Consecuencias legales derivadas de un accidente laboral

Traballo fin de grao (UDC.DER). Dereito. Curso 2014/201

Dark Matter Direct Detection in tt-channel mediator models

We provide a complete reappraisal for the Direct Detection phenomenology of Dark Matter $t$-channel portal models. We provide a complete computation of the loop induced direct detection cross-section for both scalar and fermionic Dark Matter candidates. The results are compared with current and future bounds from direct detection experiments as well as with the requirement of the correct Dark Matter relic density.Comment: 49 pages, 27 figure

Work-rate analysis of substitute players in professional soccer: Analysis of seasonal variations

This study was supported by grants Xunta de Galicia[Abstract]: The aims of this study were to evaluate physical performance of substitute players versus those replaced or completing the entire match, determine physical performance of substitute players across different playing positions and examine variations in match-related running performance in substitute players throughout the entire competitive season. The sample was composed of 943 observations of professional players who participated in the first division of the Spanish League (La Liga) during the 2014-2015 season. The players were divided into three different groups: players who completed the entire match (n = 519), players who were replaced (n = 212) and substitute players (n = 212). Substitute players covered greater distances at medium and high intensity compared to the players who played the entire match and those who were replaced. Position-specific trends indicated that attackers and central midfielder increased the distance covered at high-intensity running compared to their peers who played the whole match. During the competitive season, it was observed that substitute players attained greater match running performance during the mid-season period, allowing them to cover more distance for different variables of running performance compared to the start and end of the season

Growth hormone receptor deficiency is associated with a major reduction in pro-aging signaling, cancer, and diabetes in humans

PMCID: PMC3357623.-- et al.Mutations in growth signaling pathways extend life span, as well as protect against age-dependent DNA damage in yeast and decrease insulin resistance and cancer in mice. To test their effect in humans, we monitored for 22 years Ecuadorian individuals who carry mutations in the growth hormone receptor (GHR) gene that lead to severe GHR and IGF-1 (insulin-like growth factor-1) deficiencies. We combined this information with surveys to identify the cause and age of death for individuals in this community who died before this period. The individuals with GHR deficiency exhibited only one nonlethal malignancy and no cases of diabetes, in contrast to a prevalence of 17% for cancer and 5% for diabetes in control subjects. A possible explanation for the very low incidence of cancer was suggested by in vitro studies: Serum from subjects with GHR deficiency reduced DNA breaks but increased apoptosis in human mammary epithelial cells treated with hydrogen peroxide. Serum from GHR-deficient subjects also caused reduced expression of RAS, PKA (protein kinase A), and TOR (target of rapamycin) and up-regulation of SOD2 (superoxide dismutase 2) in treated cells, changes that promote cellular protection and life-span extension in model organisms. We also observed reduced insulin concentrations (1.4 mU/ml versus 4.4 mU/ml in unaffected relatives) and a very low HOMA-IR (homeostatic model assessment-insulin resistance) index (0.34 versus 0.96 in unaffected relatives) in individuals with GHR deficiency, indicating higher insulin sensitivity, which could explain the absence of diabetes in these subjects. These results provide evidence for a role of evolutionarily conserved pathways in the control of aging and disease burden in humans.This study was funded in part by NIH–National Institute on Aging (NIA) grants AG20642 and AG025135 to V.D.L.; Ted Bakewell (The Bakewell Foundation), the V Foundation for Cancer Research, and a University of Southern California Center for Excellence in Genomic Science pilot grant to V.D.L.; grant 1P30 DK063491to P.C.; the Institute of Endocrinology, Metabolism and Reproduction, Ecuador; and the Intramural Research Program of the NIH-NIA.Peer Reviewe

A distance correlation approach for optimum multiscale selection in 3D point cloud classification

