meat, fish or seafood, dairy products, and starchy vegetables). In addition, people with severe-FI (OR:0.51; 95% CI:0.34, 0.76) were also less likely to adhere to the dietary pattern "Traditional-Westernized" (pulses, oils or fats, sugar, sweets, industrialized drinks, foods made from corn/maize, wheat, rice, oats or bran, coffee, tea and eggs).ConclusionsIn these households FI impairs the ability to consume a healthy dietary pattern (fruits/vegetables and foods rich in animal protein). In addition, t

Objective: The aim of this work is to analyze how memorable experiences in theme parks can influence tourists' engagement in virtual social media. Methodology/approach: The sample consisted of 1,126 visitors of two theme parks in Brazil and Spain between July 2017 and May 2018. The data collection instrument was the questionnaire. For data analysis, the procedures included: Exploratory Factor Analysis (EFA), Confirmatory Factor Analysis (CFA) with the use of discriminant validity criteria and extracted mean-variance (AVE), Spearman's Correlation test, and the Bootstrapping technique. Originality/relevance: Although several studies contribute to the research of memorable experiences and consumer engagement in social media in the tourist context, few works focus on the tourist experience in theme parks. In this sense, and based on a comparative approach, such investigation is explored in an attempt to contribute to initial empirical evidence on the subject. Results: There is a positive effect of experience on virtual social media engagement in relation to the theme parks analyzed. Two constructs (attention and enthusiasm) were identified as expressive indicators of consumer engagement. The findings suggest that the more visitors engage with memorable park experiences, the more they identify with the park on virtual social media. Theoretical/methodological contributions: This work provides indicators to understand the dynamics of park visitors in countries with different cultures and customs through a new measurement tool. Social/Management Contributions: It provides support for managers to establish strategies that aim to increase the rate of engagement related to the virtual social media experience.

La usabilidad de la investigación educativa sigue siendo un desafío en las políticas, agendas internacionales, y en los foros científicos. En educación el desencuentro percibido entre los intereses de la comunidad investigadora y las necesidades del ejercicio docente es amplio. Pretendemos comprender cómo esa dicotomía influye en los usos, temáticas de interés y formas de acceso a los resultados de los procesos de indagación educativa, y plantear propuestas que faciliten la utilización de evidencias en la mejora de la práctica. Se utiliza una metodología cualitativa, con entrevistas semiestructuradas a informantes clave (responsables de políticas educativas, directivos escolares y docentes). Las evidencias de la investigación se usan, mayoritariamente, en planificación y gestión de procesos. Las temáticas de interés son heterogéneas (metodologías y funcionamiento educativo, principalmente). El acceso a los resultados de investigación, aunque variado (revistas, formación permanente, recursos on-line), está lastrado por un lenguaje excesivamente técnico, falta de tiempo y escasa aplicabilidad percibida. Se concluye que las políticas para optimizar el uso de la investigación deben promover la mejora de la formación inicial y permanente, el impulso de dinámicas colaborativas que involucren a docentes desde el diseño inicial de la investigación y el establecimiento de valores consensuados por la comunidad educativa.

We conduct an international analysis of the cross-sectional risk premiums of uncertainty risk factors in addition to traditional risk factors. We consider international stock markets in five regions separately. We measure uncertainty by the local and US economic policy uncertainty indices. Economic policy uncertainty risk has negative risk premiums. This implies that investors get lower returns for assets with high uncertainty betas. We further analyze a nonlinear relationship between excess returns and uncertainty risk by adding the downside economic policy uncertainty risk factor which captures high levels of uncertainty, similar to downside market risk. The downside uncertainty risk factor has negative risk premiums.

AI-based chatbots are an emerging technology disrupting the tourism industry. Although chatbots have received increasing attention, there is little evidence of their impact on tourists' decisions to visit a destination. This study evaluates the key attributes of chatbots and their effects on user satisfaction and visit intention. We use structural equation modeling with covariance procedures to test the proposed model and its hypotheses. The results showed that informativeness, empathy, and interactivity are critical attributes for satisfaction, which drive tourists' intention to visit a destination.Copyright: © 2023 Orden-Mejía et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Exploratory factor analysis is widely used for item analysis in the earlier stages of scale development, usually with large pools of items. In this scenario, the presence of inappropriate or ineffective items can hamper the process of analysis, making it very difficult to correctly assess dimensionality and structure. To minimize, this (quite frequent) problem, we propose and implement a simple procedure designed to flag potentially problematic items before we specify any particular factorial solution. The procedure defines regions of item appropriateness and efficiency based on the combined impact of two prior item features: extremeness and consistency. The general proposal is related to the most widely used frameworks for item analysis. The limits of the appropriateness regions are obtained by extensive simulation in conditions that mimic those found in applications. An Item Response Theory index of prior item efficiency is then defined, and a combined approach for selecting the most effective and problem-free item sub-set is proposed. The proposal is useful to normal-range measures, such as questionnaire surveys that elicit reports about non-extreme attitudes, facts, beliefs or states, or personality questionnaires that measure normal-range constructs. The procedure is implemented in a freeware software.Copyright: © 2023 Ferrando et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

