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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.
José Alberto Benítez-Andrades; Tania Fernández-Villa; Carmen Benavides; Andrea Gayubo-Serrenes; Vicente Martín; Pilar Marqués-Sánchez. A case study of university student networks and the COVID-19 pandemic using a social network analysis approach in halls of residence. Scientific Reports 2021, 11, 14877 .
AMA StyleJosé Alberto Benítez-Andrades, Tania Fernández-Villa, Carmen Benavides, Andrea Gayubo-Serrenes, Vicente Martín, Pilar Marqués-Sánchez. A case study of university student networks and the COVID-19 pandemic using a social network analysis approach in halls of residence. Scientific Reports. 2021; 11 (1):14877.
Chicago/Turabian StyleJosé Alberto Benítez-Andrades; Tania Fernández-Villa; Carmen Benavides; Andrea Gayubo-Serrenes; Vicente Martín; Pilar Marqués-Sánchez. 2021. "A case study of university student networks and the COVID-19 pandemic using a social network analysis approach in halls of residence." Scientific Reports 11, no. 1: 14877.
In this work, a sentiment analysis method that is capable of accepting audio of any length, without being fixed a priori, is proposed. Mel spectrogram and Mel Frequency Cepstral Coefficients are used as audio description methods and a Fully Convolutional Neural Network architecture is proposed as a classifier. The results have been validated using three well known datasets: EMODB, RAVDESS and TESS. The results obtained were promising, outperforming the state-of–the-art methods. Also, thanks to the fact that the proposed method admits audios of any size, it allows a sentiment analysis to be made in near real time, which is very interesting for a wide range of fields such as call centers, medical consultations or financial brokers.
María Teresa García-Ordás; Héctor Alaiz-Moretón; José Alberto Benítez-Andrades; Isaías García-Rodríguez; Oscar García-Olalla; Carmen Benavides. Sentiment analysis in non-fixed length audios using a Fully Convolutional Neural Network. Biomedical Signal Processing and Control 2021, 69, 102946 .
AMA StyleMaría Teresa García-Ordás, Héctor Alaiz-Moretón, José Alberto Benítez-Andrades, Isaías García-Rodríguez, Oscar García-Olalla, Carmen Benavides. Sentiment analysis in non-fixed length audios using a Fully Convolutional Neural Network. Biomedical Signal Processing and Control. 2021; 69 ():102946.
Chicago/Turabian StyleMaría Teresa García-Ordás; Héctor Alaiz-Moretón; José Alberto Benítez-Andrades; Isaías García-Rodríguez; Oscar García-Olalla; Carmen Benavides. 2021. "Sentiment analysis in non-fixed length audios using a Fully Convolutional Neural Network." Biomedical Signal Processing and Control 69, no. : 102946.
José Alberto Benítez Andrades. Peer Review of “Machine Learning for Risk Group Identification and User Data Collection in a Herpes Simplex Virus Patient Registry: Algorithm Development and Validation Study”. JMIRx Med 2021, 2, e28922 .
AMA StyleJosé Alberto Benítez Andrades. Peer Review of “Machine Learning for Risk Group Identification and User Data Collection in a Herpes Simplex Virus Patient Registry: Algorithm Development and Validation Study”. JMIRx Med. 2021; 2 (2):e28922.
Chicago/Turabian StyleJosé Alberto Benítez Andrades. 2021. "Peer Review of “Machine Learning for Risk Group Identification and User Data Collection in a Herpes Simplex Virus Patient Registry: Algorithm Development and Validation Study”." JMIRx Med 2, no. 2: e28922.
Industry 4.0 significantly improves productivity by collecting and analyzing data in real time. This, combined with remote access functions, and cloud processing that allows Internet of Things IoT, provides information that optimizes processes and decision support. Also involves a great growth of new networks and systems with special features, which mean that they are vulnerable to different attacks. So new security requirements are emerging in the IoT network. To improve the security of an IoT system for a transparent way, it is proposed the development of a prototype intrusion detection system IDS, which detects anomalies in IoT environments using the MQTT protocol (Message Queuing Telemetry Transport), widely used in IoT systems. For this purpose, it is generated a dataset of an IoT system in which perform different attacks on the MQTT protocol. This dataset is used to train a machine learning model, which is implemented in the IDS that captures the network frames in real time from the system to classify and detect the different attacks. Keywords: IoT, industry 4.0, cybersecurity, IDS, MQTT protocol, Machine Learning.