[Abstract] Supervised classification of 3D point clouds using machine learning algorithms and handcrafted local features as covariates frequently depends on the size of the neighborhood (scale) around each point used to determine those features. It is therefore crucial to estimate the scale or scales providing the best classification results. In this work, we propose three methods to estimate said scales, all of them based on calculating the maximum values of the distance correlation (DC) functions between the features and the label assigned to each point. The performance of the methods was tested using simulated data, and the method presenting the best results was applied to a benchmark data set for point cloud classification. This method consists of detecting the local maximums of DC functions previously smoothed to avoid choosing scales that are very close to each other. Five different classifiers were used: linear discriminant analysis, support vector machines, random forest, multinomial logistic regression and multilayer perceptron neural network. The results obtained were compared with those from other strategies available in the literature, being favorable to our approach.Xunta de Galicia; ED431G 2019/01Ministerio de Ciencia, Innovación y Universidades; MTM2016-76969-PXunta de Galicia; ED431C-2020-14MINECO/AEI/FEDER, UE; MTM2017-89422-

A Proposal for a Modified Moller-Plesset Perturbation Theory

A modified version of the Moller-Plesset approach for obtaining the correlation energy associated to a Hartree-Fock ground state is proposed. The method is tested in a model of interacting fermions that allows for an exact solution. Using up to third order terms improved results are obtained, even more accurate in the limit of loosely bound particles. This result suggests the possible convenience of the scheme for the study of chemical bound problems.Comment: 10 pages, 1 figur

A hybrid bipolar wideband VCO with linearized tuning behaviour for a new generation TTC transponder

This paper presents a wideband voltage-controlled oscillator (VCO) using hybrid technology based on bipolar transistors for a new generation TTC Transponder. The VCO is based on microstrip three-pole combline bandpass filter with just one varactor diode. The bandpass filter is embedded into the feed-back loop to treat as a frequency stabilization element. The VCO delivered 4.63 dBm maximum output power at 3.4 GHz with a current consumption of 17.4 mA for a supply voltage of 3 V and it has a tuning range achieved from 600 MHz being the frequency range from 2.8 GHz to 3.4 GHz. The developed VCO with three pole combline filter is experimentally demonstrated at 3.4 GHz with a phase noise of − 126 dBc/Hz at 1 MHz offset frequency. In addition, over this frequency range, all the phase noises measured at 1 MHz are better than −118 dBc/Hz.This work has been realized thanks to the financing of Thales Alenia Space España, the Spanish Ministry of Economy and Competitiveness, the European Regional Development Fund (ERDF/FEDER) under research projects TEC2014-60283-C3-1-R and TEC2017-88242-C3-1-R, “SUPPORT AND CONSULTING IN THE TTC&RF ACTIVE AREA” from Thales Alenia Space in Spain

Uterine contractile efficiency indexes for labor prediction: a bivariate approach from multichannel electrohysterographic records