La inclusión digital, entendida desde la perspectiva pedagógica, tiene como propósito mejorar los procesos de enseñanza-aprendizaje, haciéndolos, gracias al uso de las tecnologías digitales, más accesibles al conjunto del alumnado. Pero a pesar de su relevancia, podemos observar que ni la normativa académica ni los diferentes marcos especializados concretan como aplicarla en el aula. Con la intención de abordar esta problemática, se presenta un proceso de evaluación por competencias (relacionadas con la inclusión digital) llevado a cabo durante una experiencia formativa vehiculada a través de la metodología didáctica del aprendizaje-servicio, en la que participó alumnado universitario, docentes de educación infantil y primaria en ejercicio y profesorado de la Universitat Rovira i Virgili. Los resultados, que se obtuvieron mediante un cuestionario construido a partir del estándar COMDID y el análisis de las evidencias de aprendizaje proporcionadas por los/las estudiantes, muestran cómo el alumnado se sobrevalora en las autoevaluaciones, mientras que el profesorado universitario le otorga una puntuación más baja en cada uno de los cinco descriptores analizados. Como conclusión, se ha podido comprobar que los procesos de evaluación por competencias en los que participan diferentes agentes evaluadores son más complejos a la hora de ser implementados, pero se revisten de mayor objetividad al contar con diferentes puntos de vista que no serían posibles con una única mirada. Además, se ha constatado que los recursos digitales más utilizados por el alumnado para presentar sus evidencias de aprendizaje fueron los que menos dificultad revistieron al profesorado al ser evaluados, y a la inversa.

This paper explores the use of clustering models of stocks to improve both (a) the prediction of stock prices and (b) the returns of trading algorithms. We cluster stocks using k-means and several alternative distance metrics, using as features quarterly financial ratios, prices and daily returns. Then, for each cluster, we train ARIMA and LSTM forecasting models to predict the daily price of each stock in the cluster. Finally, we employ the clustering-empowered forecasting models to analyze the returns of different trading algorithms. We obtain three key results: (i) LSTM models outperform ARIMA and benchmark models, obtaining positive investment returns in several scenarios; (ii) forecasting is improved by using the additional information provided by the clustering methods, therefore selecting relevant data is an important preprocessing task in the forecasting process; (iii) using information from the whole sample of stocks deteriorates the forecasting ability of LSTM models. These results have been validated using data of 240 companies of the Russell 3000 index spanning 2017 to 2022, training and testing with different subperiods.

For some decades now, theories on learning methodologies have advocated collaborative learning due to its good results in terms of effectiveness and learning types and its promotion of educational and social values. This means that teachers need to be able to apply different criteria when forming heterogeneous groups of students and to use automated techniques to assist them. In this study, we have created an approach based on complex network theory to design an algorithm called Minimum Entropy Collaborative Groupings (MECG) in order to form these heterogeneous groups more effectively. The algorithm was tested firstly under a synthetic framework and secondly in a real situation. In the first case, we generated 30 synthetic classrooms of different sizes and compared our approach with a genetic algorithm and a random grouping. In the latter case, the approach was tested on a group of 200 students on two subjects of a master's degree in teacher training. For each subject there were 4 large groups of 50 students each, in which collaborative groups of 4 students were created. Two of these large groups were used as random groups, another group used the CHAEA test and the fourth group used the LML test. The results showed that the groups created with MECG were more effective, had less uncertainty and were more interrelated and mature. It was observed that the randomized groups did not obtain significantly better LML results and that this cannot be related to any emotional or motivational effect because the students performed the test as a placebo measure. In terms of learning styles, the results were significantly better with LML than with CHAEA, whereas no significant difference was observed in the randomized groups.Copyright: © 2023 Vallès-Català, Palau. This is an open acce

The advent of decentralised systems and the continuous collection of personal data managed by public and private entities require the application of measures to guarantee the privacy of individuals. Due to the necessity to preserve both the privacy and the utility of such data, different techniques have been proposed in the literature. Microaggregation, a family of data perturbation methods, relies on the principle of k-anonymity to aggregate personal data records. While several microaggregation heuristics exist, those based on the Travelling Salesman Problem (TSP) have been shown to outperform the state of the art when considering the trade-off between privacy protection and data utility. However, TSP-based heuristics suffer from scalability issues. Intuitively, methods that may reduce the computational time of TSP-based heuristics may incur a higher information loss. Nevertheless, in this article, we propose a method that improves the performance of TSP-based heuristics and can be used in both small and large datasets effectively. Moreover, instead of focusing only on the computational time perspective, our method can preserve and sometimes reduce the information loss resulting from the microaggregation. Extensive experiments with different benchmarks show how our method is able to outperform the current state of the art, considering the trade-off between information loss and computational time.

