Tools for managing references in class projects and scientific works

[EN] This paper presents a set of tools to manage references, for its application in class projects, in the university context, and in scientific works. The main aim of this paper is to provide a set of tools to support university students and researchers to store all their research, and sort all their references, documents and notes in one place. This paper is an extension of the paper Adjustment of students to be future researchers: The importance of a systematic literature review methodology for MSC students [1] that proposes a guideline to help students to systematically perform the literature review phase in the research work. The work developed in the present paper, focuses on collecting, managing and treating the results through building a personalised database, proposing in a more extended way a set of tools to manage references of the research work performed in the systematic literature review.The research leading to these results has received funding from European Community's H2020 Programme (H2020/2014-2020) under grant agreement no 636909, "Cloud Collaborative Manufacturing Networks (C2NET)".Andres, B.; Poler, R.; Díaz-Madroñero Boluda, FM. (2017). Tools for managing references in class projects and scientific works. INTED proceedings (Online). 210-219. https://doi.org/10.21125/inted.2017.0172S21021

The Sustainable Development Goals (SDGs) Applied to Higher Education. A Project Based Learning Proposal Integrated with the SDGs in Bachelor Degrees at the Campus Alcoy (UPV)

[EN] The Sustainable Development Goals (SDGs) proposed by Union Nations were defined in Rio+20 Conference. These SDGs are 17, and they define 169 different goals that countries have to reach in 2030. The awareness and implication of people about the importance of the SDGs enable the fulfilment of these goals in a satisfactory way and therefore, the university community must take part of these objectives and integrate the SDGs within their curricula in the different bachelor and master degrees. In light of this, students must also integrate the specific competences, outcomes competences and SDGs in their learning process. To reach this integration, it is necessary that lecturers develop active methodologies in which students work competences and SDGs jointly. This article shows a proposal that is being developed in the Campus of Alcoy at the Universitat Politècnica de València (UPV) to define a Project Based Learning (PBL) model integrating the SDGs. The proposal shows how PBL can support students and lecturers to promote the teaching of key competences for sustainability that are relevant for the SDGs. The article discusses the concept of PBL and SDGs; accounts for the general students¿ capabilities, highlights the integration of SDGs in the PBL methodology into Bachelor and Master Degrees curricula at the Campus Alcoy (UPV). Moreover, it shows an alignment analysis performed between the SDGs and a PBL model in a case study.This article has been supported by the Vice-rectorate for Digital Resources and Documentation (Vicerrectorado de Recursos Digitales y Documentación) and Vice-Rectorate for Studies, Quality and Accreditation (Vicerrectorado de Estudios, Calidad y Acreditación) under the Call for Learning + Teaching (Convocatoria Aprendizaje + Docencia (A+D 2019)) and Project Code: 1678-A. The authors would like to acknowledge the support of the Institute of Educational Sciences (Instituto de Ciencias de la Educación) of Universitat Politècnica de València, the Evaluation and Monitoring Commission for Educational Innovation and Improvement Projects (Comisión de Evaluación y Seguimiento de Proyectos de Innovación y Mejora Educativa (CESPIME) and Escuela Politécnica Superior de AlcoyPérez-Sánchez, M.; Díaz-Madroñero Boluda, FM.; Mula, J.; Sanchis, R. (2020). The Sustainable Development Goals (SDGs) Applied to Higher Education. A Project Based Learning Proposal Integrated with the SDGs in Bachelor Degrees at the Campus Alcoy (UPV). EDULEARN Proceedings (Internet). 3997-4005. https://doi.org/10.21125/edulearn.2020.1078S3997400

Estudio de la actividad biocida de aceites procedentes de plantas aromáticas sobre Tetranychus urticae y Ceratitis capitata

Se ha estudiado la actividad biocida de aceites esenciales extraídos de plantas aromáticas como el romero (Rosmarinus officinalis L.) y la salvia (Salvia officinalis L.) sobre la araña roja (Tetranychus urticae Koch) y la mosca de la fruta (Ceratitis capitata Wiedemann). El aceite esencial de salvia a la concentración del 1% se mostró capaz de atraer adultos de C. capitata. La mayor actividad frente a la araña roja se observó por parte del aceite esencial de salvia, provocando, con gran rapidez, una alta tasa de mortalidad. El aceite de salvia al 0,25% consiguió reducir el nivel de puesta de T. urticae, llegando incluso a tasas de reducción de un 50%

