An analysis of different resources and programmes supporting at-risk families in Spain

The purpose of this research was to present an overview of the existing family support resources in Spain for at-risk families. We analysed 64 family support services from 16 agencies belong to 11 regions of Spain. In a second phase, 20 positive parenting programmes were analysed in depth to ascertain the extent to which they met evidence-based programme quality criteria. Our results suggest that services for at-risk families are delivered by public, local and social agencies. Most interventions were psycho-educational and aimed at parental training. The analysis of the positive parenting programmes ’ quality showed both strengths and weaknesses. Most programmes relied on a previous needs analysis and interventions were, to some extent, outlined in a manual. Nevertheless, few programmes have been evaluated according to evidence-based programme criteria. In light of these results, we discuss several practical implications for services and family support policies aimed at at-risk families.Ministerio de Economía y Competitividad de España EDU2013-41441-

Effects of a mixed reality headset on the delay of visually evoked potentials

Virtual and mixed reality (VR, MR) technologies offer a powerful solution for on-the-ground flight training curricula. While these technologies offer safer and cheaper instructional programs, it is still unclear how they impact neuronal brain dynamics. Indeed, MR simulations engage students in a strange mix of incongruous visual, somatosensory and vestibular sensory input. Characterizing brain dynamics during MR simulation is important for understanding cognitive processes during virtual flight training. To this end, we studies the delays introduced in the neuronal stream from the retina to the visual cortex when presented with visual stimuli using a Varjo-XR3 headset. We recorded cortical visual evoked potentials (VEPs) from 6 subjects under two conditions. First, we recorded normal VEPs triggered by short flashes. Second, we recorded VEPs triggered by an internal image of the flashes produced by the Varjo-XR3 headset. All subjects had used the headset before and were familiar with immersive experiences. Our results show mixed-reality stimulation imposes a small, but consistent, 4 [ms] processing delay in the N2-VEP component during MR stimulation as compared to direct stimulation. Also we found that VEP amplitudes during MR stimulation were also decreased. These results suggest that visual cognition during mixed-reality training is delayed, not only by the unavoidalbe hardware/software processing delays of the headset and the attached computer, but also by an extra biological delay induced by the headset's limited visual display in terms of the image intensity and contrast. As flight training is a demanding task, this study measures visual signal latency to better understand how MR affects the sensation of immersion

Multi-scale Entropy Evaluates the Proarrhythmic Condition of Persistent Atrial Fibrillation Patients Predicting Early Failure of Electrical Cardioversion