This paper revisits the linkage between cryptocurrencies and public disclosed preferences, proxied by online searches. We show that cryptocurrencies are not related to a general uncertainty index as measured by the Google Trends data by Castelnuovo and Tran (2017). Instead, cryptocurrencies are linked to a Google Trends attention measure specific for this market. In particular, we find a bidirectional flow of information between Google Trends attention and cryptocurrency returns up to six days. Moreover, information flows from cryptocurrency volatility to Google Trends attention seem to be larger than those in the other direction. Finally, we report a significant tail dependence between cryptocurrency returns and Google Trends. These relations hold for the five cryptocurrencies analyzed and different compositions of the proposed Google Trends Cryptocurrency index.

Las tecnologías digitales brindan numerosas oportunidades para la intervención con personas con discapacidad intelectual (DI). A pesar de ello, algunas personas con DI no pueden aprovechar su potencial y hacer uso de estas, como tecnologías de asistencia, para pedir ayuda en situaciones de emergencia. El objetivo de este trabajo es presentar el proceso de diseño y validación del contenido de una aplicación para dispositivos móviles y una página web, para facilitar la atención de las personas con DI por parte de los cuerpos de seguridad y emergencias. Su elaboración ha pasado por dos fases bien diferenciadas: revisión y análisis de la literatura científica y documental, y juicio de expertos mediante el método Delphi. En este participaron expertos (n=26) de diferentes perfiles seleccionados mediante el cálculo del coeficiente de competencia experta (Coeficiente K), quienes valoraron los productos en base a los criterios de claridad, pertinencia y satisfacción. Los resultados han sido satisfactorios y han permitido perfilar las definiciones de algunos de los apartados de la aplicación y ampliar la web, añadiendo un catálogo de pictogramas que ofrece la opción de poder personalizar los mensajes y las historias sociales que contiene, así como facilitar los procesos de comunicación y aprendizaje

We introduce non-manipulability by clones for bankruptcy problems, which entitles claimants to merge or split only when they are or become identical agents. We show that this weaker non-manipulability requirement, together with either claim monotonicity or claims continuity, allows for new characterizations of the proportional rule on the general class of bankruptcy problems.

With the aim of increasing benefits and decreasing harms, risk-based breast cancer screening has been proposed as an alternative to age-based screening. This study explores barriers and facilitators to implementing a risk-based breast cancer screening program from the perspective of health professionals, in the context of a National Health Service.Socio-constructivist qualitative research carried out in Catalonia (Spain), in the year 2019. Four discussion groups were conducted, with a total of 29 health professionals from primary care, breast cancer screening programs, hospital breast units, epidemiology units, and clinical specialties. A descriptive-interpretive thematic analysis was performed.Identified barriers included resistance to reducing the number of screening exams for low-risk women; resistance to change for health professionals; difficulties in risk communication; lack of conclusive evidence of the benefits of risk-based screening; limited economic resources; and organizational transformation. Facilitators include benefits of risk-based strategies for high and low-risk women; women's active role in their health care; proximity of women and primary care professionals; experience of health professionals in other screening programs; and greater efficiency of a risk-based screening program. Organizational and administrative changes in the health system, commitment by policy makers, training of health professionals, and educational interventions addressed to the general population will be required.Despite the expressed difficulties, participants supported the implementation of risk-based screening. They highlighted its benefits, especially for women at high risk of breast cancer and those under 50 years of age, and assumed a greater efficiency of the risk-based p

Background Cardio-vascular disease and depression are thought to be closely related, due to shared risk factors. The aim of the study was to determine the association between cardio-vascular risk (CVR) factors and depressive status in a population (55–75 years) with metabolic syndrome (MetS) from the PREDIMED-Plus trial. Methods and findings Participants were classified into three groups of CVR according to the Framingham-based REGICOR function: (1) low (LR), (2) medium (MR) or (3) high/very high (HR). The Beck Depression Inventory-II (BDI-II) was used to assess depressive symptoms at baseline and after 2 years. The association between CVR and depressive status at baseline (n = 6545), and their changes after 2 years (n = 4566) were evaluated through multivariable regression models (logistic and linear models). HR women showed higher odds of depressive status than LR [OR (95% CI) = 1.78 (1.26, 2.50)]. MR and HR participants with total cholesterol <160 mg/mL showed higher odds of depression than LR [OR (95% CI) = 1.77 (1.13, 2.77) and 2.83 (1.25, 6.42) respectively)] but those with total cholesterol ≥280 mg/mL showed lower odds of depression than LR [OR (95% CI) = 0.26 (0.07, 0.98) and 0.23 (0.05, 0.95), respectively]. All participants decreased their BDI-II score after 2 years, being the decrease smaller in MR and HR diabetic compared to LR [adjusted mean±SE = -0.52±0.20, -0.41 ±0.27 and -1.25±0.31 respectively). MR and HR participants with total cholesterol between 240–279 mg/mL showed greater decreases in the BDI-II score compared to LR (adjusted mean±SE = -0.83±0.37, -0.77±0.64 and 0.97±0.52 respectively). Conclusions Improving cardiovascular health could prevent the onset of depression in the elderly. Diabetes and total cholesterol in individuals at high CVR, may pla

El análisis del paisaje y su caracterización se realiza habitualmente bajo miradas cuantitativas, es decir, su valor se establece en relación a sus características físicas y a la potencial explotación de sus recursos.