Architecture for collaborative planning, forecasting and replenishment in a mass customization environment

[EN] In this paper, an architecture for collaborative planning, forecasting and replenishment in a mass customization environment is proposed. For this, on one hand, the main activities of the most important collaborative models and, on the other hand, the main processes related to mass customization environments. In order to achieve it, a set of interfaces are proposed, associated with the definition of products and additional services, the manufacturing and shipping of products, as well as transport and reception. The proposal is composed of a conceptual model, an implementation methodology, as well as possible technological solutions for its development in industrial companies[ES] En este trabajo se propone una arquitectura para la previsión, planificación y reaprovisionamiento colaborativo en un entorno de personalización en masa. Para ello, se identifica las actividades principales de los modelos colaborativos más destacados y los procesos principales asociados a los entornos de personalización en masa. Para llegar a ésta, se proponen un conjunto de interfases asociados a la definición de productos y servicios adicionales, a la fabricación y expedición, así como a actividades de transporte y recepción. La propuesta se compone de un modelo conceptual, una metodología de implantación, así como por posibles soluciones tecnológicas asociadas para su desarrollo en empresas industriales.Díaz-Madroñero Boluda, FM.; Poler, R. (2017). Arquitectura para la previsión, planificación y reaprovisionamiento colaborativo en un entorno de personalización en masa. Direccion y Organizacion. (63):5-20. http://hdl.handle.net/10251/108649S5206

The C2NET Optimisation Solution

[EN] Today's lack of competitiveness of European enterprises has led to the Cloud Collaborative Manufacturing Networks (C2NET) European funded project to develop an optimisation solution to provide enterprises, particularly small-and medium sized ones (SMEs), affordable and easy-to-use means to optimise their planning activities to improve their efficiency and competitiveness. This paper focuses on the C2NET optimisation solu-tion, constituted mainly by C2NET Optimiser module components: (i) optimisation algorithms; (ii) the solver manager; (iii) the optimisation problem configurator; (iv) processes of the optimisation of manufacturing assets manager. To perform optimisation, it is necessary to provide the previous components with the needed input data, which can be done within the data collection framework module by defining a standardised data model (STables). Another data model is defined to show optimisation results to SMEs, namely the plan data model (PTables). The C2NET Optimisation Solution supports manufacturing networks, especially those composed of SMEs, and is based on the optimisation of manufacturing and logistics assets by the single and/or collaborative computation of production, replenishment and delivery plans.The research that led to these results forms part of the "Cloud Collaborative Manufacturing Networks" (C2NET) Project, which has received funding from the EU Horizon 2020 Research and Innovation Programme with grant agreement No. 63690.Sanchis, R.; Andres, B.; Poler, R.; Mula, J.; Díaz-Madroñero Boluda, FM. (2018). The C2NET Optimisation Solution. Direccion y Organizacion. 64:36-41. http://hdl.handle.net/10251/120631S36416

Electrohysterogram for ANN-Based Prediction of Imminent Labor in Women with Threatened Preterm Labor Undergoing Tocolytic Therapy