[EN] Atrial fibrillation (AF) is nowadays the most common cardiac arrhythmia, being associated with an increase in cardiovascular mortality and morbidity. When AF lasts for more than seven days, it is classified as persistent AF and external interventions are required for its termination. A well-established alternative for that purpose is electrical cardioversion (ECV). While ECV is able to initially restore sinus rhythm (SR) in more than 90% of patients, rates of AF recurrence as high as 20-30% have been found after only a few weeks of follow-up. Hence, new methods for evaluating the proarrhythmic condition of a patient before the intervention can serve as efficient predictors about the high risk of early failure of ECV, thus facilitating optimal management of AF patients. Among the wide variety of predictors that have been proposed to date, those based on estimating organization of the fibrillatory (f-) waves from the surface electrocardiogram (ECG) have reported very promising results. However, the existing methods are based on traditional entropy measures, which only assess a single time scale and often are unable to fully characterize the dynamics generated by highly complex systems, such as the heart during AF. The present work then explores whether a multi-scale entropy (MSE) analysis of thef-waves may provide early prediction of AF recurrence after ECV. In addition to the common MSE, two improved versions have also been analyzed, composite MSE (CMSE) and refined MSE (RMSE). When analyzing 70 patients under ECV, of which 31 maintained SR and 39 relapsed to AF after a four week follow-up, the three methods provided similar performance. However, RMSE reported a slightly better discriminant ability of 86%, thus improving the other multi-scale-based outcomes by 3-9% and other previously proposed predictors of ECV by 15-30%. This outcome suggests that investigation of dynamics at large time scales yields novel insights about the underlying complex processes generatingf-waves, which could provide individual proarrhythmic condition estimation, thus improving preoperative predictions of ECV early failure.This research has been supported by grants DPI2007-83952-C3 from MINECO/AEI/FEDER EU, SBPLY/17/180501000411 from Junta de Comunidades de Castilla la Mancha and AICO/2019/036 from Generalitat Valenciana.Cirugeda Roldan, EM.; Calero, S.; Hidalgo, VM.; Enero, J.; Rieta, JJ.; Alcaraz, R. (2020). Multi-scale Entropy Evaluates the Proarrhythmic Condition of Persistent Atrial Fibrillation Patients Predicting Early Failure of Electrical Cardioversion. Entropy. 22(7):1-17. https://doi.org/10.3390/e22070748S117227Lippi, G., Sanchis-Gomar, F., & Cervellin, G. (2020). Global epidemiology of atrial fibrillation: An increasing epidemic and public health challenge. International Journal of Stroke, 16(2), 217-221. doi:10.1177/1747493019897870Lane, D. A., Skjøth, F., Lip, G. Y. H., Larsen, T. B., & Kotecha, D. (2017). Temporal Trends in Incidence, Prevalence, and Mortality of Atrial Fibrillation in Primary Care. Journal of the American Heart Association, 6(5). doi:10.1161/jaha.116.005155Duarte, R. C. F., Rios, D. R. A., Figueiredo, E. L., Caiaffa, J. R. S., Silveira, F. R., Lanna, R., … das Graças Carvalho, M. (2020). Thrombin Generation and other hemostatic parameters in patients with atrial fibrillation in use of warfarin or rivaroxaban. Journal of Thrombosis and Thrombolysis, 51(1), 47-57. doi:10.1007/s11239-020-02126-3Khoo, C. W., Krishnamoorthy, S., Lim, H. S., & Lip, G. Y. H. (2012). Atrial fibrillation, arrhythmia burden and thrombogenesis. International Journal of Cardiology, 157(3), 318-323. doi:10.1016/j.ijcard.2011.06.088Zoni-Berisso, M., Lercari, F., Carazza, T., & Domenicucci, S. (2014). Epidemiology of atrial fibrillation: European perspective. Clinical Epidemiology, 213. doi:10.2147/clep.s47385Dietzel, J., Haeusler, K. G., & Endres, M. (2017). Does atrial fibrillation cause cognitive decline and dementia? EP Europace, 20(3), 408-419. doi:10.1093/europace/eux031Aliot, E., Botto, G. L., Crijns, H. J., & Kirchhof, P. (2014). Quality of life in patients with atrial fibrillation: how to assess it and how to improve it. Europace, 16(6), 787-796. doi:10.1093/europace/eut369Miyazawa, K., & Lip, G. Y. (2018). Atrial fibrillation. Medicine, 46(10), 627-631. doi:10.1016/j.mpmed.2018.07.009Blum, S., Meyre, P., Aeschbacher, S., Berger, S., Auberson, C., Briel, M., … Conen, D. (2019). Incidence and predictors of atrial fibrillation progression: A systematic review and meta-analysis. Heart Rhythm, 16(4), 502-510. doi:10.1016/j.hrthm.2018.10.022Berger, W. R., Meulendijks, E. R., Limpens, J., van den Berg, N. W. E., Neefs, J., Driessen, A. H. G., … de Groot, J. R. (2019). Persistent atrial fibrillation: A systematic review and meta-analysis of invasive strategies. International Journal of Cardiology, 278, 137-143. doi:10.1016/j.ijcard.2018.11.127Nattel, S., Guasch, E., Savelieva, I., Cosio, F. G., Valverde, I., Halperin, J. L., … Camm, A. J. (2014). Early management of atrial fibrillation to prevent cardiovascular complications. European Heart Journal, 35(22), 1448-1456. doi:10.1093/eurheartj/ehu028Kirchhof, P., Benussi, S., Kotecha, D., Ahlsson, A., Atar, D., Casadei, B., … Zeppenfeld, K. (2016). 