In this paper we study tax evasion by means of a unified framework, based on a behavioral approach, where each individual decision with respect to tax compliance is driven by either personal evaluations of the available information, correlated to income and the perception of the quality of the public good, and social influences, derived by the known decision of neighbors. Our model relies on individual utility functions and describes the tax-evasion problem by means of a personal evolutionary scheme, in which each citizen dynamically adapts her behavior as a response to changing economic and social factors. We will show basic economic intuitions on the relevance of penalties, imitation, satisfaction and risk aversion by means of an analytical model and its agent-based companion version, in order to analyse different elements influencing tax evasion and their dynamic effects. In particular, it is shown how the tax-evasion probability changes as a function of the risk-aversion and specific focus is dedicated to the role played by non-monetary elements of utility in inducing high levels of tax compliance also at substantially reduced fines.

We compare the performance of various advanced forecasting techniques, namely artificial neural networks, k-nearest neighbors, logistic regression, Naive Bayes, random forest classifier, support vector machine, and extreme gradient boosting classifier to predict stock price movements based on past prices. We apply these methods with the high frequency data of 27 blue-chip stocks traded in the Istanbul Stock Exchange. Our findings reveal that among the selected methodologies, random forest and support vector machine are able to capture both future price directions and percentage changes at a satisfactory level. Moreover, consistent ranking of the methodologies across different time frequencies and train/test set partitions prove the robustness of our empirical findings.

Walking for transportation is a common and accessible means of achieving recommended physical activity levels, while providing important social and environmental co-benefits. Even though walking in rapidly growing urban areas has become especially challenging given the increasing dependence on motorised transportation, walking remains a major mode of transportation in Latin American cities. In this paper we aimed to quantify self-reported walking for transportation in Mexico City, Bogota, Santiago de Chile, Sao Paulo, and Buenos Aires, by identifying both walking trips that are conducted entirely on foot and walking events involved in trips mainly conducted on other means of transportation (e.g. private vehicle, public transit) among individuals >= 5-years old. We show how walking-only trips account for approximately 30% trips in the analysed cities, and we evidence how the pedestrian dimension of mobility is largely underestimated if walking that is incidental to other transportation modes is not accounted for: when considering all walking events, we observed an increase between 73% and 217% in daily walking time. As a result, we estimated that between 19% and 25% of residents in these cities meet the WHO physical activity guidelines solely from walking for transportation. The results of the study also suggest that the promotion of public transportation in large Latin American cities can especially help certain population groups achieve the daily recommended levels of physical activity, while among low-income groups accessibility and safety seem to be the key challenges to be addressed.

Background: The aim of this study is to evaluate the short- and long-term effects of the universal mental health literacy intervention "EspaiJove.net " in increasing mental health knowledge, help seeking and reducing stigma attitudes in the adolescent population. We also examine whether these effects depend on the intervention intensity. Methods: A clustered school-based randomised controlled trial (cRCT) design. Subjects: 1,298 secondary pupils aged 13 and 14 were recruited from 18 schools in Barcelona (Spain) between September 2016 and January 2018. Intervention: Three programmes were assessed: 1) Sensitivity Programme (SP; 1 h); 2) Mental Health Literacy (MHL; 6 h); 3) MHL plus a first-person Stigma Reduction Programme (MHL + SR; 7 h); 4) Control group (CG): waiting list. Outcome measures: 1) MHL: EspaiJove.net EMHL Test (First part and Second Part); 2) Stigma: RIBS and CAMI; 3) Help-seeking and use of treatment: GHSQ. Analysis: The data was collected at baseline, post-intervention and 6 and 12 months later. An intention-to-treat analysis and imputation method was used to analyse the missing data. Intervention effects were analysed using multilevel modelling. Results: One thousand thirty-two students were included (SP = 225; MHL = 261; MHL + SR = 295 and CG = 251). The MHL and MHL + SR interventions showed short- and long-term an increase in knowledge compared to SP and CG, but no significant change post-intervention or over time (First part p = 0.52 and Second part p = 0.62) between intervention groups and CG. No significant changes were found in stigma scores post-intervention or over time (CAMI p = 0.61 and RIBS p = 0.98) or in help-seeking scores (parent p = 0.69; teacher p = 0.23 and healthcare professional p = 0.75). The MHL + SR intervention was the best value

El objetivo de este artículo es resumir de manera objetiva el informe del Comité Científico Europeo que acaba de actualizar el algoritmo en el que se basa el logotipo nutricional Nutri-Score. Se revisa la metodología utilizada, las prioridades establecidas y sus justificaciones, y los diferentes escenarios probados, las modificaciones propuestas y su impacto en los diferentes grupos de alimentos afectados.

