From Simulated Mixtures to Simulated Conversations as Training Data for End-to-End Neural Diarization

End-to-end neural diarization (EEND) is nowadays one of the most prominent research topics in speaker diarization. EEND presents an attractive alternative to standard cascaded diarization systems since a single system is trained at once to deal with the whole diarization problem. Several EEND variants and approaches are being proposed, however, all these models require large amounts of annotated data for training but available annotated data are scarce. Thus, EEND works have used mostly simulated mixtures for training. However, simulated mixtures do not resemble real conversations in many aspects. In this work we present an alternative method for creating synthetic conversations that resemble real ones by using statistics about distributions of pauses and overlaps estimated on genuine conversations. Furthermore, we analyze the effect of the source of the statistics, different augmentations and amounts of data. We demonstrate that our approach performs substantially better than the original one, while reducing the dependence on the fine-tuning stage. Experiments are carried out on 2-speaker telephone conversations of Callhome and DIHARD 3. Together with this publication, we release our implementations of EEND and the method for creating simulated conversations.Comment: Submitted to Interspeech 202

Effects of Methotrexate on IL-6alphar, VCAM-1 and NF Kappa B Expression in a Rat Model of Metabolic Syndrome

Background: In this study, we used Methotrexate (Mtx) to examine the role of immunomodulation on the activation of IL-6 and VCAM-1, which could generate a microenvironment that supports cardiovascular remodelling.Methods: Male WKY and SHR rats were separated into five groups: Control, FFR: WKY rats receiving a 10% (w/v) fructose solution during all 12 weeks, SHR, FFHR: SHR receiving a 10% (w/v) fructose solution during all 12 weeks and FFHR+Mtx (0,3 mg/kg intraperitoneal one injection per day week for 6 weeks) (n = 8 per group). Metabolic variables and systolic blood pressure were measured. Cardiac and vascular remodelling was also evaluated. To assess this, IL-6R and VCAM-1 immunostaining techniques were used.Results: The FFHR experimental model developed metabolic syndrome, vascular and cardiac remodelling, and vascular inflammation because of increased expression of IL-6 and VCAM-1. Chronic treatment with Mtx completely or partiality reversed the variables studied.Conclusions: The results demonstrated an impact on immunomodulation after mtx treatment, which included a reduction in vascular inflammation and a favourable reduction in metabolic and structural parameters.Fil: Renna, Nicolas Federico. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto de Medicina y Biología Experimental de Cuyo; Argentina. Universidad Nacional de Cuyo. Facultad de Ciencias Médicas; ArgentinaFil: Ramirez, Jésica M.. Universidad Nacional de Cuyo. Instituto de Genética; ArgentinaFil: García, Rodrigo Damián. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto de Medicina y Biología Experimental de Cuyo; Argentina. Universidad Nacional de Cuyo. Facultad de Ciencias Médicas; ArgentinaFil: Diez, Emiliano Raúl. Universidad Nacional de Cuyo. Instituto de Genética; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto de Medicina y Biología Experimental de Cuyo; ArgentinaFil: Miatello, Roberto Miguel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto de Medicina y Biología Experimental de Cuyo; Argentina. Universidad Nacional de Cuyo. Instituto de Genética; Argentin

Playing with your mind

A Brain-Computer Interface (BCI) is a communication system between the brainand a machine like a computer. Some BCI systems have been used to help people withdisabilities and sometimes, with entertainment purposes. In this paper, a BCI-game system is developed. It allows controlling the altitude of a ball inside of a glass pipe according to mental concentration level, which is measured on EEG signals of the user. The system is automatically adjusted to each user, hence, it is not needed any calibration step. Ten subjects participated in the experiments. They achieved effective control of the ball in a few minutes, demonstratingthe feasibility of the BCI-game system.Fil: Rodriguez, Mauro. Universidad Nacional de San Juan. Facultad de Ingeniería. Departamento de Electrónica y Automática. Gabinete de Tecnología Médica; ArgentinaFil: Gimenez, Ramiro. Universidad Nacional de San Juan. Facultad de Ingeniería. Departamento de Electrónica y Automática. Gabinete de Tecnología Médica; ArgentinaFil: Diez, Pablo Federico. Universidad Nacional de San Juan. Facultad de Ingeniería. Departamento de Electrónica y Automática. Gabinete de Tecnología Médica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Avila Perona, Enrique Mario. Universidad Nacional de San Juan. Facultad de Ingeniería. Departamento de Electrónica y Automática. Gabinete de Tecnología Médica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Laciar Leber, Eric. Universidad Nacional de San Juan. Facultad de Ingeniería. Departamento de Electrónica y Automática. Gabinete de Tecnología Médica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Orosco, Lorena Liliana. Universidad Nacional de San Juan. Facultad de Ingeniería. Departamento de Electrónica y Automática. Gabinete de Tecnología Médica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Garces, Agustina. Universidad Nacional de San Juan. Facultad de Ingeniería. Departamento de Electrónica y Automática. Gabinete de Tecnología Médica; Argentin

