A case study of university student networks and the COVID-19 pandemic using a social network analysis approach in halls of residence.

The COVID-19 pandemic has meant that young university students have had to adapt their learning and have a reduced relational context. Adversity contexts build models of human behaviour based on relationships. However, there is a lack of studies that analyse the behaviour of university students based on their social structure in the context of a pandemic. This information could be useful in making decisions on how to plan collective responses to adversities. The Social Network Analysis (SNA) method has been chosen to address this structural perspective. The aim of our research is to describe the structural behaviour of students in university residences during the COVID-19 pandemic with a more in-depth analysis of student leaders. A descriptive cross-sectional study was carried out at one Spanish Public University, León, from 23th October 2020 to 20th November 2020. The participation was of 93 students, from four halls of residence. The data were collected from a database created specifically at the university to "track" contacts in the COVID-19 pandemic, SiVeUle. We applied the SNA for the analysis of the data. The leadership on the university residence was measured using centrality measures. The top leaders were analyzed using the Egonetwork and an assessment of the key players. Students with higher social reputations experience higher levels of pandemic contagion in relation to COVID-19 infection. The results were statistically significant between the centrality in the network and the results of the COVID-19 infection. The most leading students showed a high degree of Betweenness, and three students had the key player structure in the network. Networking behaviour of university students in halls of residence could be related to contagion in the COVID-19 pandemic. This could be described on the basis of aspects of similarities between students, and even leaders connecting the cohabitation sub-networks. In this context, Social Network Analysis could be considered as a methodological approach for future network studies in health emergency contexts.

Diabetes detection using deep learning techniques with oversampling and feature augmentation.

BACKGROUND AND OBJECTIVE: Diabetes is a chronic pathology which is affecting more and more people over the years. It gives rise to a large number of deaths each year. Furthermore, many people living with the disease do not realize the seriousness of their health status early enough. Late diagnosis brings about numerous health problems and a large number of deaths each year so the development of methods for the early diagnosis of this pathology is essential. METHODS: In this paper, a pipeline based on deep learning techniques is proposed to predict diabetic people. It includes data augmentation using a variational autoencoder (VAE), feature augmentation using an sparse autoencoder (SAE) and a convolutional neural network for classification. Pima Indians Diabetes Database, which takes into account information on the patients such as the number of pregnancies, glucose or insulin level, blood pressure or age, has been evaluated. RESULTS: A 92.31% of accuracy was obtained when CNN classifier is trained jointly the SAE for featuring augmentation over a well balanced dataset. This means an increment of 3.17% of accuracy with respect the state-of-the-art. CONCLUSIONS: Using a full deep learning pipeline for data preprocessing and classification has demonstrate to be very promising in the diabetes detection field outperforming the state-of-the-art proposals.

eHealth Intervention to Improve Health Habits in the Adolescent Population: Mixed Methods Study.

BACKGROUND: Technology has provided a new way of life for the adolescent population. Indeed, strategies aimed at improving health-related behaviors through digital platforms can offer promising results. However, since it has been shown that peers are capable of modifying behaviors related to food and physical exercise, it is important to study whether digital interventions based on peer influence are capable of improving the weight status of adolescents. OBJECTIVE: The purpose of this study was to assess the effectiveness of an eHealth app in an adolescent population in terms of improvements in their age- and sex-adjusted BMI percentiles. Other goals of the study were to examine the social relationships of adolescents pre- and postintervention, and to identify the group leaders and study their profiles, eating and physical activity habits, and use of the web app. METHODS: The BMI percentiles were calculated in accordance with the reference guidelines of the World Health Organization. Participants' diets and levels of physical activity were assessed using the Mediterranean Diet Quality Index (KIDMED) questionnaire and the Physical Activity Questionnaire for Adolescents (PAQ-A), respectively. The variables related to social networks were analyzed using the social network analysis (SNA) methodology. In this respect, peer relationships that were considered reciprocal friendships were used to compute the "degree" measure, which was used as an indicative parameter of centrality. RESULTS: The sample population comprised 210 individuals in the intervention group (IG) and 91 individuals in the control group (CG). A participation rate of 60.1% (301/501) was obtained. After checking for homogeneity between the IG and the CG, it was found that adolescents in the IG at BMI percentiles both below and above the 50th percentile (P50) modified their BMI to approach this reference value (with a significance of P<.001 among individuals with an initial BMI below the P50 and P=.04 for those with an initial BMI above the P50). The diet was also improved in the IG compared with the CG (P<.001). After verifying that the social network had increased postintervention, it was seen that the group leaders (according to the degree SNA measure) were also leaders in physical activity performed (P=.002) and use of the app. CONCLUSIONS: The eHealth app was able to modify behaviors related to P50 compliance and exert a positive influence in relation to diet and physical exercise. Digital interventions in the adolescent population, based on the improvement in behaviors related to healthy habits and optimizing the social network, can offer promising results that help in the fight against obesity.