2016 ESC Guidelines for the management of atrial fibrillation developed in collaboration with EACTS. European Heart Journal, 37(38), 2893-2962. doi:10.1093/eurheartj/ehw210Scheuermeyer, F. X., Andolfatto, G., Christenson, J., Villa‐Roel, C., & Rowe, B. (2019). A Multicenter Randomized Trial to Evaluate a Chemical‐first or Electrical‐first Cardioversion Strategy for Patients With Uncomplicated Acute Atrial Fibrillation. Academic Emergency Medicine, 26(9), 969-981. doi:10.1111/acem.13669Fried, A. M., Strout, T. D., & Perron, A. D. (2021). Electrical cardioversion for atrial fibrillation in the emergency department: A large single-center experience. The American Journal of Emergency Medicine, 42, 115-120. doi:10.1016/j.ajem.2020.02.001Brandes, A., Crijns, H. J. G. M., Rienstra, M., Kirchhof, P., Grove, E. L., Pedersen, K. B., & Van Gelder, I. C. (2020). Cardioversion of atrial fibrillation and atrial flutter revisited: current evidence and practical guidance for a common procedure. EP Europace, 22(8), 1149-1161. doi:10.1093/europace/euaa057Alegret, J. M., Viñolas, X., Tajes, H., Valdovinos, P., Palomares, R., Arias, M. A., & Bazán, V. (2020). Utility of Amiodarone Pre-Treatment as a Facilitator of the Acute Success of Electrical Cardioversion in Persistent Atrial Fibrillation. Cardiovascular Drugs and Therapy, 34(1), 89-94. doi:10.1007/s10557-019-06934-5Piccini, J. P., & Fauchier, L. (2016). Rhythm control in atrial fibrillation. The Lancet, 388(10046), 829-840. doi:10.1016/s0140-6736(16)31277-6Jaakkola, S., Lip, G. Y. H., Biancari, F., Nuotio, I., Hartikainen, J. E. K., Ylitalo, A., & Airaksinen, K. E. J. (2017). Predicting Unsuccessful Electrical Cardioversion for Acute Atrial Fibrillation (from the AF-CVS Score). The American Journal of Cardiology, 119(5), 749-752. doi:10.1016/j.amjcard.2016.11.026Fujimoto, Y., Yodogawa, K., Maru, Y., Oka, E., Hayashi, H., Yamamoto, T., … Shimizu, W. (2018). Advanced interatrial block is an electrocardiographic marker for recurrence of atrial fibrillation after electrical cardioversion. International Journal of Cardiology, 272, 113-117. doi:10.1016/j.ijcard.2018.07.135GRÖNBERG, T., HARTIKAINEN, J. E. K., NUOTIO, I., BIANCARI, F., VASANKARI, T., NIKKINEN, M., … AIRAKSINEN, K. E. J. (2014). Can We Predict the Failure of Electrical Cardioversion of Acute Atrial Fibrillation? The FinCV Study. Pacing and Clinical Electrophysiology, 38(3), 368-375. doi:10.1111/pace.12561Doruchowska, A., Wita, K., Bochenek, T., Szydło, K., Filipecki, A., Staroń, A., … Trusz-Gluza, M. (2014). Role of left atrial speckle tracking echocardiography in predicting persistent atrial fibrillation electrical cardioversion success and sinus rhythm maintenance at 6 months. Advances in Medical Sciences, 59(1), 120-125. doi:10.1016/j.advms.2013.10.003Luong, C. L., Thompson, D. J. S., Gin, K. G., Jue, J., Nair, P., Lee, P.-K., … Tsang, T. S. M. (2016). Usefulness of the Atrial Emptying Fraction to Predict Maintenance of Sinus Rhythm After Direct Current Cardioversion for Atrial Fibrillation. The American Journal of Cardiology, 118(9), 1345-1349. doi:10.1016/j.amjcard.2016.07.066Wałek, P., Sielski, J., Gorczyca, I., Roskal-Wałek, J., Starzyk, K., Jaskulska-Niedziela, E., … Wożakowska-Kapłon, B. (2020). Left atrial mechanical remodelling assessed as the velocity of left atrium appendage wall motion during atrial fibrillation is associated with maintenance of sinus rhythm after electrical cardioversion in patients with persistent atrial fibrillation. PLOS ONE, 15(1), e0228239. doi:10.1371/journal.pone.0228239Zhao, T. X., Martin, C. A., Cooper, J. P., & Gajendragadkar, P. R. (2017). Coarse fibrillatory waves in atrial fibrillation predict success of electrical cardioversion. Annals of Noninvasive Electrocardiology, 23(4), e12528. doi:10.1111/anec.12528Lombardi, F., Colombo, A., Basilico, B., Ravaglia, R., Garbin, M., Vergani, D., … Fiorentini, C. (2001). Heart rate variability and early recurrence of atrial fibrillation after electrical cardioversion. Journal of the American College of Cardiology, 37(1), 157-162. doi:10.1016/s0735-1097(00)01039-1Vikman, S., Mäkikallio, T. H., Yli‐Mäyry, S., Nurmi, M., Juhani