Determining the state of truthfulness and falsehood by analyzing the acquired EEG signals

Detection of deception is particular importance for the criminal case and cognitive behaviors of individual. To understanding criminal behavior, extracting the characteristic of brain waves have obviously crucial. According to hypothesis, particularly prefrontal lobes associated with the deception. This paper alleged to understanding the relationship between deception and truth from frontal lobe during some specific tasks by mapping their EEG signals. In the present study, multiplayer neural network are used for bio-signal classification to diversify between patterns of lie and truth types of EEG classes with the accuracy of around 96%. Brain activity have been captured and characterized with EEG by focusing alpha waves. During the test, lie detection identified and especially focus to detect lie in individual subjects, rather than group averages. In this research, the classification methods applied and EEG machine differentiated the specific patterns of brain activity from frontal lobes associated with deception and truth. The responses from the 3 subjects was discriminated correctly with 99%. The ranges of accuracy of test from three subjects was between 88% to 96%, there was an exception in round three with subject three with 46%. While the participants were playing with Pokemon card, alpha waves were collected successfully. © 2016 IEEE

Epidemiology and outcomes of hospital-acquired bloodstream infections in intensive care unit patients: the EUROBACT-2 international cohort study

Purpose In the critically ill, hospital-acquired bloodstream infections (HA-BSI) are associated with significant mortality. Granular data are required for optimizing management, and developing guidelines and clinical trials. Methods We carried out a prospective international cohort study of adult patients (≥ 18 years of age) with HA-BSI treated in intensive care units (ICUs) between June 2019 and February 2021. Results 2600 patients from 333 ICUs in 52 countries were included. 78% HA-BSI were ICU-acquired. Median Sequential Organ Failure Assessment (SOFA) score was 8 [IQR 5; 11] at HA-BSI diagnosis. Most frequent sources of infection included pneumonia (26.7%) and intravascular catheters (26.4%). Most frequent pathogens were Gram-negative bacteria (59.0%), predominantly Klebsiella spp. (27.9%), Acinetobacter spp. (20.3%), Escherichia coli (15.8%), and Pseudomonas spp. (14.3%). Carbapenem resistance was present in 37.8%, 84.6%, 7.4%, and 33.2%, respectively. Difficult-to-treat resistance (DTR) was present in 23.5% and pan-drug resistance in 1.5%. Antimicrobial therapy was deemed adequate within 24 h for 51.5%. Antimicrobial resistance was associated with longer delays to adequate antimicrobial therapy. Source control was needed in 52.5% but not achieved in 18.2%. Mortality was 37.1%, and only 16.1% had been discharged alive from hospital by day-28. Conclusions HA-BSI was frequently caused by Gram-negative, carbapenem-resistant and DTR pathogens. Antimicrobial resistance led to delays in adequate antimicrobial therapy. Mortality was high, and at day-28 only a minority of the patients were discharged alive from the hospital. Prevention of antimicrobial resistance and focusing on adequate antimicrobial therapy and source control are important to optimize patient management and outcomes