Jose Aveleira Mata; Angel Luis Muñoz Castañeda; María Teresa García Ordás; Carmen Benavides Cuellar; José Alberto Benítez Andrades; Hector Alaiz Moreton. IDS PROTOTYPE FOR INTRUSION DETECTION WITH MACHINE LEARNING MODELS IN IOT SYSTEMS OF THE INDUSTRY 4.0. DYNA 2021, 96, 270 -275.
AMA StyleJose Aveleira Mata, Angel Luis Muñoz Castañeda, María Teresa García Ordás, Carmen Benavides Cuellar, José Alberto Benítez Andrades, Hector Alaiz Moreton. IDS PROTOTYPE FOR INTRUSION DETECTION WITH MACHINE LEARNING MODELS IN IOT SYSTEMS OF THE INDUSTRY 4.0. DYNA. 2021; 96 (3):270-275.
Chicago/Turabian StyleJose Aveleira Mata; Angel Luis Muñoz Castañeda; María Teresa García Ordás; Carmen Benavides Cuellar; José Alberto Benítez Andrades; Hector Alaiz Moreton. 2021. "IDS PROTOTYPE FOR INTRUSION DETECTION WITH MACHINE LEARNING MODELS IN IOT SYSTEMS OF THE INDUSTRY 4.0." DYNA 96, no. 3: 270-275.
The increasing number of connected devices and the complexity of Internet of Things (IoT) ecosystems are demanding new architectures for managing and securing these networked environments. Intrusion Detection Systems (IDS) are security solutions that help to detect and mitigate the threats that IoT systems face, but there is a need for new IDS strategies and architectures. This paper describes a development environment that allows the programming and debugging of distributed, rule-based multi-agent IDS solutions. The proposed solution consists in the integration of a rule engine into the agent, the use of a specialized, wrapping agent class with a graphical user interface for programming and debugging purposes, and a mechanism for the incremental composition of behaviors. A comparative study and an example IDS are used to test and show the suitability and validity of the approach. The JADE multi-agent middleware has been used for the practical implementations.
Francisco José Aguayo-Canela; Héctor Alaiz-Moretón; María Teresa García-Ordás; José Alberto Benítez-Andrades; Carmen Benavides; Isaías García-Rodríguez. Enriched multi-agent middleware for building rule-based distributed security solutions for IoT environments. The Journal of Supercomputing 2021, 1 -23.
AMA StyleFrancisco José Aguayo-Canela, Héctor Alaiz-Moretón, María Teresa García-Ordás, José Alberto Benítez-Andrades, Carmen Benavides, Isaías García-Rodríguez. Enriched multi-agent middleware for building rule-based distributed security solutions for IoT environments. The Journal of Supercomputing. 2021; ():1-23.
Chicago/Turabian StyleFrancisco José Aguayo-Canela; Héctor Alaiz-Moretón; María Teresa García-Ordás; José Alberto Benítez-Andrades; Carmen Benavides; Isaías García-Rodríguez. 2021. "Enriched multi-agent middleware for building rule-based distributed security solutions for IoT environments." The Journal of Supercomputing , no. : 1-23.
The spread of the Internet of Things (IoT) is demanding new, powerful architectures for handling the huge amounts of data produced by the IoT devices. In many scenarios, many existing isolated solutions applied to IoT devices use a set of rules to detect, report and mitigate malware activities or threats. This paper describes a development environment that allows the programming and debugging of such rule-based multi-agent solutions. The solution consists of the integration of a rule engine into the agent, the use of a specialized, wrapping agent class with a graphical user interface for programming and testing purposes, and a mechanism for the incremental composition of behaviors. Finally, a set of examples and a comparative study were accomplished to test the suitability and validity of the approach. The JADE multi-agent middleware has been used for the practical implementation of the approach.