Evaluation of Country Dietary Habits Using Machine Learning Techniques in Relation to Deaths from COVID-19.

COVID-19 disease has affected almost every country in the world. The large number of infected people and the different mortality rates between countries has given rise to many hypotheses about the key points that make the virus so lethal in some places. In this study, the eating habits of 170 countries were evaluated in order to find correlations between these habits and mortality rates caused by COVID-19 using machine learning techniques that group the countries together according to the different distribution of fat, energy, and protein across 23 different types of food, as well as the amount ingested in kilograms. Results shown how obesity and the high consumption of fats appear in countries with the highest death rates, whereas countries with a lower rate have a higher level of cereal consumption accompanied by a lower total average intake of kilocalories.

Detecting Respiratory Pathologies Using Convolutional Neural Networks and Variational Autoencoders for Unbalancing Data.

The aim of this paper was the detection of pathologies through respiratory sounds. The ICBHI (International Conference on Biomedical and Health Informatics) Benchmark was used. This dataset is composed of 920 sounds of which 810 are of chronic diseases, 75 of non-chronic diseases and only 35 of healthy individuals. As more than 88% of the samples of the dataset are from the same class (Chronic), the use of a Variational Convolutional Autoencoder was proposed to generate new labeled data and other well known oversampling techniques after determining that the dataset classes are unbalanced. Once the preprocessing step was carried out, a Convolutional Neural Network (CNN) was used to classify the respiratory sounds into healthy, chronic, and non-chronic disease. In addition, we carried out a more challenging classification trying to distinguish between the different types of pathologies or healthy: URTI, COPD, Bronchiectasis, Pneumonia, and Bronchiolitis. We achieved results up to 0.993 F-Score in the three-label classification and 0.990 F-Score in the more challenging six-class classification.

A Semantic Social Network Analysis Tool for Sensitivity Analysis and What-If Scenario Testing in Alcohol Consumption Studies.

Social Network Analysis (SNA) is a set of techniques developed in the field of social and behavioral sciences research, in order to characterize and study the social relationships that are established among a set of individuals. When building a social network for performing an SNA analysis, an initial process of data gathering is achieved in order to extract the characteristics of the individuals and their relationships. This is usually done by completing a questionnaire containing different types of questions that will be later used to obtain the SNA measures needed to perform the study. There are, then, a great number of different possible network-generating questions and also many possibilities for mapping the responses to the corresponding characteristics and relationships. Many variations may be introduced into these questions (the way they are posed, the weights given to each of the responses, etc.) that may have an effect on the resulting networks. All these different variations are difficult to achieve manually, because the process is time-consuming and error-prone. The tool described in this paper uses semantic knowledge representation techniques in order to facilitate this kind of sensitivity studies. The base of the tool is a conceptual structure, called "ontology" that is able to represent the different concepts and their definitions. The tool is compared to other similar ones, and the advantages of the approach are highlighted, giving some particular examples from an ongoing SNA study about alcohol consumption habits in adolescents.

Socioeconomic Status in Adolescents: A Study of Its Relationship with Overweight and Obesity and Influence on Social Network Configuration.