[EN] Labor prediction is one of the most challenging goals in obstetrics, mainly due to the poor understanding of the factors responsible for the onset of labor. The electrohysterogram (EHG) is the recording of the myoelectrical activity of myometrial cells and has been shown to provide relevant information on the electrophysiological state of the uterus. This information could be used to obtain more accurate labor predictions than those of the currently used techniques, such as the Bishop score, tocography or biochemical markers. Indeed, a number of efforts have already been made to predict labor by this method, separately characterizing the intensity, the coupling degree of the EHG signals and myometrial cell excitability, these being the cornerstones on which contraction efficiency is built. Although EHG characterization can distinguish between different obstetric situations, the reported results have not been shown to provide a practical tool for the clinical detection of true labor. The aim of this work was thus to define and calculate indexes from multichannel EHG recordings related to all the phenomena involved in the efficiency of uterine myoelectrical activity (intensity, excitability and synchronization) and to combine them to form global efficiency indexes (GEI) able to predict delivery in less than 7/14 days. Four EHG synchronization indexes were assessed: linear correlation, the imaginary part of the coherence, phase synchronization and permutation cross mutual information. The results show that even though the synchronization and excitability efficiency indexes can detect increasing trends as labor approaches, they cannot predict labor in less than 7/14 days. However, intensity seems to be the main factor that contributes to myometrial efficiency and is able to predict labor in less than 7/14 days. All the GEls present increasing monotonic trends as pregnancy advances and are able to identify (p < 0.05) patients who will deliver in less than 7/14 days better than single channel and single phenomenon parameters. The GEI based on the permutation cross mutual information shows especially promising results. A simplified EHG recording protocol is proposed here for clinical practice, capable of predicting deliveries in less than 7/14 days, consisting of 4 electrodes vertically aligned with the median line of the uterus. (C) 2018 Elsevier Ltd. All rights reserved.The authors are grateful to Zhenhu Liang, of the Yanshan University, who provided essential information for computing the PLV and NPCMI synchronization indexes. This work was supported by the Spanish Ministry of Economy and Competitiveness and the European Regional Development Fund (DPI2015-68397-R, MINECO/FEDER).Mas-Cabo, J.; Ye Lin, Y.; Garcia-Casado, J.; Alberola Rubio, J.; Perales Marín, AJ.; Prats-Boluda, G. (2018). Uterine contractile efficiency indexes for labor prediction: a bivariate approach from multichannel electrohysterographic records. Biomedical Signal Processing and Control. 46:238-248. https://doi.org/10.1016/j.bspc.2018.07.018S2382484

Design and Assessment of a Robust and Generalizable ANN-Based Classifier for the Prediction of Premature Birth by means of Multichannel Electrohysterographic Records