Francisco José Aguayo-Canela; Héctor Alaiz-Moretón; María Teresa García-Ordás; José Alberto Benítez-Andrades; Carmen Benavides; Paulo Novais; Isaías García-Rodríguez. Middleware-based multi-agent development environment for building and testing distributed intelligent systems. Cluster Computing 2021, 1 -13.
AMA StyleFrancisco José Aguayo-Canela, Héctor Alaiz-Moretón, María Teresa García-Ordás, José Alberto Benítez-Andrades, Carmen Benavides, Paulo Novais, Isaías García-Rodríguez. Middleware-based multi-agent development environment for building and testing distributed intelligent systems. Cluster Computing. 2021; ():1-13.
Chicago/Turabian StyleFrancisco José Aguayo-Canela; Héctor Alaiz-Moretón; María Teresa García-Ordás; José Alberto Benítez-Andrades; Carmen Benavides; Paulo Novais; Isaías García-Rodríguez. 2021. "Middleware-based multi-agent development environment for building and testing distributed intelligent systems." Cluster Computing , no. : 1-13.
José Alberto Benítez Andrades. Peer Review of “Machine Learning for Risk Group Identification and User Data Collection in a Herpes Simplex Virus Patient Registry: Algorithm Development and Validation Study” (Preprint). 2021, 1 .
AMA StyleJosé Alberto Benítez Andrades. Peer Review of “Machine Learning for Risk Group Identification and User Data Collection in a Herpes Simplex Virus Patient Registry: Algorithm Development and Validation Study” (Preprint). . 2021; ():1.
Chicago/Turabian StyleJosé Alberto Benítez Andrades. 2021. "Peer Review of “Machine Learning for Risk Group Identification and User Data Collection in a Herpes Simplex Virus Patient Registry: Algorithm Development and Validation Study” (Preprint)." , no. : 1.
Objectives To analyse the physical activity carried out by the adolescents in the study, its relationship to being overweight (overweight+obese) and to analyse the structure of the social network of friendship established in adolescents doing group sports, using different parameters indicative of centrality. Setting It was carried out in an educational environment, in 11 classrooms belonging to 5 Schools in Ponferrada (Spain). Participants 235 adolescents were included in the study (49.4% female), who were classified as normal weight or overweight. Primary and secondary outcome measures Physical Activity Questionnaire for Adolescents (PAQ-A) was used to study the level of physical activity. A social network analysis was carried out to analyse structural variables of centrality in different degrees of contact. Results 30.2% of the participants in our study were overweight. Relative to female participants in this study, males obtained significantly higher scores in the PAQ-A (OR: 2.11; 95% CI: 1.04 to 4.25; p value: 0.036) and were more likely to participate in group sport (OR: 4.59; 95% CI: 2.28 to 9.22; p value: 0.000). We found no significant relationship between physical activity and the weight status in the total sample, but among female participants, those with overweight status had higher odds of reporting high levels of physical exercise (OR: 4.50; 95% CI: 1.21 to 16.74; p value: 0.025). In terms of centrality, differentiating by gender, women who participated in group sports were more likely to be classified as having low values of centrality, while the opposite effect occurred for men, more likely to be classified as having high values of centrality. Conclusions Our findings, with limitations, underline the importance of two fundamental aspects to be taken into account in the design of future strategies: gender and the centrality within the social network depending on the intensity of contact they have with their peers.
Pilar Marqués-Sánchez; José Alberto Benítez-Andrades; María Dolores Calvo Sánchez; Natalia Arias. The socialisation of the adolescent who carries out team sports: a transversal study of centrality with a social network analysis. BMJ Open 2021, 11, e042773 .
AMA StylePilar Marqués-Sánchez, José Alberto Benítez-Andrades, María Dolores Calvo Sánchez, Natalia Arias. The socialisation of the adolescent who carries out team sports: a transversal study of centrality with a social network analysis. BMJ Open. 2021; 11 (3):e042773.
Chicago/Turabian StylePilar Marqués-Sánchez; José Alberto Benítez-Andrades; María Dolores Calvo Sánchez; Natalia Arias. 2021. "The socialisation of the adolescent who carries out team sports: a transversal study of centrality with a social network analysis." BMJ Open 11, no. 3: e042773.
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.