Socioeconomic status (SES) influences all the determinants of health, conditioning health throughout life. The aim of the present study was to explore the relationship between socioeconomic status and obesity in adolescence through an analysis of the patterns of contact between peers as a function of this parameter. A cross-sectional study was performed, analyzing a sample of 235 students aged 14 to 18 and 11 class networks. Social network analysis was used to analyze structural variables of centrality from a sociocentric perspective. We found that adolescents with a medium-low SES presented a two-fold higher probability of being overweight, but we did not detect any differences in the configuration of their social networks when compared with those of normal-weight adolescents. However, we did find significant differences in the formation of networks according to SES in the overall sample and disaggregated by gender, whereby adolescents with a high SES in general presented a higher capacity to form wider social networks. Elucidating the relationship between SES and overweight and its influence on social network formation can contribute to the design of preventative strategies against overweight and obesity in adolescents, since their social environment can provide them with several resources to combat excess weight.

A Web-Based Tool for Automatic Data Collection, Curation, and Visualization of Complex Healthcare Survey Studies including Social Network Analysis.

There is a great concern nowadays regarding alcohol consumption and drug abuse, especially in young people. Analyzing the social environment where these adolescents are immersed, as well as a series of measures determining the alcohol abuse risk or personal situation and perception using a number of questionnaires like AUDIT, FAS, KIDSCREEN, and others, it is possible to gain insight into the current situation of a given individual regarding his/her consumption behavior. But this analysis, in order to be achieved, requires the use of tools that can ease the process of questionnaire creation, data gathering, curation and representation, and later analysis and visualization to the user. This research presents the design and construction of a web-based platform able to facilitate each of the mentioned processes by integrating the different phases into an intuitive system with a graphical user interface that hides the complexity underlying each of the questionnaires and techniques used and presenting the results in a flexible and visual way, avoiding any manual handling of data during the process. Advantages of this approach are shown and compared to the previous situation where some of the tasks were accomplished by time consuming and error prone manipulations of data.

A Qualitative Study of Secondary School Teachers' Perception of Social Network Analysis Metrics in the Context of Alcohol Consumption among Adolescents.

Adolescence is a transitional period during which a number of changes occur. Social relationships established during this period influence adolescent behaviour and affect academic performance or alcohol consumption habits, among other issues. Teachers are very important actors in observing and guiding the evolution of their students, and should therefore have the appropriate knowledge and tools to gain insight into the complex social relationships that exist in their classes. The use of social network analysis (SNA) techniques may be helpful in order to study and monitor the evolution of these social networks. This study tries to understand how teachers perceive SNA metrics from an intuitive point of view. Using this information, useful tools could be created that allow teachers to use SNA techniques to improve their understanding of student relationships. A number of interviews with different teachers were held in secondary schools in Spain, allowing SNA concepts to be related to the everyday terms used by the teachers to characterize their students. Results from the study have an impact on questionnaire design for gathering data from students in order to perform an SNA analysis and on the design of software applications that can help teachers to understand the results of this analysis.

BaeSR, involved in envelope stress response, protects against lysogenic conversion by Shiga toxin 2-encoding phages.

Infection and lysogenic conversion with Shiga toxin-encoding bacteriophages (Stx phages) drive the emergence of new Shiga toxin-producing Escherichia coli strains. Phage attachment to the bacterial surface is the first stage of phage infection. Envelope perturbation causes activation of envelope stress responses in bacterial cells. Although many external factors are known to activate envelope stress responses, the role of these responses in the phage-bacterium interaction remains unexplored. Here, we investigate the link between three envelope signaling systems in E. coli (RcsBC, CpxAR, and BaeSR) and Stx2 phage infection by determining the success of bacterial lysogenic conversion. For this purpose, E. coli DH5α wild-type (WT) and mutant strains lacking RcsBC, CpxAR, or BaeSR signaling systems were incubated with a recombinant Stx2 phage (933W). Notably, the number of lysogens obtained with the BaeSR mutant was 5 log10 units higher than with the WT, and the same differences were observed when using 7 different Stx2 phages. To assess whether the membrane receptor used by Stx phages, BamA, was involved in the differences observed, bamA gene expression was monitored by reverse transcription-quantitative PCR (RT-qPCR) in all host strains. A 4-fold-higher bamA expression level was observed in the BaeSR mutant than in the WT strain, suggesting that differential expression of the receptor used by Stx phages accounted for the increase in the number of lysogenization events. Establishing the link between the role of stress responses and phage infection has important implications for understanding the factors affecting lysogenic conversion, which drives the emergence of new pathogenic clones.