[EN] Threatened preterm labor (TPL) is the most common cause of hospitalization in the second half of pregnancy and entails high costs for health systems. Currently, no reliable labor proximity prediction techniques are available for clinical use. Regular checks by uterine electrohysterogram (EHG) for predicting preterm labor have been widely studied. The aim of the present study was to assess the feasibility of predicting labor with a 7- and 14-day time horizon in TPL women, who may be under tocolytic treatment, using EHG and/or obstetric data. Based on 140 EHG recordings, artificial neural networks were used to develop prediction models. Non-linear EHG parameters were found to be more reliable than linear for differentiating labor in under and over 7/14 days. Using EHG and obstetric data, the <7- and <14-day labor prediction models achieved an AUC in the test group of 87.1 +/- 4.3% and 76.2 +/- 5.8%, respectively. These results suggest that EHG can be reliable for predicting imminent labor in TPL women, regardless of the tocolytic therapy stage. This paves the way for the development of diagnostic tools to help obstetricians make better decisions on treatments, hospital stays and admitting TPL women, and can therefore reduce costs and improve maternal and fetal wellbeing.This work was supported by the Spanish Ministry of Economy and Competitiveness, the European Regional Development Fund (MCIU/AEI/FEDER, UE RTI2018-094449-A-I00-AR) and by the Generalitat Valenciana (AICO/2019/220).Mas-Cabo, J.; Prats-Boluda, G.; Garcia-Casado, J.; Alberola Rubio, J.; Monfort-Ortiz, R.; Martinez-Saez, C.; Perales, A.... (2020). Electrohysterogram for ANN-Based Prediction of Imminent Labor in Women with Threatened Preterm Labor Undergoing Tocolytic Therapy. Sensors. 20(9):1-16. https://doi.org/10.3390/s20092681S116209Beck, S., Wojdyla, D., Say, L., Pilar Bertran, A., Meraldi, M., Harris Requejo, J., … Van Look, P. (2010). The worldwide incidence of preterm birth: a systematic review of maternal mortality and morbidity. Bulletin of the World Health Organization, 88(1), 31-38. doi:10.2471/blt.08.062554Zeitlin, J., Szamotulska, K., Drewniak, N., Mohangoo, A., Chalmers, J., … Sakkeus, L. (2013). Preterm birth time trends in Europe: a study of 19 countries. BJOG: An International Journal of Obstetrics & Gynaecology, 120(11), 1356-1365. doi:10.1111/1471-0528.12281Goldenberg, R. L., Culhane, J. F., Iams, J. D., & Romero, R. (2008). Epidemiology and causes of preterm birth. The Lancet, 371(9606), 75-84. doi:10.1016/s0140-6736(08)60074-4Petrou, S. (2005). The economic consequences of preterm birth duringthe first 10 years of life. BJOG: An International Journal of Obstetrics & Gynaecology, 112, 10-15. doi:10.1111/j.1471-0528.2005.00577.xLucovnik, M., Chambliss, L. R., & Garfield, R. E. (2013). Costs of unnecessary admissions and treatments for «threatened preterm labor». American Journal of Obstetrics and Gynecology, 209(3), 217.e1-217.e3. doi:10.1016/j.ajog.2013.06.046Haas, D., Benjamin, T., Sawyer, R., & Quinney, S. (2014). Short-term tocolytics for preterm delivery &ndash; current perspectives. International Journal of Women’s Health, 343. doi:10.2147/ijwh.s44048Euliano, T. Y., Nguyen, M. T., Darmanjian, S., McGorray, S. P., Euliano, N., Onkala, A., & Gregg, A. R. (2013). Monitoring uterine activity during labor: a comparison of 3 methods. American Journal of Obstetrics and Gynecology, 208(1), 66.e1-66.e6. doi:10.1016/j.ajog.2012.10.873Devedeux, D., Marque, C., Mansour, S., Germain, G., & Duchêne, J. (1993). Uterine electromyography: A critical review. 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Accuracy of Frequency-Related Parameters of the Electrohysterogram for Predicting Preterm Delivery. Obstetrical & Gynecological Survey, 64(8), 529-541. doi:10.1097/ogx.0b013e3181a8c6b1Vrhovec, J., Macek-Lebar, A., & Rudel, D. (s. f.). Evaluating Uterine Electrohysterogram with Entropy. IFMBE Proceedings, 144-147. doi:10.1007/978-3-540-73044-6_36Diab, A., Hassan, M., Marque, C., & Karlsson, B. (2014). Performance analysis of four nonlinearity analysis methods using a model with variable complexity and application to uterine EMG signals. Medical Engineering & Physics, 36(6), 761-767. doi:10.1016/j.medengphy.2014.01.009Lemancewicz, A., Borowska, M., Kuć, P., Jasińska, E., Laudański, P., Laudański, T., & Oczeretko, E. (2016). Early diagnosis of threatened premature labor by electrohysterographic recordings – The use of digital signal processing. Biocybernetics and Biomedical Engineering, 36(1), 302-307. doi:10.1016/j.bbe.2015.11.005Hassan, M., Terrien, J., Marque, C., & Karlsson, B. (2011). Comparison between approximate entropy, correntropy and time reversibility: Application to uterine electromyogram signals. Medical Engineering & Physics, 33(8), 980-986. doi:10.1016/j.medengphy.2011.03.010Fergus, P., Idowu, I., Hussain, A., & Dobbins, C. (2016). Advanced artificial neural network classification for detecting preterm births using EHG records. Neurocomputing, 188, 42-49. doi:10.1016/j.neucom.2015.01.107Acharya, U. R., Sudarshan, V. K., Rong, S. Q., Tan, Z., Lim, C. M., Koh, J. E., … Bhandary, S. V. (2017). Automated detection of premature delivery using empirical mode and wavelet packet decomposition techniques with uterine electromyogram signals. Computers in Biology and Medicine, 85, 33-42. doi:10.1016/j.compbiomed.2017.04.013Fergus, P., Cheung, P., Hussain, A., Al-Jumeily, D., Dobbins, C., & Iram, S. (2013). Prediction of Preterm Deliveries from EHG Signals Using Machine Learning. 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Identification of Human Term and Preterm Labor using Artificial Neural Networks on Uterine Electromyography Data. Annals of Biomedical Engineering, 35(3), 465-473. doi:10.1007/s10439-006-9248-8Mas-Cabo, J., Prats-Boluda, G., Garcia-Casado, J., Alberola-Rubio, J., Perales, A., & Ye-Lin, Y. (2019). Design and Assessment of a Robust and Generalizable ANN-Based Classifier for the Prediction of Premature Birth by means of Multichannel Electrohysterographic Records. Journal of Sensors, 2019, 1-13. doi:10.1155/2019/5373810Terrien, J., Marque, C., & Karlsson, B. (2007). Spectral characterization of human EHG frequency components based on the extraction and reconstruction of the ridges in the scalogram. 2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. doi:10.1109/iembs.2007.4352680Rooijakkers, M. J., Rabotti, C., Oei, S. G., Aarts, R. M., & Mischi, M. (2014). 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Dispersion Entropy: A Measure of Electrohysterographic Complexity for Preterm Labor Discrimination