La presencia de hombres como demandantes de empleo en las ocupaciones de cuidados de larga duración plantea nuevos desafíos para las organizaciones que operan en el sector. Desde una perspectiva cualitativa analizamos los discursos y las prácticas de los gestores que prestan servicios de cuidados sobre la contratación de hombres, para profundizar en cómo se movilizan las masculinidades y comprobar si una mayor presencia de hombres conlleva una alteración de los requisitos de contratación en términos de género. Introducimos el concepto de (in) movilización de masculinidades para ilustrar cómo, aunque las prácticas de contratación de las organizaciones de servicios de atención movilizan concepciones idealizadas y alternativas de masculinidad, la contratación de hombres no es su prioridad. Estas prácticas ayudan a reproducir las desigualdades de género en el sector de los cuidados de larga duración.

Introducción: los trastornos de la conducta alimentaria (TCA) son un grupo de afecciones en las cuales las creencias negativas sobre la comida, la forma del cuerpo y el peso corporal se acompañan de conductas que incluyen restricción de la ingesta, atracones, realización excesiva de ejercicio, provocación del vómito y uso de laxantes. Pueden llegar a ser graves, repercutir sobre la calidad de vida y conducir a múltiples complicaciones físicas y psiquiátricas, incluso con desenlace fatal. El propósito de este artículo es describir las características, la epidemiología y las tendencias de los TCA con información actualizada a partir de las publicaciones más recientes. Métodos: se ha realizado una búsqueda sistemática de la literatura en Medline, EMBASE, Cochrane y Web of Science. Los términos de búsqueda fueron “anorexia nervosa”, “bulimia nervosa”, “binge eating disorders” and “epidemiology” en título y resumen. Resultados y conclusiones: los TCA se presentan generalmente en adolescentes y adultos jóvenes. Los mejor caracterizados son la anorexia nerviosa (AN), la bulimia nerviosa (BN) y el trastorno por atracón (TA). Los estudios de prevalencia indican amplias diferencias en función del grupo de edad y el sexo, muy superior en las mujeres jóvenes (AN: 0,1-2 %; BN: 0,37-2,98 %; TA: 0,62-4,45 %). La prevalencia de los TCA es del 2,2 % (0,2-13,1 %) en Europa, del 3,5 % (0,6-7,8 %) en Asia y del 4,6 % (2,0-13,5 %) en América. La comorbilidad es elevada con problemas psiquiátricos como la depresión, la ansiedad, el déficit de atención e hiperactividad, el trastorno obsesivo-compulsivo y los trastornos de personalidad.

Los trastornos de la alimentación son poco frecuentes en las edades de la etapa escolar, siendo predominantes en el sexo femenino. Los principales factores predictivos en esta edad son similares a los de otros grupos de edad, siendo particularmente importante la influencia de los cambios corporales, sobre todo en las niñas. Aunque los programas preventivos en este grupo de edad son escasos, los centrados principalmente en la aceptación de la imagen corporal, la internalización del ideal de apariencia y la alfabetización mediática han observado cierta eficacia. No obstante, son necesarias nuevas investigaciones que confirmen los enfoques con mejores resultados.

La evidencia científica apoya un modelo interactivo de influencias biopsicosociales en la etiología de los trastornos de la conducta alimentaria (TCA). Los nuevos estudios de asociación de genoma completo sugieren una base de desregulación metabólica en la anorexia nerviosa. Entre los factores psicológicos, la insatisfacción corporal (IC) puede considerarse el predictor más consistente, principalmente en el género femenino. Baja autoestima, afecto negativo e interiorización del ideal de delgadez determinan la IC. Ciertos rasgos de personalidad y otros factores individuales como un alto índice de masa corporal, problemas emocionales y algunas enfermedades, metabólicas y digestivas, factores sociales como algunas actividades deportivas o profesionales centradas en la presión por la figura corporal, características del entorno familiar, y presiones sociales y del grupo de pares por estar delgada, mediado actualmente por el uso/abuso de las redes sociales, actúan como condicionantes de riesgo en los TCA. La mayoría de los programas de prevención se dirigen a las mujeres adolescentes en educación secundaria y jóvenes. Son escasas las intervenciones en edades tempranas, en adultos y en varones. Los programas con buenos resultados se centran en uno o más factores de riesgo, se basan en enfoques cognitivos o conductuales e incluyen contenido sobre alimentación saludable o nutrición, alfabetización mediática o presiones socioculturales y aceptación corporal o satisfacción corporal. Incorporan nuevas tecnologías y son interactivos. Se necesitan más investigación y programas de prevención de los TCA innovadores para niños pequeños, adultos y varones.