Assessment of high-frequency steady-state visual evoked potentials from below-the-hairline areas for a brain-computer interface based on Depth-of-Field

Background and Objective: Recently, a promising Brain-Computer Interface based on Steady-State Visual Evoked Potential (SSVEP-BCI) was proposed, which composed of two stimuli presented together in the center of the subject's field of view, but at different depth planes (Depth-of-Field setup). Thus, users were easily able to select one of them by shifting their eye focus. However, in that work, EEG signals were collected through electrodes placed on occipital and parietal regions (hair-covered areas), which demanded a long preparation time. Also, that work used low-frequency stimuli, which can produce visual fatigue and increase the risk of photosensitive epileptic seizures. In order to improve the practicality and visual comfort, this work proposes a BCI based on Depth-of-Field using the high-frequency SSVEP response measured from below-the-hairline areas (behind-the-ears). Methods: Two high-frequency stimuli (31 Hz and 32 Hz) were used in a Depth-of-Field setup to study the SSVEP response from behind-the-ears (TP9 and TP10). Multivariate Spectral F-test (MSFT) method was used to verify the elicited response. Afterwards, a BCI was proposed to command a mobile robot in a virtual reality environment. The commands were recognized through Temporally Local Multivariate Synchronization Index (TMSI) method. Results: The data analysis reveal that the focused stimuli elicit distinguishable SSVEP response when measured from hairless areas, in spite of the fact that the non-focused stimulus is also present in the field of view. Also, our BCI shows a satisfactory result, reaching average accuracy of 91.6% and Information Transfer Rate (ITR) of 5.3 bits/min. Conclusion: These findings contribute to the development of more safe and practical BCI.Fil: Floriano, Alan. Universidade Federal do Espírito Santo; BrasilFil: Delisle Rodriguez, Denis. Universidade Federal do Espírito Santo; BrasilFil: Diez, Pablo Federico. Universidad Nacional de San Juan. Facultad de Ingeniería. Departamento de Electrónica y Automática. Gabinete de Tecnología Médica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan; ArgentinaFil: Bastos Filho, Teodiano Freire. Universidade Federal do Espírito Santo; Brasi

Adaptive Filtering for Epileptic Event Detection in the EEG

Purpose The development of online seizure detection techniques as well as prediction methods are very critical. Patient quality of life could improve signifcantly if the beginning of a seizure could be predicted or detected early. Methods This paper proposes a method to automatically detect epileptic seizures based on adaptive flters and signal averaging. The process was applied to 425 h of epileptic EEG records from CHB-MIT EEG database. The developed algorithm does not require any training since it is simple and involves low processing time. Therefore, it can be implemented in real time as well as ofine. Results Three thresholds were evaluated and calculated as 10, 20 and 30 times the median value of ST(n). The threshold of 20 showed the best relation between SEN and SPE. In this case, these indexes reached average values, across all the patients, of 90.3% and 73.7% respectively. Conclusions The proposed method has several strengths, for example: that no training is required due to the automatic adaptation to the threshold to each new EEG record. The algorithm could be implemented in real time. It is simple owing to its low processing time which makes it suitable for the analysis of long-term records and a large number of channels. The system could be implemented on electronic devices for warning purposes (of the seizure onset). It employs methods to process signals that were not used with epileptic seizure detection in EEG, such as in the case of adaptive predictive flters.Fil: Garces Correa, Maria Agustina. Universidad Nacional de San Juan. Facultad de Ingeniería. Departamento de Electrónica y Automática. Gabinete de Tecnología Médica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan; ArgentinaFil: Orosco, Lorena Liliana. Universidad Nacional de San Juan. Facultad de Ingeniería. Departamento de Electrónica y Automática. Gabinete de Tecnología Médica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan; ArgentinaFil: Diez, Pablo Federico. Universidad Nacional de San Juan. Facultad de Ingeniería. Departamento de Electrónica y Automática. Gabinete de Tecnología Médica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan; ArgentinaFil: Laciar Leber, Eric. Universidad Nacional de San Juan. Facultad de Ingeniería. Departamento de Electrónica y Automática. Gabinete de Tecnología Médica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan; Argentin

Caracterización y cuantificación de células progenitoras endoteliales de ratas espontáneamente hipertensas alimentadas con fructosa