[EN] Preterm labor is one of the major causes of neonatal deaths and also the cause of significant health and development impairments in those who survive. However, there are still no reliable and accurate tools for preterm labor prediction in clinical settings. Electrohysterography (EHG) has been proven to provide relevant information on the labor time horizon. Many studies focused on predicting preterm labor by using temporal, spectral, and nonlinear parameters extracted from single EHG recordings. However, multichannel analysis, which includes information from the whole uterus and about coupling between the recording areas, may provide better results. The cross validation method is often used to design classifiers and evaluate their performance. However, when the validation dataset is used to tune the classifier hyperparameters, the performance metrics of this dataset may not properly assess its generalization capacity. In this work, we developed and compared different classifiers, based on artificial neural networks, for predicting preterm labor using EHG features from single and multichannel recordings. A set of temporal, spectral, nonlinear, and synchronization parameters computed from EHG recordings was used as the input features. All the classifiers were evaluated on independent test datasets, which were never ¿seen¿ by the models, to determine their generalization capacity. Classifiers¿ performance was also evaluated when obstetrical data were included. The experimental results show that the classifier performance metrics were significantly lower in the test dataset (AUC range 76-91%) than in the train and validation sets (AUC range 90-99%). The multichannel classifiers outperformed the single-channel classifiers, especially when information was combined into mean efficiency indexes and included coupling information between channels. Including obstetrical data slightly improved the classifier metrics and reached an AUC of for the test dataset. These results show promise for the transfer of the EHG technique to preterm labor prediction in clinical practice.This work was supported by the Spanish Ministry of Economy and Competitiveness, the European Regional Development Fund (DPI2015-68397-R, MINECO/FEDER, and RTI2018-094449-A-I00-AR); Generalitat Valenciana (AICO/2019/220); and the VLC/Campus (UPV-FE-2018-B03).Mas-Cabo, J.; Prats-Boluda, G.; Garcia-Casado, J.; Alberola Rubio, J.; Perales Marín, AJ.; 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. https://doi.org/10.1155/2019/5373810S1132019Goldenberg, 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)60074-4Zeitlin, 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:10.1111/1471-0528.12281Fitzpatrick, K., Tuffnell, D., Kurinczuk, J., & Knight, M. (2016). Pregnancy at very advanced maternal age: a UK population-based cohort study. BJOG: An International Journal of Obstetrics & Gynaecology, 124(7), 1097-1106. doi:10.1111/1471-0528.14269Haas, 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.s44048Garfield, R. E., Maner, W. L., Maul, H., & Saade, G. R. (2005). Use of uterine EMG and cervical LIF in monitoring pregnant patients. BJOG: An International Journal of Obstetrics & Gynaecology, 112, 103-108. doi:10.1111/j.1471-0528.2005.00596.xDevedeux, D., Marque, C., Mansour, S., Germain, G., & Duchêne, J. (1993). Uterine electromyography: A critical review. American Journal of Obstetrics and Gynecology, 169(6), 1636-1653. doi:10.1016/0002-9378(93)90456-sChkeir, A., Fleury, M.-J., Karlsson, B., Hassan, M., & Marque, C. (2013). Patterns of electrical activity synchronization in the pregnant rat uterus. BioMedicine, 3(3), 140-144. doi:10.1016/j.biomed.2013.04.007Fuchs, A.-R., Fuchs, F., Husslein, P., & Soloff, M. S. (1984). Oxytocin receptors in the human uterus during pregnancy and parturition. American Journal of Obstetrics and Gynecology, 150(6), 734-741. doi:10.1016/0002-9378(84)90677-xTezuka, N., Ali, M., Chwalisz, K., & Garfield, R. E. (1995). Changes in transcripts encoding calcium channel subunits of rat myometrium during pregnancy. American Journal of Physiology-Cell Physiology, 269(4), C1008-C1017. doi:10.1152/ajpcell.1995.269.4.c1008Honest, H., Bachmann, L., Sundaram, R., Gupta, J., Kleijnen, J., & Khan, K. (2004). The accuracy of risk scores in predicting preterm birth—a systematic review. Journal of Obstetrics and Gynaecology, 24(4), 343-359. doi:10.1080/01443610410001685439Garfield, R. E., & Hayashi, R. H. (1981). Appearance of gap junctions in the myometrium of women during labor. American Journal of Obstetrics and Gynecology, 140(3), 254-260. doi:10.1016/0002-9378(81)90270-2Maner, W. (2003). Predicting term and preterm delivery with transabdominal uterine electromyography. Obstetrics & Gynecology, 101(6), 