An accurate knowledge of the relocation of prostate neoplasms during biopsy is of great importance to reduce the number of false negative results. Prostate neoplasms are visible in magnetic resonance images (MRI) but it is difficult for the practitioner to locate them at the time of performing a transrectal ultrasound (TRUS) guided biopsy. In this study, we present a new methodology, based on simulation, that predicts both prostate deformation and lesion migration during the biopsy.A three-dimensional (3-D) anatomy model of the pelvic region, based on medical images, is constructed. A finite element (FE) numerical simulation of the organs motion and deformation as a result of the pressure exerted by the TRUS probe is carried out using the Code-Aster open-source computer software. Initial positions of potential prostate lesions prior to biopsy are taken into consideration and the final location of each lesion is targeted in the FE simulation output.Our 3-D FE simulations show that the effect of the pressure exerted by the TRUS probe is twofold as the prostate experiences both a motion and a deformation of its original shape. We targeted the relocation of five small prostate lesions when the TRUS probe exerts a force of 30 N on the rectum inner wall. The distance travelled by these lesions ranged between 5.6 and 13.9 mm.Our new methodology can help to predict the location of neoplasms during a prostate biopsy but further studies are needed to validate our results. Moreover, the new methodology is completely developed on open-source software, which means that its implementation would be affordable to all healthcare providers.© 2022. The Author(s).

Cryptocurrency history begins in 2008 as a means of payment proposal. However, cryptocurrencies evolved into a complex ecosystem of high yield speculative assets. Contrary to traditional financial instruments, they are not (mostly) traded in organized, law-abiding venues, but on online platforms, where anonymity reigns. This paper examines the long term memory in return and volatility, using high frequency time series of seven important coins. Our study covers the pre-Covid-19 and the subsequent pandemic period. We use a recently developed method, based on the wavelet transform, which provides more robust estimators of the Hurst exponent. We detect that, during the peak of Covid-19 pandemic (around March 2020), the long memory of returns was only mildly affected. However, volatility suffered a temporary impact in its long range correlation structure. Our results could be of interest for both academics and practitioners.

© 2017 Springer Science+Business Media, LLC This paper considers the problem of finding suitable sites for wind farms in a region of Catalonia (Spain). The evaluation criteria are structured into a hierarchy that identifies several intermediate sub-goals dealing with different points of view. Therefore, the recent ELECTRE-III-H hierarchical multi-criteria analysis method is proposed as a good solution to help decision-makers. This method establishes an order among the set of possible sites for the wind farms for each sub-goal. ELECTRE-III-H aggregates these orders into an overall order using different parameters. The procedure is based on the construction and exploitation of a pairwise outranking relation, following the principles of concordance (i.e. majority rule) and discordance (i.e. respect for the minority opinions). This paper makes two main contributions. First, it contributes to the ELECTRE-III-H method by studying its mathematical properties for the construction of outranking relations. Second, the case study is solved and its results show that we can effectively represent and manage the overall influence of the various criteria on the global result at different levels of the hierarchy. The paper compares different scenarios with strict, normal, and optimistic preference, indifference and veto thresholds. Results show that the best site differs for technical, economic, environmental, and social intermediate criteria. Therefore, the best overall solution changes depending on the preference and veto thresholds fixed at the intermediate level of the hierarchy.

This article examines the extent to which the 2008 economic crisis has led to a shift in ways of eating among people living in precarious conditions in Spain, and the kinds of strategies they have developed to obtain daily food. Building on a literature review on precarisation in Spain and an analysis of action plans to combat food insecurity, participant-observation ethnography was carried out in Catalonia. Fieldwork was conducted during 2017–2019 in public and private spaces focusing on the food practices of 51 first-time applicants for social assistance. Qualitative data obtained from interviews and direct observation were recorded, transcribed and coded using the ATLAS-ti program to facilitate thematic analysis. Study participants’ oral narratives reveal substantial changes in food procurement and eating practices. Strategies include buying different foods, shopping less often and/or in different stores, seeking out cheaper brands, preparing simpler dishes, growing food and recycling leftovers. Their food itineraries reflect increasing reliance on charities, although a common alternative is meals prepared outside the home by family, neighbourhood, activist organisations or themselves. Eating patterns reveal not only experiences of food deprivation and social suffering, but also alternative ways of food procurement. Although food aid is based mainly on an assistance-oriented model, participatory initiatives have the potential to become political spaces that invite us to rethink the distribution of food resources and the limitations of social policies.

Long bone breakage for bone marrow recovery is a commonly observed practice in Middle Palaeolithic contexts, regardless of the climatic conditions. While lithic technology is largely used to define cultural patterns in human groups, despite dedicating research by zooarchaeologists, for now butchering techniques rarely allowed the identification of clear traditions, notably for ancient Palaeolithic periods. In this paper, we test the hypothesis of butchery traditions among Neandertal groupsusing the bone assemblages from three sites in southwestern Europe. These sites are located in southeastern France and northern Italy and are dated to the Late Middle Palaeolithic: Abri du Maras (Marine Isotopic Stages (MIS) 4-3, Ardèche), Saint-Marcel (MIS 3, Ardèche), and Riparo Tagliente (MIS 4-3, Verona). The detection of culturally-induced patterns of bone breakage involves differentiating them from intuitively generated patterns. To tackle this issue, we used a zooarchaeological approach focusing on the percussion marks produced during the bone breakage process. Statistical analyses as the chi-square test of independence were employed to verify if percussion mark locations were randomly distributed, and if these distributions were different from the intuitive ones. For femurs and humeri, our results demonstrate that Neandertal groups occupying the Abri du Maras (levels 4.1 and 4.2) and the Saint-Marcel Cave (levels g and h) sites in France applied butchery traditions to recover yellow marrow. However, the traditions developed at each site were different. On the contrary, in Riparo Tagliente, in Italy, several groups or individuals of a same group did not share the same butchery traditions over time. Regarding the Abri du Maras and Saint Marcel Cave assemblages, our research demon

