128 research outputs found
Electrophysiological Brain-Cardiac Coupling in Train Drivers during Monotonous Driving
Electrophysiological research has previously investigated monotony and the cardiac health of drivers independently; however, few studies have explored the association between the two. As such the present study aimed to examine the impact of monotonous train driving (indicated by electroencephalogram (EEG) activity) on an individual's cardiac health as measured by heart rate variability (HRV). Sixty-three train drivers participated in the present study, and were required to complete a monotonous train driver simulator task. During this task, a 32 lead EEG and a three-lead electrocardiogram were recorded from each participant. In the present analysis, the low (LF) and high frequency (HF) HRV parameters were associated with delta (p < 0.05), beta (p = 0.03) and gamma (p < 0.001) frequency EEG variables. Further, total HRV was associated with gamma activity, while sympathovagal balance (i.e., LF:HF ratio) was best associated fronto-temporal delta activity (p = 0.02). HRV and EEG parameters appear to be coupled, with the parameters of the delta and gamma EEG frequency bands potentially being the most important to this coupling. These relationships provide insight into the impact of a monotonous task on the cardiac health of train drivers, and may also be indicative of strategies employed to combat fatigue or engage with the driving task
ВОЛЬТАМПЕРОМЕТРИЧЕСКАЯ МУЛЬТИСЕНСОРНАЯ СИСТЕМА НА ОСНОВЕ МОДИФИЦИРОВАННЫХ ПОЛИАРИЛЕНФТАЛИДАМИ СТЕКЛОУГЛЕРОДНЫХ ЭЛЕКТРОДОВ ДЛЯ РАСПОЗНАВАНИЯ И ОПРЕДЕЛЕНИЯ ВАРФАРИНА
Voltammetric sensors and sensory system based on glassy carbon electrodes modified by polyarylenephthalides (chlorinated polyphthalidylidenefluorene, polyphthalidylidene diphenyl and brominated polyphthalidylidene diphenyl) were developed for the recognition and determination of warfarin. The electrochemical and analytical characteristics of the sensors were studied. The optimal conditions for recording voltammograms of warfarin oxidation were established: the range of working potentials was 0.5 ÷ 1.2 V, scan rate was 20 mVs-1, the electrode holding time in the analyzed solution was 30s, and the pH of the supporting electrolyte was 6.86 (Na2HPO4 + KH2PO4). Using the values of the slope of the dependence log ip = log v + const (Δlg ip / Δlg v = 0.7 ÷ 0.9), it was found that the rate-controlling step of warfarin oxidation was the depolarizer adsorption on the surface of the polymer modifier. The linear range of the dependence of the maximum of warfarin oxidation peak on the concentration was 0.3×10-6 ÷ 0.5×10-3 М. Using the “added-found” method, the accuracy of determining the warfarin content in the model solutions was evaluated. The relative standard deviation and relative measurements error didn’t exceed 4.63% and 11.1% respectively. By the means of chemometrics methods (principal components analysis and SIMCA) the possibility of the recognition of warfarin preparations without isolating the active substances in dosage forms was shown, which made it possible to distinguish pharmaceutical preparations from the different manufacturers. At the same time, the sample preparation procedure was significantly simplified, and the cost and time of the analysis were reduced. It was also shown that the use of the multisensory system of the “electronic tongue” type significantly increased the percentage of correctly recognized samples in comparison to the registration of voltammograms on the single sensor. The proportion of correctly recognized samples was 97-100%.Keywords: warfarin, voltammetry, polyarylenephthalide, modified electrodes, sensor system(Russian) DOI: http://dx.doi.org/10.15826/analitika.2019.23.4.003R.A. Zilberg, Yu.A. Yarkaeva, D.I. Dubrovsky, L.R. Zagitova, V.N. MaistrenkoBashkir State University, Department of Chemistry,32, Validy Str., Ufa, 450076, Russian FederationРазработаны вольтамперометрические сенсоры и сенсорная система на основе стеклоуглеродных электродов, модифицированных полиариленфталидами – хлорированными полифталидилиденфлуореном, полифталидилидендифенилом и бромированным полифталидилидендифенилом, для распознавания и определения варфарина. Изучены электрохимические и аналитические характеристики сенсоров. Установлены оптимальные условия регистрации вольтамперограмм варфарина: диапазон рабочих потенциалов 0.5 ÷ 1.2 В, скорость развертки потенциалов 20 мВ/с, время выдерживания электрода в анализируемом растворе 30 с, pH фонового