Carmen Benavides; José Alberto Benítez-Andrades; Pilar Marqués-Sánchez; Natalia Arias. eHealth Intervention to Improve Health Habits in the Adolescent Population: Mixed Methods Study. JMIR mHealth and uHealth 2021, 9, e20217 .
AMA StyleCarmen Benavides, José Alberto Benítez-Andrades, Pilar Marqués-Sánchez, Natalia Arias. eHealth Intervention to Improve Health Habits in the Adolescent Population: Mixed Methods Study. JMIR mHealth and uHealth. 2021; 9 (2):e20217.
Chicago/Turabian StyleCarmen Benavides; José Alberto Benítez-Andrades; Pilar Marqués-Sánchez; Natalia Arias. 2021. "eHealth Intervention to Improve Health Habits in the Adolescent Population: Mixed Methods Study." JMIR mHealth and uHealth 9, no. 2: e20217.
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.
María Teresa García-Ordás; Carmen Benavides; José Alberto Benítez-Andrades; Héctor Alaiz-Moretón; Isaías García-Rodríguez. Diabetes detection using deep learning techniques with oversampling and feature augmentation. Computer Methods and Programs in Biomedicine 2021, 202, 105968 .
AMA StyleMaría Teresa García-Ordás, Carmen Benavides, José Alberto Benítez-Andrades, Héctor Alaiz-Moretón, Isaías García-Rodríguez. Diabetes detection using deep learning techniques with oversampling and feature augmentation. Computer Methods and Programs in Biomedicine. 2021; 202 ():105968.
Chicago/Turabian StyleMaría Teresa García-Ordás; Carmen Benavides; José Alberto Benítez-Andrades; Héctor Alaiz-Moretón; Isaías García-Rodríguez. 2021. "Diabetes detection using deep learning techniques with oversampling and feature augmentation." Computer Methods and Programs in Biomedicine 202, no. : 105968.
The detection and prevention of addictive behaviour at an early age is essential given the relationship between the age of the onset of consumption and the appearance of addiction disorders. The aim of this study was to describe the behavior related to substance use and addictive behaviors in adolescents at secondary school from 12 to 16 years of age. A cross-sectional descriptive study has been conducted. The prevalence of consumption of different addictive substances (alcohol, tobacco, cannabis, cocaine) and addictive behaviours (use of social networks and video games) were collated, and the influence of the surrounding social environment and risk perception were evaluated. The final sample was 1298 students. Alcohol, tobacco and cannabis use reflect the prevalence of last month's consumption: 14% (11.8–15.6), 15% (13.4–17.4) and 3% (1.9–2.7) respectively. 76% of the sample frequently use the Internet (5–7 days per week). There is a positive association between the frequency of use and use in the immediate environment. The relationships found show the need for educational and preventive intervention aimed at parents and students that will allow them to know and effectively deal with possible problems associated with the consumption of addictive substances.
Elena García-García; María-Lara Martínez-Gimeno; José Benítez-Andrades; Joselin Miranda-Gómez; Enrique Zapata-Cornejo; Gema Escobar-Aguilar. Substance Use and Addictive Behavior in Spanish Adolescents in Secondary School. Healthcare 2021, 9, 186 .
AMA StyleElena García-García, María-Lara Martínez-Gimeno, José Benítez-Andrades, Joselin Miranda-Gómez, Enrique Zapata-Cornejo, Gema Escobar-Aguilar. Substance Use and Addictive Behavior in Spanish Adolescents in Secondary School. Healthcare. 2021; 9 (2):186.
Chicago/Turabian StyleElena García-García; María-Lara Martínez-Gimeno; José Benítez-Andrades; Joselin Miranda-Gómez; Enrique Zapata-Cornejo; Gema Escobar-Aguilar. 2021. "Substance Use and Addictive Behavior in Spanish Adolescents in Secondary School." Healthcare 9, no. 2: 186.