Airaksinen, K., & Huikuri, H. V. (2003). Heart rate variability and recurrence of atrial fibrillation after electrical cardioversion. Annals of Medicine, 35(1), 36-42. doi:10.1080/07853890310004110VAN DEN BERG, M. P., VAN NOORD, T., BROUWER, J., HAAKSMA, J., VAN VELDHUISEN, D. J., CRIJNS, H. J. G. M., & VAN GELDER, I. C. (2004). Clustering of RR Intervals Predicts Effective Electrical Cardioversion for Atrial Fibrillation. Journal of Cardiovascular Electrophysiology, 15(9), 1027-1033. doi:10.1046/j.1540-8167.2004.03686.xZOHAR, P., KOVACIC, M., BREZOCNIK, M., & PODBREGAR, M. (2005). Prediction of maintenance of sinus rhythm after electrical cardioversion of atrial fibrillation by non-deterministic modelling. Europace, 7(5), 500-507. doi:10.1016/j.eupc.2005.04.007Seeck, A., Rademacher, W., Fischer, C., Haueisen, J., Surber, R., & Voss, A. (2013). Prediction of atrial fibrillation recurrence after cardioversion—Interaction analysis of cardiac autonomic regulation. Medical Engineering & Physics, 35(3), 376-382. doi:10.1016/j.medengphy.2012.06.002Eren, H., Kaya, Ü., Öcal, L., Şenbaş, A., & Kalçık, M. (2019). The presence of fragmented QRS may predict the recurrence of nonvalvular atrial fibrillation after successful electrical cardioversion. Annals of Noninvasive Electrocardiology, 25(1). doi:10.1111/anec.12700Langberg, J. J., Burnette, J. C., & McTeague, K. K. (1998). Spectral analysis of the electrocardiogram predicts recurrence of atrial fibrillation after cardioversion. Journal of Electrocardiology, 31, 80-84. doi:10.1016/s0022-0736(98)90297-7Watson, J. N., Addison, P. S., Uchaipichat, N., Shah, A. S., & Grubb, N. R. (2007). Wavelet transform analysis predicts outcome of DC cardioversion for atrial fibrillation patients. Computers in Biology and Medicine, 37(4), 517-523. doi:10.1016/j.compbiomed.2006.08.003Cervigón, R., Sánchez, C., Castells, F., Blas, J. M., & Millet, J. (2007). Wavelet analysis of electrocardiograms to characterize recurrent atrial fibrillation. Journal of the Franklin Institute, 344(3-4), 196-211. doi:10.1016/j.jfranklin.2006.10.005Alcaraz, R., & Rieta, J. J. (2008). A non-invasive method to predict electrical cardioversion outcome of persistent atrial fibrillation. Medical & Biological Engineering & Computing, 46(7), 625-635. doi:10.1007/s11517-008-0348-5Alcaraz, R., & Rieta, J. J. (2009). Time and frequency recurrence analysis of persistent atrial fibrillation after electrical cardioversion. Physiological Measurement, 30(5), 479-489. doi:10.1088/0967-3334/30/5/005Lankveld, T., de Vos, C. B., Limantoro, I., Zeemering, S., Dudink, E., Crijns, H. J., & Schotten, U. (2016). Systematic analysis of ECG predictors of sinus rhythm maintenance after electrical cardioversion for persistent atrial fibrillation. Heart Rhythm, 13(5), 1020-1027. doi:10.1016/j.hrthm.2016.01.004ALCARAZ, R., HORNERO, F., & RIETA, J. J. (2011). Noninvasive Time and Frequency Predictors of Long-Standing Atrial Fibrillation Early Recurrence after Electrical Cardioversion. Pacing and Clinical Electrophysiology, 34(10), 1241-1250. doi:10.1111/j.1540-8159.2011.03125.xCosta, M., Goldberger, A. L., & Peng, C.-K. (2002). Multiscale Entropy Analysis of Complex Physiologic Time Series. Physical Review Letters, 89(6). doi:10.1103/physrevlett.89.068102Humeau-Heurtier, A. (2015). The Multiscale Entropy Algorithm and Its Variants: A Review. Entropy, 17(5), 3110-3123. doi:10.3390/e17053110Wu, S.-D., Wu, C.-W., Lin, S.-G., Wang, C.-C., & Lee, K.-Y. (2013). Time Series Analysis Using Composite Multiscale Entropy. Entropy, 15(3), 1069-1084. doi:10.3390/e15031069Valencia, J. F., Porta, A., Vallverdu, M., Claria, F., Baranowski, R., Orlowska-Baranowska, E., & Caminal, P. (2009). Refined Multiscale Entropy: Application to 24-h Holter Recordings of Heart Period Variability in Healthy and Aortic Stenosis Subjects. IEEE Transactions on Biomedical Engineering, 56(9), 2202-2213. doi:10.1109/tbme.2009.2021986Alcaraz, R., & Rieta, J. J. (2008). Adaptive singular value cancelation of ventricular activity in single-lead atrial fibrillation electrocardiograms. Physiological Measurement, 29(12), 1351-1369. doi:10.1088/0967-3334/29/12/001Vest, A. N., Da Poian, G., Li, Q., Liu, C., Nemati, S., Shah, A. J., & Clifford, G. D. (2018). An open source benchmarked toolbox for cardiovascular waveform and interval analysis. Physiological Measurement, 39(10), 105004. doi:10.1088/1361-6579/aae021Nabil, D., & Bereksi Reguig, F. (2015). Ectopic beats detection and correction methods: A review. Biomedical Signal Processing and Control, 18, 228-244. doi:10.1016/j.bspc.2015.01.008Martínez, A., Alcaraz, R., & Rieta, J. J. (2013). Ventricular activity