Drawing on observation-based ethnography, interviews of health personnel and document review, this article describes and examines how, in clinical handling of Chagas disease, infection is treated as latent risk. It suggests that how this risk is managed has enabled a clinical practice to be conducted among people classified as at the indeterminate stage, by adding a dimension of possibility (Is it going to happen?) and potentiality (When and where?). This allows measures to be taken, including administration of medication or permanent monitoring. The reification of latent risk as a phenomenon that is manageable through a process of medicalisation engages, in turn, with other conceptions and specific experiences of risk among the affected groups. Framing the clinical practices deployed to address this risk as objects of study is a first step towards being able to describe and include them concretely in health system organisation.

Objective Novel foods and dietary practices, a lack of available land, and displacement by armed conflict have affected the ancestral food traditions practiced by the Inga community in Aponte, in Narino, Colombia. These factors have led to problems with food security and malnutrition, which have impacted the growth and development of children. Therefore, this study is aimed at identifying the changes in ancestral food practices reported by Inga grandmothers, and the possibility of recuperating them in order to improve children's health. Method A qualitative study was conducted that included 24 mothers with children under five years old and 25 grandmothers in nine Inga communities. Participants were recruited using snowball sampling. Free listing was used to identify changes in food patterns, and semi-structured interviews were conducted with 20 grandmothers to delve deeper into the subject. A translator of the Inga language facilitated communication, and the Inga researcher validated the translation using audio recordings. Each interview was transcribed and categorized for the purpose of analysis, using the NVivo 12 software. Results Free lists showed changes from a corn-based to a rice-based diet and a wide variety of non-ancestral food products. According to the grandmothers, "tiendas" have replaced traditional foods with those that are easy to prepare, which are attractive to mothers as well as to the children because of their flavor. Ancestral practices such as grinding, peeling, and log cooking are being abandoned. Government programs and daycare have incorporated new food that compete with traditional ones, with no clear evidence of an intercultural approach. Added to this is the dismissal by young mothers of the knowledge held by their grandmothers, which hinders

Ethical sensitivity is a requirement for people care as well as for decision-making in everyday practice. The aim is to present an adaptation and transcultural validation -in Spanish- of the Moral Sensitivity Questionnaire by Lützén et al. in Spain. In addition to that, we provide a practical implementation analysing the degree of moral sensitivity of nursing students. The data used for data collection were moral Sensitivity Questionnaire, socio-demographic data and a self-report questionnaire. The psychometric properties of the questionnaire were assessed, including validity and reliability. Fit indices of the overall model were computed. The fit indices of the Confirmatory Factor Analysis (CFA) indicate a poor fit, although the Exploratory Factor Analysis (EFA) revealed two dimensions that show a better fit of its indices. Women and those women with more experience in the clinical setting have a higher mean score, as well as those who study in centers where the strategic lines are the humanization of care. Female nursing students with more experience in the clinical setting and with more educational training present higher sensitivity indexes, as well as those who study in centers where the strategic lines are the humanization of care. The findings confirm that the Lützén et al. questionnaire is multidimensional. In the Spanish sample, it was necessary to group the three initial factors into two: sense of moral burden and moral strength-grouping the moral responsibility items into the above items to make the instrument more resilient.

Clinical simulation as a teaching methodology allows the student to train and learn technical abilities and/or non-technical abilities. One of the key elements of this teaching methodology is the debriefing, which consists of a conversation between several people, in which the participants go over a real or simulated event in order to analyze their actions and reflect on the role that thought processes, psychomotor skills and emotional states can play in maintaining, or improving their performance in the future. The Debriefing Experience Scale allows the experience of students in debriefing to be measured. The objective of this study is to translate the Debriefing Experience Scale (DES) into Spanish and analyze its reliability and validity to measure the experience of nursing students during the debriefing. The study was developed in two phases: One: the adaption of the instrument to Spanish, two: a transversal study carried out in a sample of 290 nursing students. The psychometric properties were analyzed in terms of reliability and construct validity using confirmatory factorial analysis (CFA). Cronbach’s alpha was adequate for all the scales and for each one of the dimensions. The confirmatory factorial analysis showed that the 4-dimensional model is acceptable for both scales (experience and opinion). The Spanish version Debriefing Experience Scale questionnaire is useful, valid and reliable for use to measure the debriefing experience of university students in a simulation activity.