Objetivo: Examinar cómo se ve afecta la participación de las células progenitoras endoteliales (CPE) por la resistencia a la insulina (IR) asociada a un modelo experimental de síndrome metabólico (SM), generado por la administración crónica de fructosa a ratas espontáneamente hipertensas. Material y métodos: Ratas WKY y SHR, macho, distribuidas en 4 grupos (n=8 c/u): WKY: controles; FFR: WKY recibiendo fructosa en agua de bebida al 10 % (v/v) durante 6 semanas; SHR; FFHR: SHR recibiendo fructosa en agua de bebida al 10 % (v/v) durante 6 semanas. Al finalizar el protocolo se determinó: presión arterial sistólica, variables bioquímicas, índice HOMA, cuantificación por citometría de flujo de los niveles de CPE en sangre periférica y en médula ósea, inmunofluorescencia en cultivo celular, para identificar los marcadores CD34 y VEGFR-2, recuento de colonias de CPE y actividad de NAD(P)H-oxidasa en tejido aórtico. Resultados: Se confirmó el modelo experimental en base a las variables metabólicas analizadas. Se observó una disminución en los niveles de CPE; en sangre periférica y médula ósea, la que se hace más importante en los grupos de animales tratados con fructosa. En estos también hay menor número de colonias de CPE desarrolladas en cultivo celular y presentan un aumento en los niveles de estrés oxidativo, estimado por la actividad de NAD(P)H oxidasa. Conclusión: el SM causado por la administración crónica de fructosa en FFHR ha demostrado generar una disminución en los niveles de CPE, así como en su capacidad funcional. Los mecanismos intracelulares que producen este fenómeno podrían estar desencadenados por el grado de IR que presenta este modelo experimental.Objective: To examine alterations in participation of endothelial progenitor cells (EPC) because of insulin resistance (IR) associated with an experimental model of metabolic syndrome (MS) generated by chronic administration of fructose to spontaneously hypertensive rats (SHR) Material and methods: WKY and SHR rats, male, were distributed into 4 groups (n = 8 c/u): WKY: control; FFR: WKY receiving fructose in drinking water to 10% (v/v) for 6 weeks , SHR; FFHR: SHR receiving fructose in drinking water to 10% (v/v) for 6 weeks. At the end of the protocol the following variables were determined: systolic blood pressure, biochemical variables, HOMA index, levels of EPC quantified by flow cytometry in peripheral blood and bone marrow, immunofluorescence in cell culture to identify markers CD34 and VEGFR-2, EPC colony count and NAD(P)H-oxidase activity in aortic tissue. Results: We confirmed the experimental model based on metabolic variables analyzed. A decrease in the levels of CPE, in peripheral blood and bone marrow, which becomes more important groups of animals treated with fructose was observed .In these groups there are also fewer colonies of developed EPC in cell culture and exhibit an increased levels of oxidative stress, estimated by the activity of NAD(P)H-oxidase. Conclusion: the SM caused by chronic administration of fructose in FFHR has proven to generate a decrease in the levels of CPE, as well as its functional capacity. The intracellular mechanisms that produce this phenomenon could be triggered by the degree of IR presented in this experimental model.Fil: Lembo, Carina. Universidad Nacional de Cuyo. Facultad de Ciencias MédicasFil: Renna, Nicolás Federico. Universidad Nacional de Cuyo. Facultad de Ciencias MédicasFil: Diez, Emiliano Raúl. Universidad Nacional de Cuyo. Facultad de Ciencias MédicasFil: Vazquez-Prieto, Marcela Alejandra. Universidad Nacional de Cuyo. Facultad de Ciencias MédicasFil: Miatello, Roberto. Universidad Nacional de Cuyo. Facultad de Ciencias Médica

A Deep Learning Approach for Robust Detection of Bots in Twitter Using Transformers

© 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other worksDuring the last decades, the volume of multimedia content posted in social networks has grown exponentially and such information is immediately propagated and consumed by a significant number of users. In this scenario, the disruption of fake news providers and bot accounts for spreading propaganda information as well as sensitive content throughout the network has fostered applied researh to automatically measure the reliability of social networks accounts via Artificial Intelligence (AI). In this paper, we present a multilingual approach for addressing the bot identification task in Twitter via Deep learning (DL) approaches to support end-users when checking the credibility of a certain Twitter account. To do so, several experiments were conducted using state-of-the-art Multilingual Language Models to generate an encoding of the text-based features of the user account that are later on concatenated with the rest of the metadata to build a potential input vector on top of a Dense Network denoted as Bot-DenseNet. Consequently, this paper assesses the language constraint from previous studies where the encoding of the user account only considered either the metadatainformation or the metadata information together with some basic semantic text features. Moreover, the Bot-DenseNet produces a low-dimensional representation of the user account which can be used for any application within the Information Retrieval (IR) framewor