The special situation brought about by the coronavirus pandemic and the confinement imposed by the Government, has given rise to numerous changes in working habits. The workers at the universities have had to start a period of teleworking that could give rise to consequences for the musculoskeletal system. The objective of this article is to analyze the impact of the confinement on the musculoskeletal health of the staff of two Spanish universities. A cross-sectional, observational study was carried out on the workers. Data was taken in April–May 2020 and included: The Standardized Kuorinka Modified Nordic Questionnaire, the Perceived Stress Scale and another one on sociodemographic data. This study comprised 472 people. The areas of pain noted during the confinement period concluded that it was less in all cases (p < 0.001). The frequency of physical activity carried out increased significantly during the period of confinement (p < 0.04), especially in women. The type of physical activity done was also seen to modify during this period (p < 0.001), with a preference for strength training and stretching exercises. In conclusion, the confinement gave rise to changes in the lifestyle and in the musculoskeletal pain of the workers at the universities. All of this must be taken into account by health institutions and those responsible for the Prevention of Occupational Risks at Spanish universities.
Óscar Rodríguez-Nogueira; Raquel Leirós-Rodríguez; José Benítez-Andrades; María Álvarez-Álvarez; Pilar Marqués-Sánchez; Arrate Pinto-Carral. Musculoskeletal Pain and Teleworking in Times of the COVID-19: Analysis of the Impact on the Workers at Two Spanish Universities. International Journal of Environmental Research and Public Health 2020, 18, 31 .
AMA StyleÓscar Rodríguez-Nogueira, Raquel Leirós-Rodríguez, José Benítez-Andrades, María Álvarez-Álvarez, Pilar Marqués-Sánchez, Arrate Pinto-Carral. Musculoskeletal Pain and Teleworking in Times of the COVID-19: Analysis of the Impact on the Workers at Two Spanish Universities. International Journal of Environmental Research and Public Health. 2020; 18 (1):31.
Chicago/Turabian StyleÓscar Rodríguez-Nogueira; Raquel Leirós-Rodríguez; José Benítez-Andrades; María Álvarez-Álvarez; Pilar Marqués-Sánchez; Arrate Pinto-Carral. 2020. "Musculoskeletal Pain and Teleworking in Times of the COVID-19: Analysis of the Impact on the Workers at Two Spanish Universities." International Journal of Environmental Research and Public Health 18, no. 1: 31.
The lockdown, due to the coronavirus, has led to a change in lifestyle and physical activity in Spanish university students. The objective of this study was to analyze the prevalence of musculoskeletal pain and changes in physical activity and self-perceived stress in the student bodies of two Spanish Universities during the lockdown. A cross-sectional study was carried out in a sample of 1198 students (70.6% women). The main instruments used for measuring were the Standardized Kuorinka Modified Nordic Questionnaire and the Perceived stress scale (the questionnaire regarding the practice of physical activity). A reduction in the prevalence of musculoskeletal pain (p < 0.001) was identified in the sample of men and women, an increase (12.5%) in the frequency of carrying out physical activity from moderate to frequent, and the preference for strength training (15.1%), especially among women, was identified. All of this may be taken into account by health institutions when implementing measures to encourage physical activity in both suitable amounts and types, which improves the quality of life of the students.
Raquel Leirós-Rodríguez; Óscar Rodríguez-Nogueira; Arrate Pinto-Carral; Mª José Álvarez-Álvarez; Miguel Á. Galán-Martín; Federico Montero-Cuadrado; José Alberto Benítez-Andrades. Musculoskeletal Pain and Non-Classroom Teaching in Times of the COVID-19 Pandemic: Analysis of the Impact on Students from Two Spanish Universities. Journal of Clinical Medicine 2020, 9, 4053 .
AMA StyleRaquel Leirós-Rodríguez, Óscar Rodríguez-Nogueira, Arrate Pinto-Carral, Mª José Álvarez-Álvarez, Miguel Á. Galán-Martín, Federico Montero-Cuadrado, José Alberto Benítez-Andrades. Musculoskeletal Pain and Non-Classroom Teaching in Times of the COVID-19 Pandemic: Analysis of the Impact on Students from Two Spanish Universities. Journal of Clinical Medicine. 2020; 9 (12):4053.
Chicago/Turabian StyleRaquel Leirós-Rodríguez; Óscar Rodríguez-Nogueira; Arrate Pinto-Carral; Mª José Álvarez-Álvarez; Miguel Á. Galán-Martín; Federico Montero-Cuadrado; José Alberto Benítez-Andrades. 2020. "Musculoskeletal Pain and Non-Classroom Teaching in Times of the COVID-19 Pandemic: Analysis of the Impact on Students from Two Spanish Universities." Journal of Clinical Medicine 9, no. 12: 4053.