morphological characterization: Ectopic beats removal in long term atrial fibrillation recordings. Computer Methods and Programs in Biomedicine, 109(3), 283-292. doi:10.1016/j.cmpb.2012.10.011Alcaraz Martínez, R. (2013). Journal of Medical and Biological Engineering, 33(5), 455. doi:10.5405/jmbe.1069Corino, V. D. A., Sassi, R., Mainardi, L. T., & Cerutti, S. (2006). Signal processing methods for information enhancement in atrial fibrillation: Spectral analysis and non-linear parameters. Biomedical Signal Processing and Control, 1(4), 271-281. doi:10.1016/j.bspc.2006.12.003Alcaraz, R., & Rieta, J. J. (2009). Sample entropy of the main atrial wave predicts spontaneous termination of paroxysmal atrial fibrillation. Medical Engineering & Physics, 31(8), 917-922. doi:10.1016/j.medengphy.2009.05.002Richman, J. S., & Moorman, J. R. (2000). Physiological time-series analysis using approximate entropy and sample entropy. American Journal of Physiology-Heart and Circulatory Physiology, 278(6), H2039-H2049. doi:10.1152/ajpheart.2000.278.6.h2039Alcaraz, R., Abásolo, D., Hornero, R., & Rieta, J. J. (2010). Optimal parameters study for sample entropy-based atrial fibrillation organization analysis. Computer Methods and Programs in Biomedicine, 99(1), 124-132. doi:10.1016/j.cmpb.2010.02.009Costa, M., Peng, C.-K., L. Goldberger, A., & Hausdorff, J. M. (2003). Multiscale entropy analysis of human gait dynamics. Physica A: Statistical Mechanics and its Applications, 330(1-2), 53-60. doi:10.1016/j.physa.2003.08.022Pincus, S. M., & Goldberger, A. L. (1994). Physiological time-series analysis: what does regularity quantify? American Journal of Physiology-Heart and Circulatory Physiology, 266(4), H1643-H1656. doi:10.1152/ajpheart.1994.266.4.h1643Maturana-Candelas, A., Gómez, C., Poza, J., Pinto, N., & Hornero, R. (2019). EEG Characterization of the Alzheimer’s Disease Continuum by Means of Multiscale Entropies. Entropy, 21(6), 544. doi:10.3390/e21060544Crespo, A., Álvarez, D., Gutiérrez-Tobal, G. C., Vaquerizo-Villar, F., Barroso-García, V., Alonso-Álvarez, M. L., … Campo, F. del. (2017). Multiscale Entropy Analysis of Unattended Oximetric Recordings to Assist in the Screening of Paediatric Sleep Apnoea at Home. Entropy, 19(6), 284. doi:10.3390/e19060284Massey, F. J. (1951). The Kolmogorov-Smirnov Test for Goodness of Fit. Journal of the American Statistical Association, 46(253), 68-78. doi:10.1080/01621459.1951.10500769Williams, L. L., & Quave, K. (2019). Comparing Two Groups: t-Tests. Quantitative Anthropology, 89-104. doi:10.1016/b978-0-12-812775-9.00007-4Zweig, M. H., & Campbell, G. (1993). Receiver-operating characteristic (ROC) plots: a fundamental evaluation tool in clinical medicine. Clinical Chemistry, 39(4), 561-577. doi:10.1093/clinchem/39.4.561Qu, Z. (2011). Chaos in the genesis and maintenance of cardiac arrhythmias. Progress in Biophysics and Molecular Biology, 105(3), 247-257. doi:10.1016/j.pbiomolbio.2010.11.001Qu, Z., Hu, G., Garfinkel, A., & Weiss, J. N. (2014). Nonlinear and stochastic dynamics in the heart. Physics Reports, 543(2), 61-162. doi:10.1016/j.physrep.2014.05.002Qu, Z., Garfinkel, A., Chen, P.-S., & Weiss, J. N. (2000). Mechanisms of Discordant Alternans and Induction of Reentry in Simulated Cardiac Tissue. Circulation, 102(14), 1664-1670. doi:10.1161/01.cir.102.14.1664Dharmaprani, D., Dykes, L., McGavigan, A. D., Kuklik, P., Pope, K., & Ganesan, A. N. (2018). Information Theory and Atrial Fibrillation (AF): A Review. Frontiers in Physiology, 9. doi:10.3389/fphys.2018.00957Schotten, U., Dobrev, D., Platonov, P. G., Kottkamp, H., & Hindricks, G. (2016). Current controversies in determining the main mechanisms of atrial fibrillation. Journal of Internal Medicine, 279(5), 428-438. doi:10.1111/joim.12492Yin, R., Fu, Y., Yang, Z., Li, B., Pen, J., & Zheng, Z. (2017). Fibrillatory wave amplitude on transesophageal ECG as a marker of left atrial low-voltage areas in patients with persistent atrial fibrillation. Annals of Noninvasive Electrocardiology, 22(4), e12421. doi:10.1111/anec.12421Pourafkari, L., Baghbani-Oskouei, A., Aslanabadi, N., Tajlil, A., Ghaffari, S., Sadigh, A. M., … Nader, N. D. (2018). Fine versus coarse atrial fibrillation in rheumatic mitral stenosis: The impact of aging and the clinical significance. Annals of Noninvasive Electrocardiology, 23(4), e12540. doi:10.1111/anec.12540Nault, I., Lellouche, N., Matsuo, S., Knecht, S., Wright, M., Lim, K.-T., … Haïssaguerre, M. (2009). Clinical value of fibrillatory wave amplitude on surface ECG in patients with persistent atrial fibrillation. 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The effectiveness of a child day-care program in child welfare services