The impact of economic activity in Asturias on greenhouse gas emissions: consequences for environmental policy within the Kyoto Protocol framework.

Climate change is one of the major worldwide environmental concerns. It is especially the case in many developed countries, where the greenhouse gas emissions responsible for this change are mainly concentrated. For the first time, the Kyoto Protocol includes an international agreement for the reduction of the net emissions of these gases. To fulfil this agreement measures designed to reduce or limit current emissions have to be brought into force. Consequently, fears have arisen about possible consequences on competitiveness and future development of manufacturing activities and the need for support mechanisms for the affected sectors is obvious. In this paper, we carry out a study of the emissions of gases responsible for climate change in Asturias (Spain), a region with an important economic presence of sectors with intensive emissions of CO(2), the chief greenhouse gas. To be precise, in the first place, the volumes of direct emissions of the said gases in 1995 were calculated, showing that the sectors most affected by the Kyoto Protocol in Asturias are iron and steel and electricity production. Secondly, input-output analysis was applied to determine the direct and indirect emissions and the direct, indirect and induced emissions of the different production sectors, respectively. The results derived from the direct and indirect emissions analysis and their comparison with the results of the former allow us to reach some conclusions and environmental policy implications.

Herbal remedies in a Nicaraguan barrio.

To become more culturally competent, nurses need to increase their knowledge of the health practices of their immigrant clients. With the growing Latino immigrant community, it is imperative that nurses learn more about the cultures from which the immigrants come. This article examines the use of herbal remedies in treating common illnesses in a barrio in Managua, Nicaragua. Data were collected in a random sample of households in an impoverished community of more than 1,600 persons. The use of herbal remedies occurred in 78% of the households. Herbal remedies were used for a variety of symptoms. There was no difference in herbal remedy use based on age or education. The discussion focuses on the availability and functionality of these herbal remedies for this vulnerable population. Implications are addressed for incorporating this information into nursing practice with Central American immigrants, thereby increasing cultural competence.

Efecto de la administración semanal de ácido fólico sobre los valores sanguíneos / The effect of weekly administration of folic acid on folic acid blood levels

Objetivo. Evaluar el efecto de la administración de 5 mg por semana de ácido fólico sobre los valores sanguíneos. Material y métodos. Estudio de comparación concurrente realizado en zonas urbanas y rurales del estado de Nuevo León, México, en 1998, a 74 mujeres, 39 de ellas con antecedente de un producto con defecto de cierre del tubo neural y 35 sin dicho antecedente. La muestra sólo incluyó a mujeres que parieron durante 1997. Las mujeres recibieron 5 mg de ácido fólico por semana durante tres meses. El AF sanguíneo fue determinado por radioinmunoanálisis (RIA), al inicio y una semana después de la última tableta. Se calcularon promedios y desviaciones estándar. Resultados. El 90 por ciento de las mujeres aumentó significativamente los valores sanguíneos. El ácido fólico intraeritrocitario se incrementó de 150.49 ñ 31.17 ng/ml a 184.21 ñ 35.53 ng/ml (p<0.005) y el plasmático de 5.93 ñ 1.98 ng/ml a 7.03 ñ 2.5 ng/ml (p<0.05). El 82 por ciento alcanzó cifras mayores de 160 ng/ml. Conclusiones. La administración semanal de 5 mg de ácido fólico puede ser una estrategia adecuada y costo eficiente para la suplementación con esta vitamina a la población de escasos recursos. El texto completo en inglés de este artículo está disponible en: http://www.insp.mx/salud/index.html