This work addresses the performance comparison of clustering techniques in order to achieve robust hybrid models. With this goal, three different clustering techniques have been tested. The experimental environment designed for this purpose is based on a real case study, a thermal solar generation system installed in a bio-climate house located in Sotavento Experimental Wind Farm, in Xermade (Lugo) in Galicia (Spain). In this way, clustering methods have been applied over the real dataset extracted from the thermal solar generation installation. For comparing the quality of each clustering technique, two approaches have been used. The first one is oriented to a set of three unsupervised learning metrics (Silhouette, Calinski-Harabasz, and Davies-Bouldin), while the second one is based on error measurements associated with a regression method such as Multi-Layer Perceptron.
María Teresa García-Ordás; Héctor Alaiz-Moretón; José-Luis Casteleiro-Roca; Esteban Jove; José Alberto Benítez Andrades; Carmen Benavides Cuellar; Héctor Quintián; José Luis Calvo-Rolle. Clustering Techniques Performance Analysis for a Solar Thermal Collector Hybrid Model Implementation. Transactions on Petri Nets and Other Models of Concurrency XV 2020, 329 -340.
AMA StyleMaría Teresa García-Ordás, Héctor Alaiz-Moretón, José-Luis Casteleiro-Roca, Esteban Jove, José Alberto Benítez Andrades, Carmen Benavides Cuellar, Héctor Quintián, José Luis Calvo-Rolle. Clustering Techniques Performance Analysis for a Solar Thermal Collector Hybrid Model Implementation. Transactions on Petri Nets and Other Models of Concurrency XV. 2020; ():329-340.
Chicago/Turabian StyleMaría Teresa García-Ordás; Héctor Alaiz-Moretón; José-Luis Casteleiro-Roca; Esteban Jove; José Alberto Benítez Andrades; Carmen Benavides Cuellar; Héctor Quintián; José Luis Calvo-Rolle. 2020. "Clustering Techniques Performance Analysis for a Solar Thermal Collector Hybrid Model Implementation." Transactions on Petri Nets and Other Models of Concurrency XV , no. : 329-340.
Excessive alcohol consumption in adolescents is one of the most significant public health problems currently facing society. Social and geographical contexts contribute to the development of alcohol-related behavior in adolescents. The aim of this research is to analyze the social pattern related to alcohol consumption in adolescents based on their geographical environment. We designed a descriptive cross-sectional study based on social network analysis. We recruited 196 high school students between 16 and 18 years of age to participate in the study. The methodology applied was social network analysis by means of transitivity and homophily social triads. The data were analyzed using STATA statistical software. A total of 58.48% of rural adolescents consumed alcohol compared to 49.52% of urban adolescents. These results demonstrate that adolescents who live in rural areas exhibit a greater risk of drinking alcohol than those who live in urban areas. The presence of transitive triads increases the probability of sharing sociodemographic attributes in such a way that it may be considered one of the causes of homophily, contributing to adolescents taking greater risks, such as consuming alcohol.
Pilar Marqués-Sánchez; Enedina Quiroga Sánchez; Cristina Liébana-Presa; Elena Fernández-Martínez; Isaías García-Rodríguez; José Alberto Benítez-Andrades. The consumption of alcohol by adolescent schoolchildren: Differences in the triadic relationship pattern between rural and urban environments. PLOS ONE 2020, 15, e0241135 .
AMA StylePilar Marqués-Sánchez, Enedina Quiroga Sánchez, Cristina Liébana-Presa, Elena Fernández-Martínez, Isaías García-Rodríguez, José Alberto Benítez-Andrades. The consumption of alcohol by adolescent schoolchildren: Differences in the triadic relationship pattern between rural and urban environments. PLOS ONE. 2020; 15 (11):e0241135.
Chicago/Turabian StylePilar Marqués-Sánchez; Enedina Quiroga Sánchez; Cristina Liébana-Presa; Elena Fernández-Martínez; Isaías García-Rodríguez; José Alberto Benítez-Andrades. 2020. "The consumption of alcohol by adolescent schoolchildren: Differences in the triadic relationship pattern between rural and urban environments." PLOS ONE 15, no. 11: e0241135.
