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In this study, the main scope was to develop a brain-computer interface (BCI) with the use of PiCar and EEG/ERP devices. Thus, it is aimed to facilitate the lives of people with certain diseases and disabilities. The ultimate goal of this project has been to direct and control a BCI-based PiCar concerning the signals captured via the EEG/ERP device. With the EEG headset, the EMG signals of the gestures (facial expressions) of the participant were captured. With the collected data, filtering and other preprocessing methods were applied to have noise-free signals. In the preprocessing, the detrending method was used to clean the data set which showed a constantly increasing trend, to a certain range, and zero trends. The denoising (Wavelet Denoising) and outlier detection/elimination methods (OneClassSVM) were used for noise elimination. The SMOTE oversampling method was used for data augmentation. Welch's method was used to get band powers from the signals. With the use of augmented data, several machine learning algorithms were applied such as Support Vector Machine, Logistic Regression, Linear Discriminant Analysis, Random forest Classifier, Gradient Boosting Classifier, Multinomial Naive Bayes, Decision tree, K-Nearest Neighbor, and voting classifier. The developed models were used to predict the direction that is passed as an input to PiCar's API. After that, PiCar was controlled concerning the predicted direction with HTTP GET requests. In this project, the OpenBCI headset and the Brainflow library for EEG/EMG signal obtaining and processing were used. Also, the Tkinter library was used for the Graphical user interface and Django for establishing a server on PiCar's brain which is RaspberryPi. © 2022 IEEE. 2-s2.0-85141839049

Introduction and objectives: Eating frequency has been suggested to modify blood pressure. Yet, the results are inconclusive, possibly because eating frequency, particularly meal intake behavior (MIB), does not differentiate between meals and snacks. Hence, the aim of this study was to examine the association between more specifi c MIBs, like the consumption of the three main meals, the intake of forenoon and afternoon meals and snacking between the regular meals, and systolic/diastolic blood pressure (SBP/DBP). Methods: This cross-sectional study includes 1,314 Spanish adults aged 20-79 years. Data collection occurred during cardiovascular health day events organized in four Spanish cities (Madrid, Las Palmas, Seville and Valencia) in 2008. Linear regression analysis was performed to assess the independent association between the mentioned MIBs and SBP/DBP, controlling for several confounders in multiples models. Results: After adjusting for sex, age and individual risk factors, having an afternoon meal was associated with lower SBP (ß -3.91, 95% CI [-6.33, -1.49]) and DBP (ß -2.35, 95% CI [-3.76, -0.94]). This association was attenuated when introducing dietary intake and waist circumference in the predictive models (SBP: ß -2.83, 95% CI [-5.25, -0.40]; DBP: ß -1.67, 95% CI [-3.04, -0.31]), although it still remained signifi cant. None of the other investigated MIBs showed any associations with SBP/DBP. Conclusions: This study suggests that SBP/DBP might be reduced by the intake of an afternoon meal. However, population-based prospective studies are needed in order to confi rm the consequences of the investigated associations on health, Introducción y objetivos: evidencias sugieren que el número de ingestas alimentarias modifi can la presión arterial. Sin embargo, los resultados encontrados no son concluyentes, probablemente debido a que esta conducta relacionada con la ingesta de alimentos (CRIA) no diferencia entre comidas y snacks. Este estudio examina la asociación entre CRIA más específi cas como la realización de las tres comidas principales, de la media mañana, de la merienda y picar entre las comidas regulares, y la tensión arterial sistólica y diastólica (TAS y TAD). Métodos: es un estudio transversal, en el cual fueron incluidos 1.314 españoles (20-79 años). Los datos fueron recogidos en las Jornadas de Salud Cardiovascular en Madrid, Las Palmas, Sevilla y Valencia, durante el año 2008. Se aplicaron análisis de regresión lineal, controlando el efecto de diversos factores de confusión en múltiples modelos. Resultados: después de ajustar por sexo, edad y factores de riesgo individual, tomar la merienda se asoció directamente a menor TAS (ß -3,91, 95% CI [-6,33, -1,49]) y TAD (ß -2,35, 95% CI [-3,76, -0,94]). La introducción del consumo alimentario y la circunferencia de cintura en los modelos predictivos atenuó esta asociación (TAS: ß -2,83, 95% CI [-5,25, -0,40]; TAD: ß -1,67, 95% CI [-3,04, -0,31]). Ninguna de las otras CRIA investigadas mostró asociaciones con TAS y TAD. Conclusiones: el estudio sugiere que tanto la TAS como la TAD podrían verse reducidas mediante la ingesta de la merienda, aunque se requieren estudios adicionales para confi rmar y profundizar en las consecuencias sobre la salud de las asociaciones investigadas

The project PICAR (Cultural landscaPe and human Impact in Circum-mediterranean countries: multidisciplinary Archaeobotanical research for environmental, phylogeographic, climatic and virtual Reconstructions; Programmi di Ricerca Scientifica di Rilevante Interesse Nazionale 2008FJCEF4 - Italy) focuses on cultural landscape reconstructions and on the recognition of plants related to anthropic presence or activities in a territory (collected or cultivated economic plants; useful, including those that are currently neglected, plants; wild synanthropic plants). The focus is on the knowledge of the general response of environmental dynamics to human impact in the past, and on how different environments changed under the pressure of different civilizations. This communication will report some examples of the multidisciplinary archaeobotanical studies that the research team of the laboratory of Modena has carried out in the last years, mainly dealing with contexts from Italian archaeological sites. Pollen and macroremains analyses were and are commonly integrated with archaeological data. This methodology allows comparisons between different times and geographical areas giving new hints to human landscape reconstructions, by comparing in which way humans exploited plant resources in their territories, adapting them to the changing environment under the changing Holocene climate, and by transforming soils and vegetation according to their cultural needs.