Family support initiatives aimed at guaranteeing children's rights and preserving the family are undergoing extensive diversification, to meet the specific needs and strengths of families. Child day-care initiatives constitute a novel approach in child welfare services, as a way to complement family service for at-risk families. They are delivered in a child-group format and follow a psycho-educational methodology. This study analyzed the impact of a novel child day-care program on children's quality of life, adjustment and development, and explored the moderating role of different child and family dimensions on the program's impact. For this purpose, we followed a pretest-posttest evaluation with a control group (N=83). The results showed improvements in different facets of children's quality of life, as well as a positive impact in other adjustment and developmental dimensions, such as social skills, internalizing problems, and intelligence. Interaction effects were found between internalizing problems and children's sex, and between academic competence and family risk level. In conclusion, this article brings the first wave of evidence about the effectiveness of child day-care programs for supporting at-risk children from a preservation approach. Practical implications for child welfare services are discussed.Ministerio de Economía y Competitividad de España EDU2013-41441-P

Proyecto de creación y funcionamiento del departamento de recursos humanos para la Asociación de Ahorro, Crédito y Servicios de los mercados de Occidente de Responsabilidad Limitada COOP-1 de R.L

En la actualidad las empresas deben de ser capaces de dar respuestas a los cambios que experimenten la sociedad en general y el mundo laboral en particular. Ninguna empresa funciona sin recursos humanos, este sin duda es el más complejo dentro de cualquier organización por su diversidad; por lo tanto, es necesario gestionarlo adecuadamente para que cada integrante de la empresa contribuya en el logro de los objetivos. La importancia del departamento de RRHH está dada por sus funciones (el reclutamiento, la selección, capacitación, remuneración del personal, entre otros) y el eficiente desarrollo de estas