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.
María García-Ordás; Natalia Arias; Carmen Benavides; Oscar García-Olalla; José Benítez-Andrades. Evaluation of Country Dietary Habits Using Machine Learning Techniques in Relation to Deaths from COVID-19. Healthcare 2020, 8, 371 .
AMA StyleMaría García-Ordás, Natalia Arias, Carmen Benavides, Oscar García-Olalla, José Benítez-Andrades. Evaluation of Country Dietary Habits Using Machine Learning Techniques in Relation to Deaths from COVID-19. Healthcare. 2020; 8 (4):371.
Chicago/Turabian StyleMaría García-Ordás; Natalia Arias; Carmen Benavides; Oscar García-Olalla; José Benítez-Andrades. 2020. "Evaluation of Country Dietary Habits Using Machine Learning Techniques in Relation to Deaths from COVID-19." Healthcare 8, no. 4: 371.
University students establish networks that impact on their behavior. Social Network Analysis (SNA) allows us to analyze the reticular structures formed and find patterns of interaction between university students. The main objective of this study was to observe the impact of interdisciplinary collaborative work between nursing and computer engineering students on the collaboration and friendship networks, emotions and performance of the participants. It is a quasi-experimental descriptive study with pre- and post-intervention measurements. The contact networks analyzed showed an increase in density in the post-intervention period. The most central people in the network corresponded with those who considered positive emotions most in their academic environment, while the less central people coincided with those who highlighted negative emotions. Academic performance was only significantly associated in the collaboration network, between this and OutdegreeN. This study shows the impact of interdisciplinary activities on teaching methodologies and the repercussions of emotions on curricular activity.
Pilar Marqués-Sánchez; Isaías García-Rodríguez; José Benítez-Andrades; Iván Fulgueiras-Carril; Patricia Fernández-Sierra; Elena Fernández-Martínez. Networks and Emotions in Cooperative Work: A Quasi-Experimental Study in University Nursing and Computer Engineering Students. Healthcare 2020, 8, 220 .
AMA StylePilar Marqués-Sánchez, Isaías García-Rodríguez, José Benítez-Andrades, Iván Fulgueiras-Carril, Patricia Fernández-Sierra, Elena Fernández-Martínez. Networks and Emotions in Cooperative Work: A Quasi-Experimental Study in University Nursing and Computer Engineering Students. Healthcare. 2020; 8 (3):220.
Chicago/Turabian StylePilar Marqués-Sánchez; Isaías García-Rodríguez; José Benítez-Andrades; Iván Fulgueiras-Carril; Patricia Fernández-Sierra; Elena Fernández-Martínez. 2020. "Networks and Emotions in Cooperative Work: A Quasi-Experimental Study in University Nursing and Computer Engineering Students." Healthcare 8, no. 3: 220.
The use of social network theory and methods of analysis have been applied to different domains in recent years, including public health. The complete procedure for carrying out a social network analysis (SNA) is a time-consuming task that entails a series of steps in which the expert in social network analysis could make mistakes. This research presents a multi-domain knowledge model capable of automatically gathering data and carrying out different social network analyses in different domains, without errors and obtaining the same conclusions that an expert in SNA would obtain. The model is represented in an ontology called OntoSNAQA, which is made up of classes, properties and rules representing the domains of People, Questionnaires and Social Network Analysis. Besides the ontology itself, different rules are represented by SWRL and SPARQL queries. A Knowledge Based System was created using OntoSNAQA and applied to a real case study in order to show the advantages of the approach. Finally, the results of an SNA analysis obtained through the model were compared to those obtained from some of the most widely used SNA applications: UCINET, Pajek, Cytoscape and Gephi, to test and confirm the validity of the model.
José Alberto Benítez-Andrades; Isaías García-Rodríguez; Carmen Benavides; Héctor Alaiz-Moretón; José Emilio Labra Gayo. An ontology-based multi-domain model in social network analysis: Experimental validation and case study. Information Sciences 2020, 540, 390 -413.