1254-1260. doi:10.1016/s0029-7844(03)00341-7Fele-Žorž, G., Kavšek, G., Novak-Antolič, Ž., & Jager, F. (2008). A comparison of various linear and non-linear signal processing techniques to separate uterine EMG records of term and pre-term delivery groups. Medical & Biological Engineering & Computing, 46(9), 911-922. doi:10.1007/s11517-008-0350-yDiab, 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.2014.01.009Lucovnik, M., Maner, W. L., Chambliss, L. R., Blumrick, R., Balducci, J., Novak-Antolic, Z., & Garfield, R. E. (2011). Noninvasive uterine electromyography for prediction of preterm delivery. American Journal of Obstetrics and Gynecology, 204(3), 228.e1-228.e10. doi:10.1016/j.ajog.2010.09.024Acharya, 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., 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.2015.01.107Ren, P., Yao, S., Li, J., Valdes-Sosa, P. A., & Kendrick, K. M. (2015). Improved Prediction of Preterm Delivery Using Empirical Mode Decomposition Analysis of Uterine Electromyography Signals. PLOS ONE, 10(7), e0132116. doi:10.1371/journal.pone.0132116Bradley, A. P. (1997). The use of the area under the ROC curve in the evaluation of machine learning algorithms. Pattern Recognition, 30(7), 1145-1159. doi:10.1016/s0031-3203(96)00142-2Maner, W. L., & Garfield, R. E. (2007). 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/s10439-006-9248-8Smrdel, A., & Jager, F. (2015). Separating sets of term and pre-term uterine EMG records. Physiological Measurement, 36(2), 341-355. doi:10.1088/0967-3334/36/2/341Aditya, S., & Tibarewala, D. N. (2012). Comparing ANN, LDA, QDA, KNN and SVM algorithms in classifying relaxed and stressful mental state from two-channel prefrontal EEG data. International Journal of Artificial Intelligence and Soft Computing, 3(2), 143. doi:10.1504/ijaisc.2012.049010Li, Q., Rajagopalan, C., & Clifford, G. D. (2014). A machine learning approach to multi-level ECG signal quality classification. Computer Methods and Programs in Biomedicine, 117(3), 435-447. doi:10.1016/j.cmpb.2014.09.002Li, Z., Zhang, Q., & Zhao, X. (2017). Performance analysis of K-nearest neighbor, support vector machine, and artificial neural network classifiers for driver drowsiness detection with different road geometries. International Journal of Distributed Sensor Networks, 13(9), 155014771773339. doi:10.1177/1550147717733391Murthy, H. S. N., & Meenakshi, D. M. (2015). ANN, SVM and KNN Classifiers for Prognosis of Cardiac Ischemia- A Comparison. Bonfring International Journal of Research in Communication Engineering, 5(2), 07-11. doi:10.9756/bijrce.8030Ren, J. (2012). ANN vs. SVM: Which one performs better in classification of MCCs in mammogram imaging. Knowledge-Based Systems, 26, 144-153. doi:10.1016/j.knosys.2011.07.016Maul, H., Maner, W., Olson, G., Saade, G., & Garfield, R. (2004). Non-invasive transabdominal uterine electromyography correlates with the strength of intrauterine pressure and is predictive of labor and delivery. The Journal of Maternal-Fetal & Neonatal Medicine, 15(5), 297-301. doi:10.1080/14767050410001695301Mas-Cabo, J., Prats-Boluda, G., Perales, A., Garcia-Casado, J., Alberola-Rubio, J., & Ye-Lin, Y. (2018). Uterine electromyography for discrimination of labor imminence in women with threatened preterm labor under tocolytic treatment. Medical & Biological Engineering & Computing, 57(2), 401-411. doi:10.1007/s11517-018-1888-yGarfield, R. E., & Maner, W. L. (2007). Physiology and electrical activity of uterine contractions. Seminars in Cell & Developmental Biology, 18(3), 289-295. doi:10.1016/j.semcdb.2007.05.004Ahmed, M., Chanwimalueang, T., Thayyil, S., & Mandic, D. (2016). A Multivariate Multiscale Fuzzy Entropy Algorithm with Application to Uterine EMG Complexity Analysis. Entropy, 19(1), 2. doi:10.3390/e19010002Brennan, M., Palaniswami, M., & Kamen, P. (2001). Do existing measures of Poincare plot geometry reflect nonlinear features of heart rate variability? IEEE Transactions on Biomedical Engineering, 48(11), 1342-1347. doi:10.1109/10.959330Cui, D., Pu, W., Liu, J., Bian, Z., Li, Q., Wang, L., & Gu, G. (2016). A new EEG synchronization strength analysis method: S-estimator based normalized weighted-permutation mutual information. Neural Networks, 82, 30-38. doi:10.1016/j.neunet.2016.06.004Chawla, N. V., Bowyer, K. W., Hall, L. O., & Kegelmeyer, W. P. (2002). SMOTE: Synthetic Minority Over-sampling Technique. Journal of Artificial Intelligence Research, 16, 321-357. doi:10.1613/jair.953Bottou, L. (2012). Stochastic Gradient Descent Tricks. Neural Networks: Tricks of the Trade, 421-436. doi:10.1007/978-3-642-35289-8_25Lim, K., Butt, K., & Crane, J. M. (2018). No. 257-Ultrasonographic Cervical Length Assessment in Predicting Preterm Birth in Singleton Pregnancies. Journal of Obstetrics and Gynaecology Canada, 40(2), e151-e164. doi:10.1016/j.jogc.2017.11.01