© 2020 Informa UK Limited, trading as Taylor & Francis Group. This paper examines the ongoing transition of Venice towards a short-term city, posited as an urban form which accommodates the dwelling practices of temporary populations as tourists, at the expenses of a stable resident population. This shift is approached through the conceptual framework of resilience, which is also explored in its political and discursive dimensions. At the base of the emergence of a short-term city, we analyse the redistributive impacts of short-term rentals mediated by digital platforms and their influence on the housing market, but also the related entrenchments of a local policy agenda supporting the resilience of the industry itself above that of the city as a living organism. After illustrating the development of the hospitality sector in the city fabric over the last four decades and presenting the historical challenges that Venice has been facing in regard to its capacity to retain a stable population, we seek to unravel the debate on ‘the future of Venice’, which confronts local and global agents defending a ‘conservationist’ approach for Venice as an ineluctably tourist city, with social actors who claim for the defence of residence–and therefore for a ban on STR–as a necessary condition for a socially resilient alternative.

European cities have experienced an intense growth in tourism and other related mobilities. This pressure on urban centers has increased the public's perception of the need to design more sustainable tourism policies that deal with the various associated dilemmas. This article compares the tourism policies of eleven European cities considering what governments have introduced, or avoided, in their tourism policy documents. The objective is to observe the extent to which these actions directly related to sustainability are being incorporated. The results indicate that local tourism policies are moving away from a model of public action based only on considering the economic impact of tourism and are starting to work with a wider range of associated impacts. In this scenario, the ideas of balance and sustainability find a much clearer accommodation. This research presents a pre-crisis tourism framework that can be challenged during post--Covid19 transitions.

Purpose The aim of this study was to analyze the internal structure of the EORTC QLQ-C30, to examine the validity and normative data for cancer patients. Method Exploratory and Confirmatory factor analyses were conducted to explore the scale's dimensionality and test for strong measurement invariance across sex and tumor site. All the analyses were based on a multicenter cohort of 931 patients who completed the Brief Symptom Inventory (BSI-18) and the EORTC QLQ-C30. Results Our findings indicate that the EORTC QLQ-C30 has acceptable psychometric properties and an internal structure that is well accounted for a bifactor model: a general factor that evaluates quality of life and a group factor that would analyze physical health that would be defined by physical function, role function, and fatigue. The result of the multi-group CFA revealed a strong invariance according to sex, tumor, and over time. Reliability of the EORTC exceeding 0.86 and the simple sum of the items of the scale was a good indicator of oncology patients' quality of life. Both factors correlate closely with depression, anxiety, and psychological distress and are sensitive to change, especially the quality of life, with a significant decrease in the post-test. Conclusion The Spanish version of the EORTC QLQ-C30 proved to be a valid, reliable instrument to appraise quality of life in cancer patients. The normative data collected from this study may be useful for the early detection of initial symptoms of deterioration of quality of life in oncology patients.

Several studies in different countries have reported that part of the population does not fully comply with the measures recommended to prevent COVID-19, and therefore poses a risk to public health. For this reason, several measures have been developed to assess the level of compliance, although many of them have methodological limitations or do not include a comprehensive set of items. The main goal of the current study was to develop a new instrument with suitable psychometric properties, which includes a more complete set of items and controls the impact of acquiescence bias. The participants were 1410 individuals (59.2% women) from Spain, who answered the new questionnaire and several items on sociodemographic and attitudinal issues. Exploratory and confirmatory factor analyses were carried out, and the results suggested that only one content factor was underlying the data. This solution was replicated in a different subsample, which shows the stability of the solution. Furthermore, the relationships between the scores of the new questionnaire and the sociodemographic and attitudinal variables are similar to those obtained in previous studies, which can be regarded as evidence of the validity of the new questionnaire.

This article describes the main models for embedding research and the successful experiences and challenges faced in joint work by researchers and decisionmakers who participated in the Embedding Research for the Sustainable Development Goals (ER-SDG) initiative, and the experience of the Technical Support Center. In June 2018, funding was granted to 13 pre-selected research projects from 11 middle- and low-income countries in Latin America and the Caribbean (Argentina, Bolivia, Brazil, Colombia, Dominican Republic, Ecuador, Guatemala, Guyana, Haiti, Paraguay, and Peru). The projects focused on the system-, policy-, or program-level changes required to improve health and build on the joint work of researchers and decisionmakers, with a view to bringing together evidence production and decision-making in health systems and services. The Technical Support Center supported and guided the production of quality results useful for decision-making. This experience confirmed the value of initiatives such as ER-SDG in consolidating bridges between research on the implementation of health policies, programs, and systems, and the officials responsible for operating health-related programs, services, and interventions. It highlighted the importance of both respecting and taking advantage of each context-and the specific arrangements and patterns in the relationships between researchers and decisionmakers-through incentives for embedded research.