AMA StyleJosé Alberto Benítez-Andrades, Isaías García-Rodríguez, Carmen Benavides, Héctor Alaiz-Moretón, José Emilio Labra Gayo. An ontology-based multi-domain model in social network analysis: Experimental validation and case study. Information Sciences. 2020; 540 ():390-413.
Chicago/Turabian StyleJosé Alberto Benítez-Andrades; Isaías García-Rodríguez; Carmen Benavides; Héctor Alaiz-Moretón; José Emilio Labra Gayo. 2020. "An ontology-based multi-domain model in social network analysis: Experimental validation and case study." Information Sciences 540, no. : 390-413.
Background: Alzheimer’s disease (AD) which is the most common type of dementia is characterized by mental or cognitive disorders. People suffering with this condition find it inherently difficult to communicate and describe symptoms. As a consequence, both detection and treatment of comorbidities associated with Alzheimer’s disease are substantially impaired. Equally, action protocols in the case of emergencies must be clearly formulated and stated. Methods: We performed a bibliography search followed by an observational and cross-sectional study involving a thorough review of medical records. A group of AD patients was compared with a control group. Each group consisted of 100 people and were all León residents aged ≥65 years. Results: The following comorbidities were found to be associated with AD: cataracts, urinary incontinence, osteoarthritis, hearing loss, osteoporosis, and personality disorders. The most frequent comorbidities in the control group were the following: eye strain, stroke, vertigo, as well as circulatory and respiratory disorders. Comorbidities with a similar incidence in both groups included type 2 diabetes mellitus, glaucoma, depression, obesity, arthritis, and anxiety. We also reviewed emergency procedures employed in the case of an emergency involving an AD patient. Conclusions: Some comorbidities were present in both the AD and control groups, while others were found in the AD group and not in the control group, and vice versa.
Macrina Tortajada-Soler; Leticia Sánchez-Valdeón; Marta Blanco-Nistal; José Alberto Benítez-Andrades; Cristina Liébana-Presa; Enrique Bayón-Darkistade. Prevalence of Comorbidities in Individuals Diagnosed and Undiagnosed with Alzheimer’s Disease in León, Spain and a Proposal for Contingency Procedures to Follow in the Case of Emergencies Involving People with Alzheimer’s Disease. International Journal of Environmental Research and Public Health 2020, 17, 3398 .
AMA StyleMacrina Tortajada-Soler, Leticia Sánchez-Valdeón, Marta Blanco-Nistal, José Alberto Benítez-Andrades, Cristina Liébana-Presa, Enrique Bayón-Darkistade. Prevalence of Comorbidities in Individuals Diagnosed and Undiagnosed with Alzheimer’s Disease in León, Spain and a Proposal for Contingency Procedures to Follow in the Case of Emergencies Involving People with Alzheimer’s Disease. International Journal of Environmental Research and Public Health. 2020; 17 (10):3398.
Chicago/Turabian StyleMacrina Tortajada-Soler; Leticia Sánchez-Valdeón; Marta Blanco-Nistal; José Alberto Benítez-Andrades; Cristina Liébana-Presa; Enrique Bayón-Darkistade. 2020. "Prevalence of Comorbidities in Individuals Diagnosed and Undiagnosed with Alzheimer’s Disease in León, Spain and a Proposal for Contingency Procedures to Follow in the Case of Emergencies Involving People with Alzheimer’s Disease." International Journal of Environmental Research and Public Health 17, no. 10: 3398.
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.
Carmen Benavides; José Alberto Benítez-Andrades; Pilar Marqués-Sánchez; Natalia Arias. eHealth Intervention to Improve Health Habits in the Adolescent Population: Mixed Methods Study (Preprint). 2020, 1 .
AMA StyleCarmen Benavides, José Alberto Benítez-Andrades, Pilar Marqués-Sánchez, Natalia Arias. eHealth Intervention to Improve Health Habits in the Adolescent Population: Mixed Methods Study (Preprint). . 2020; ():1.
Chicago/Turabian StyleCarmen Benavides; José Alberto Benítez-Andrades; Pilar Marqués-Sánchez; Natalia Arias. 2020. "eHealth Intervention to Improve Health Habits in the Adolescent Population: Mixed Methods Study (Preprint)." , no. : 1.