BackgroundThe transmission of the hepatitis B virus (HBV) is parenteral, sexual and perinatal. Prevention of vertical transmission of HBV is extremely important because HBV infection in early life usually results in a chronic carrier State.MethodsA descriptive seroepidemiological study of hepatitis B virus and its effects on hematological parameters was investigated in pregnant women attending antenatal clinic of LAUTECH Teaching Hospital, Osogbo, Nigeria. 200 venous samples were subjected to full blood count and its sera were subjected to enzyme–linked immunosorbent assay for the detection of surface antigen of hepatitis B virus.ResultsPrevalence rate of 16.5% was obtained for hepatitis B surface antigen in pregnant women. The highest HBsAg prevalence rate recorded was 23.3% for pregnant women between aged 30–34 years while the lowest recorded was zero percent for those aged greater than 40 years. RBC, WBC, neutrophil, hemoglobin lymphocyte and platelet counts have no significant effects on HBsAg positivity of pregnant women (p = 0.801). There was no significant difference in HBsAg positivity in relation to maternal age, gravidity, gestational age, family type, level of education and occupation (p = 0.073). Among the potential risk factors, there was significant difference in HBsAg positivity in the pregnant women in relation to their history of HBV vaccination (p = 0.039).ConclusionsWe advocate universal free screening of pregnant women as the endemicity of HBV infections is thus being propagated.

Emotions play an important role in human cognition, perception, decision making, and interaction. This paper presents a six-layer biologically inspired feedforward neural network to discriminate human emotions from EEG.

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Coping with stress has shown to be able to avoid many complications in medical condition. In this paper we present an alternative method in analyzing and understanding stress using the four basic emotions of happy, calm, sad and fear as our basis function. Electroencephalogram (EEG) signals were captured from the scalp of the brain and measured in responds to various stimuli from the four basic emotions to stimulating stress base on the IAPS emotion stimuli. Features from the EEG signals were extracted using the Kernel Density Estimation (KDE) and classified using the Multilayer Perceptron (MLP), a neural network classifier to obtain accuracy of the subject's emotion leading to stress. Results have shown the potential of using the basic emotion basis function to visualize the stress perception as an alternative tool for engineers and psychologist.

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