Indoor and outdoor carbon monoxide concentration relationships at different microenvironments in the Athens area.

Simultaneous measurements of indoor and outdoor carbon monoxide (CO) concentrations conducted at two different microenvironments in Athens, Greece, using a non-dispersive infrared analyzer, are described in this paper. The two selected microenvironments, an office and a public school, were located in the vicinity of two streets with heavy traffic, near the center of Athens. A statistical correlation analysis of indoor concentration levels with outdoor concentrations monitored at the school and at the office, as well as with meteorological parameters and outdoor concentrations monitored at a fixed monitoring site, was conducted. Hourly indoor concentrations at the office and at the school showed a significant positive correlation with outdoor concentrations measured at both measurement locations (with correlation coefficient values R=0.74 and R=0.83 respectively) and at the fixed site (with R=0.70 and R=0.67 respectively). The correlation between indoor and outdoor concentrations was even better when hourly concentrations averaged over a 4 h period were considered (correlation coefficient values between indoor and outdoor concentrations measured at the office and at the school were R=0.85 and R=0.92 respectively and the correlation coefficient value between indoor and outdoor fixed site concentrations was R=0.75 for both sites). Mean hourly outdoor concentrations at the fixed monitoring site explained approximately 56% (R=0.75) of the variation of outdoor concentrations at the office and approximately 68 % (R=0.83) of the variation of outdoor concentrations at the school. The mean daily indoor to outdoor (I/O) ratio ranged between 0.74 and 1.00 at the office and between 0.53 and 0.89 at the school.

Exposure to carbon monoxide in the Athens urban area during commuting.

An extensive survey has been designed to provide detailed information on carbon monoxide (CO) concentration in the main transport modes and along heavy traffic routes in the Athens urban area. Specifically the study identifies the main factors affecting CO exposure during commuting. Several portable, electrochemical CO monitors (Solomat's MPM4100), were used to record the in-vehicle CO concentrations every 15 s. Measurements were performed during rush hour periods. Field monitoring was conducted in summer 1998 and winter 1998-1999. Exposure estimates were compared to WHO guidelines. The findings showed that the mean CO level over trips of 30 min was 21.4 ppm for private car against 10.4, 9.6, 4 and 11.5 ppm for bus, trolley, electric train and pedestrians, respectively. Transport mode, route, monitoring period and season had a significant influence on the measured CO concentrations. The study points out the importance of microenvironmental monitoring, instead of using fixed-site data in assessing commuter's CO exposure.

Detección universal de hipoacusias en recién nacidos / Universal detection of hearing loss in newborns

El objetivo de este trabajo de investigación es demostrar la importancia de la detección temprana de hipoacusias en recién nacidos, para evitar posteriores alteraciones linguisticas, sociales y cognitivas en los niños, realizando para tal fin screening universal y búsqueda activa de alteraciones auditivas en neonatos. Se aplicaron métodos subjetivos como también electrofisiológicos, con una prevalencia de hipoacusia neurosensorial bilateral severa o profunda del 2,5 al 3 por ciento. Los resultados obtenidos demostraron que si bien existen diferencias de opinión considerables en relación a especificidad y sensibilidad de las téncias disponibles, un examen subjetivo aplicado en el momento exacto y por profesionales capacitados nos ofrece también alto grado de especificidad y sensibilidad como primer método de rastreo

An artificial neural network that uses eye-tracking performance to identify patients with schizophrenia.

Several researchers have underscored the importance of precise characterization of eye-tracking dysfunction (ETD) in patients with schizophrenia. This biological trait appears to be useful in estimating the probability of genetic recombination in an individual, so it may be helpful in linkage studies. This article describes a nonlinear computational model for using ETD to identify schizophrenia. A back-propagation neural network (BPNN) was used to classify schizophrenia patients and normal control subjects on the basis of their eye-tracking performance. Better classification results were obtained with BPNN than with a linear computational model (discriminant analysis): a priori predictions were approximately 80 percent correct. These results suggest, first, that eye-tracking patterns can be useful in distinguishing patients with schizophrenia from a normal comparison group with an accuracy of approximately 80 percent. Second, parallel distributed processing networks are able to detect higher order nonlinear relationships among predictor quantitative measurements of eye-tracking performance.