[EN] Although preterm labor is a major cause of neonatal death and often leaves health sequels in the survivors, there are no accurate and reliable clinical tools for preterm labor prediction. The Electrohysterogram (EHG) has arisen as a promising alternative that provides relevant information on uterine activity that could be useful in predicting preterm labor. In this work, we optimized and assessed the performance of the Dispersion Entropy (DispEn) metric and compared it to conventional Sample Entropy (SampEn) in EHG recordings to discriminate term from preterm deliveries. For this, we used the two public databases TPEHG and TPEHGT DS of EHG recordings collected from women during regular checkups. The 10th, 50th and 90th percentiles of entropy metrics were computed on whole (WBW) and fast wave high (FWH) EHG bandwidths, sweeping the DispEn and SampEn internal parameters to optimize term/preterm discrimination. The results revealed that for both the FWH and WBW bandwidths the best separability was reached when computing the 10th percentile, achieving a p-value (0.00007) for DispEn in FWH, c = 7 and m = 2, associated with lower complexity preterm deliveries, indicating that DispEn is a promising parameter for preterm labor prediction.This work was supported by the Spanish ministry of economy and competitiveness, the European Regional Development Fund (MCIU/AEI/FEDER, UE RTI2018-094449-A-I00-AR) and the Generalitat Valenciana (AICO/2019/220).Nieto-Del-Amor, F.; Ye Lin, Y.; Garcia-Casado, J.; Díaz-Martínez, MDA.; González Martínez, M.; Monfort-Ortiz, R.; Prats-Boluda, G. (2021). Dispersion Entropy: A Measure of Electrohysterographic Complexity for Preterm Labor Discrimination. SCITEPRESS. 260-267. https://doi.org/10.5220/0010316602600267S26026