DIDÁCTICA DEL AULA INVERTIDA Y LA ENSEÑANZA DE FÍSICA EN LA UNIVERSIDAD TÉCNICA DE AMBATO

El presente documento tiene como objeto utilizar el aula invertida o flipped classroom como una estrategia para mejorar los aprendizajes en los estudiantes, dando lugar a un auto aprendizaje y al desarrollo de capacidades de investigación, observación, reflexión, análisis, interpretación, síntesis en la adquisición de sus propios conocimientos. Por otro lado el docente se convierte en planificador de los materiales que investiga el estudiante en casa y facilitador en el aula, donde se abren foros y discusiones para aclarar las inquietudes y dudas de lo aprendido. La metodología para determinar si en la carrera de Ingeniería Industrial en Procesos de Automatización de la Universidad Técnica de Ambato se aplica el auto aprendizaje, se realizó una encuesta a profesores y estudiantes, observándose el desconocimiento de la estrategia del aula invertida, por lo tanto se considera que es necesario diseñar y planificar una clase utilizando esta estrategia, la misma que se convertirá en un sistema de acciones centrado en los interés de los estudiantes y el empoderamiento de su conocimiento.PALABRAS CLAVE: Aula invertida; didáctica; enseñanza; aprendizaje.DIDACTICS OF THE INVERTED CLASSROOM AND PHYSICS TEACHING AT THE TECHNICAL UNIVERSITY OF AMBATOABSTRACTThe purpose of this document is to use the inverted classroom or flipped classroom as a strategy to improve student learning, leading to self-learning and the development of research, observation, reflection, analysis, and interpretation and synthesis skills in knowledge self-acquisition. On the other hand the teacher becomes a planner of the materials researched by the student at home and facilitator in the classroom, where forums and discussions are opened to clarify the concerns and doubts of what was learned. The methodology to determine if in the Industrial Engineering course in Automation Processes of the Technical University of Ambato the self-learning is applied, a survey was made to professors and students, observing the ignorance of the inverted classroom strategy, therefore considers that it is necessary to design and plan a class using this strategy, which will become a system of actions focused on the interests of students and the empowerment of their knowledge.KEYWORDS: Flipped classroom; didactics; teaching; learning

Estudio Comparativo De Las Metodologías De Análisis Forense Informático Para La Examinación De Datos En Medios Digitales

The aim of this research is to compare the different standards and methodologies of computer forensic analysis used in the examination of data in digital media. The research was developed based on the scientific method, and a standard and two analysis methodologies were specifically used, which were applied to ten researchers. The analysis variables were based on the feasibility of use and on the time of extracting information from the computer. Among the comparison results of the different methodologies analyzed, it was determined that for the Methodology UNE 71506: 2013, 60% of the researchers used it due to the feasibility of use because it is made up of a robust process (contains the most detailed steps of computer forensics). Reliable and applicable in any field necessarily supervised by specialists working in the area, compared to the National Institute of Standards and Technology that selected 30%, Integrated Digital Investigation Process 10%. Regarding the time of analysis in the examination of digital media with different methodologies (Case study: Extraction of a file of 100 Mb, of a hard disk of 20 Gb in off mode. It is revealed that in the UNE 71506: 2013 it took less than 1 hour compared to the National Institute of Standards and Technology, which took between 1 and less than 2 hours, the Integrated Digital Investigation Process, which lasted longer than 3 hours. In addition, with the use of the Methodology UNE 71506: 2013, it was possible to have greater feasibility in the examination of digital media, since it is composed of four stages such as the preservation, acquisition, analysis and presentation of information results