электролита 6.86 (Na2HPO4 + KH2PO4). По значениям тангенса угла наклона зависимости lg ip = lg v + const (Δlg ip/Δlg v = 0.7÷ 0.9) установлено, что лимитирующей стадией процесса окисления варфарина является преимущественно адсорбция деполяризатора на поверхности полимерного модификатора. Линейный характер зависимости максимального тока окисления варфарина от концентрации сохраняется в диапазоне 0.3·10-6 ÷ 0.5·10-3 М. При определении содержания варфарина в модельных растворах методом «введено-найдено», относительное стандартное отклонение не превышает 4.6 %, относительная погрешность не превышает 11.1 %. С использованием методов хемометрики: метода главных компонент (МГК) и метода формального независимого моделирования аналогий классов (SIMCA) показана возможность распознавания препаратов варфарина без выделения действующих веществ в лекарственных формах, что позволяет различать лекарственные средства различных производителей. При этом заметно упрощается процедура пробоподготовки, снижаются стоимость и время анализа. Показано, что использование мультисенсорной системы типа «электронный язык» существенно повышает процент правильно распознанных образцов по сравнению с регистрацией вольтамперограмм на одном сенсоре. Доля правильно распознанных образцов составляет 97-100 %.Ключевые слова: варфарин, вольтамперометрия, полиариленфталид, модифицированные электроды, сенсорная системаDOI: http://dx.doi.org/10.15826/analitika.2019.23.4.00
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Screening of desert plants for use against bacterial pathogens in fish
The antibacterial activity of aqueous extracts of 104 desert plant species was studied on the fol- lowing fish bacterial pathogens: Aeromonas hydrophila, Photobacterium damselae subspecies piscicida, Streptococcus iniae, and Vibrio alginolyticus. Seventeen plant species had antibacte- rial activity, as identified by disk diffusion assay. The pathogen P. damselae was sensitive to all 17 active extracts except Peganum harmala and a high inhibitory effect (14-19.5 mm) was pro- duced by Anchusa strigosa, Hammada scoparia, Achillea fragrantissima, Pulicaria crispa and Loranthus acaciae. The pathogens A. hydrophila and V. alginolyticus were inhibited by H. sco- paria, L. acaciae, and P. harmala (7-20.5 mm). The pathogen S. iniae was inhibited by Ochradenus baccatus and Reseda stenostachya (10.5 mm). The benefits of using desert plants as an alternative to conventional antibiotics are discussed
Methodology and initial analysis results for development of non-invasive and hybrid driver drowsiness detection systems
Application of piezofilm movement sensors integrated into the car seat, seat belt and steering wheel was proposed for development of a non-invasive and hybrid systems for detecting driver drowsiness. A car simulator study was designed to collect physiological data for validation of this technology. Methodology for analysis of physiological data, independent assessment of driver drowsiness and development of drowsiness detection algorithm by means of sequential fitting and selection of regression models is presented. Statistical analysis shows that during the episodes of transitions to dangerous levels of drowsiness movement variations recorded by the seat sensors are decreasing. This finding indicates that the piezofilm movement sensors could be used as noninvasive devices for detecting the level of drowsiness on their own or in combination with other physiological signals. © 2007 IEEE
Comparing accuracy of two algorithms for detecting driver drowsiness Single source (EEG) and hybrid (EEG and body movement)
Driver fatigue is acknowledged to have similar effects on driving performance as driving under the influence of alcohol. As such, drowsiness detection systems should prove to be valuable in-vehicle safety measures. There are many algorithms that are currently being developed for this purpose, however, they often utilise a single source of data to detect drowsiness onset. It is anticipated that using hybrid data sources would increase the accuracy of such devices. The objective of this analysis was to compare the performance of a hybrid drowsiness detection algorithm with its single source counterpart. Addition of the body movement data to form a hybrid algorithm improved drowsiness detection performance over its EEG only (single source) counterpart, such that area under the ROC curve values increased from 0.764 (single source) to 0.783 (hybrid). © 2011 IEEE
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