Análisis Comparativo De Herramientas Forenses Informáticas Para La Realización De Peritajes En Medios Digitales

This paper focuses on making a comparison of the different computer forensic tools used in the performance of data surveys in digital media. The research was developed based on the method of weighting by criteria (scientific and descriptive study). In this study, specifically four computer forensic tools were used and evaluated by six criteria for the selection of them, and they were chosen based on ISO 9126:1998. Based on the comparison, the results of the four computer forensic tools were analyzed. It was determined that for the different criteria (Case study: Clone of 500 Gb hard disk in off mode), the HD Clone and XWay Forensics tools obtained 84.62% of acceptability, compared to Norton Ghost that obtained a contribution of 69.23% and the tool EnCase with a score of 58.46% to obtain the cloning of the disks. In addition, with the use of ISO 9126: 1998, greater portability, reliability of the results, acquisition cost of the tool, ease of use and application, greater operational capacity and support for the tool was achieved in the cloning of digital media. This is attributed to the fact that it is composed of six evaluation criteria as mentioned above

Incidencia del Software Educativo en el proceso de enseñanza-aprendizaje de la Matemática

The teaching-learning process of Mathematics is complex due to its level of abstraction, making it a challenge for the strategies and didactic resources used by teachers, since the goal is to achieve an adequate academic level in the students, for this it results evident the use of technology since nowadays they play a leading role in society, for that reason the research had as intent the improvement of the learning of the rational numbers of the students of the Educational Unit "Benito Juárez", through the technological resource didactic based on the application of a Mathematical Software. The design of the research is quasi-experimental, correlational-explanatory, the "t" test for independent samples was used to contrast the hypothesis. For data collection, the survey and a test were used that were validated to ensure reliability, the data were analyzed using descriptive statistics. The important results were: (a) better academic performance of the sayers of the experimental group as opposed to the group that did not use it, (b) acceptance and motivation by the didactic resource (c) put into practice their cognitive and motor skills. Therefore, the research provided evidence to use the Mathematical Software as a suitable didactic technological resource for a meaningful learning of Mathematics

Diagnosing hospital bacteraemia in the framework of predictive, preventive and personalised medicine using electronic health records and machine learning classifiers

Background The bacteraemia prediction is relevant because sepsis is one of the most important causes of morbidity and mortality. Bacteraemia prognosis primarily depends on a rapid diagnosis. The bacteraemia prediction would shorten up to 6 days the diagnosis, and, in conjunction with individual patient variables, should be considered to start the early administration of personalised antibiotic treatment and medical services, the election of specific diagnostic techniques and the determination of additional treatments, such as surgery, that would prevent subsequent complications. Machine learning techniques could help physicians make these informed decisions by predicting bacteraemia using the data already available in electronic hospital records. Objective This study presents the application of machine learning techniques to these records to predict the blood culture’s outcome, which would reduce the lag in starting a personalised antibiotic treatment and the medical costs associated with erroneous treatments due to conservative assumptions about blood culture outcomes. Methods Six supervised classifiers were created using three machine learning techniques, Support Vector Machine, Random Forest and K-Nearest Neighbours, on the electronic health records of hospital patients. The best approach to handle missing data was chosen and, for each machine learning technique, two classification models were created: the first uses the features known at the time of blood extraction, whereas the second uses four extra features revealed during the blood culture. Results The six classifiers were trained and tested using a dataset of 4357 patients with 117 features per patient. The models obtain predictions that, for the best case, are up to a state-of-the-art accuracy of 85.9%, a sensitivity of 87.4% and an AUC of 0.93. Conclusions Our results provide cutting-edge metrics of interest in predictive medical models with values that exceed the medical practice threshold and previous results in the literature using classical modelling techniques in specific types of bacteraemia. Additionally, the consistency of results is reasserted because the three classifiers’ importance ranking shows similar features that coincide with those that physicians use in their manual heuristics. Therefore, the efficacy of these machine learning techniques confirms their viability to assist in the aims of predictive and personalised medicine once the disease presents bacteraemia-compatible symptoms and to assist in improving the healthcare economy