Mechanical Ventilation in Office Buildings and the Sick Building Syndrome. An Experimental and Epidemiological Study

The effects of mechanical ventilation on the sick building syndrome (SBS) were studied in an office building with 2150 employees, where the mechanical ventilation and indoor air quality were commonly blamed for causing symptoms typical of the SBS (nasal, eye, and mucous membrane symptoms, lethargy, skin symptoms and headache). The mechanical ventilation rates in the building were high (mean 26 l/s/person). To test the hypothesis that mechanical ventilation causes the SBS, a controlled experimental study was carried out by shutting off the ventilation in one part of the building and reducing the ventilation rate by 75% and 60% in two areas while leaving one part unaltered as a control. The experimental reduction of the ventilation rate did not alleviate the symptoms. On the contrary, the reduction of the ventilation rate caused a slight but statistically significant relative increase in symptoms (p < 0.05). In the cross-sectional analysis of the baseline data the SBS symptoms did not associate significantly with the ventilation rate (range 7–70 l/s/person). In the linear regression model, a positive correlation was found between temperatures above 22°C and the occurrence of symptoms (p < 0.05). Subjects exposed to environmental tobacco smoke had more symptoms than those not exposed (p < 0.01). Women reported more symptoms than men (p < 0.001). In addition, any prior history of allergic diseases (p < 0.001) and a negative attitude towards the social atmosphere at work (p < 0.001) were significant determinants of the SBS.     

Polarity and fusion of JAR choriocarcinoma cells as assessed by enveloped viral glycoproteins

Twenty-two monkeys (Macaca fascicularis) were utilized in this study. Ten animals were rendered parkinsonian with serial injections of MPTP (1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine). Five of these parkinsonian monkeys received L-dopa/carbidopa treatment, and five animals did not. The remaining twelve animals did not receive MPTP. Eight of these animals received no L-dopa treatment, two animals were treated chronically with L-dopa/carbidopa and two animals received L-dopa/carbidopa only on the day of sacrifice. All animals were given weekly scored neurologic examinations throughout the study. Their movement was quantitated in an activity box. All animals were sacrificed by an overdose of sodium pentobarbital. The parkinsonian animals were sacrificed 107-355 days after their last MPTP injection. The brains were removed and frozen. Punch samples were taken from the caudate and putamen for tissue dopamine determination. Selected areas of the basal ganglia were cut into 20 microns sections for quantitative receptor autoradiography. The density of D1 and D2 receptors was evaluated in the basal ganglia of these animals at the level of the anterior commissure. For the D2 assay, total binding was determined using various concentrations of [3H]spiperone in buffer containing 300 nm mianserin. For the D1 assay, total binding was determined using various concentrations of [3H]SCH-23390. Tissue isotope concentration was determined from the autoradiographs. The MPTP parkinsonian monkeys showed a mean striatal dopamine depletion of 93.5% and a mean clinical score of 9.0. The untreated parkinsonian monkeys demonstrated an increase in the number of D2 sites as compared to controls. This increase was greatest in the lateral putamen.(ABSTRACT TRUNCATED AT 250 WORDS)     

Ray-casting and block model conversion using a spatial index

A spatial index is a data structure designed to facilitate spatial search, exemplified by the point-in-polyhedron inclusion problem. The 3D extensible cell (EXCELL) index is presented together with algorithms for spatial search and for converting a complex polyhedron (boundary representation) into an octree-like block model. We illustrate the techniques by an application to geometric mine modelling and demonstrate the efficiency of the approach by practical experiments.     

Increase in Perceived Odor Emissions with Loading of Ventilation Filters

The development of odor emission rates from EU6 classified glass fiber bag filters was studied in four air-handling units (AHU), and emissions from the same kind of filters with EU3 classified polyester prefilters were studied in two units. The filters were loaded in six AHU in downtown Helsinki. The pressure drop was measured, and the odors of the filters were evaluated by a trained panel under laboratory conditions (T = 20°C, face velocity 1.0 m/s) every sixth week. The odor emissions of simultaneous atmospheric dust samples were also studied. The odor emissions of the filters rose during the first three months to a level where every third person would be dissatisfied. The emissions from coarse prefilters were similar to those from the more efficient filters without prefilters, and the emissions of the main filters were significantly lower if used with prefilters. This result indicates that the prefilters effectively protected the fine filters from odor-causing particles. The results of tests made with atmospheric samples agree with this result. Relative odor emissions were the highest in coarse fractions (> 10.0 μm). The pressure drop increased with the particle mass collected on the ventilation filter, but it did not correlate well with the odor emission of the filter. Thus, pressure drop alone is not an adequate criterion for changing supply air filters when hygienic aspects are a concern.     

Trace element distributions between matte and slag in direct nickel matte smelting

ABSTRACT

Behaviour of trace elements in the nickel matte smelting was studied at 1673 K (1400°C) by equilibration-quenching techniques followed by direct phase analyses using electron probe X-ray microanalysis and laser ablation-inductively coupled plasma-mass spectrometry. The matte-slag samples at silica saturation were equilibrated with SO₂-CO-CO₂-Ar mixtures of fixed p_SO2, p_S2 and p_O2 in order to obtain a pre-determined oxidation degree for the sulphide matte, and thus to generate a targeted iron concentration of the nickel-copper–iron sulphide matte (Ni:Cu = 5, w/w), depending on the slag chemistry. The slag composition was varied from 0 to 2 wt-% K₂O and 0–10 wt-% MgO in silica saturation. The studied trace elements were Co, Ge, Pb, Se and Sn, but also the matte-to-slag distributions of the slag forming fluxing components Mg (MgO) and Si (SiO₂) were determined experimentally. Selenium was the only trace element studied which strongly enriched in the low-iron nickel mattes, and the deportment became larger when the sulphide matte depleted with iron. All the other trace elements behaved in the opposite way.     

The regiospecific position of 18∶1 cis and trans monoenoic fatty acids in milk fat triacylglycerols

TAG of butterfat were fractionated according to the type and degree of unsaturation into six fractions by silver-ion HPLC. The fractions containing TAG with either cis-or trans-monoenoic FA were collected and fractionated further by reversed-phase HPLC to obtain fractions containing cis TAG of ACN:DB (acyl carbon number:double bonds) 48∶1, 50∶1, and 52∶1 as well as trans 48∶1, 50∶1, and 52∶1. The FA compositions of these fractions were elucidated by GC. The MW distribution of each fraction was determined by ammonia negative-ion CI-MS. Each of the [M-H]⁻ parent ions was fractionated further by collision-induced dissociation with argon, which gave information on the location of cis-and trans-FA between the primary and secondary positions of TAG. The results suggest that the sn-positions of the monoenoic cis-and trans-FA depend on the two other FA present in the molecule. With 14∶0 FA in the TAG molecule, the 18∶1 FA in the sn-2 position are mostly present as cis-isomers. When there is no 14∶0 in the TAG molecule, the trans-18∶1 isomers seem to be more common in the sn-2 position. Also when other long-chain FA are present, the trans-isomers are more likely to be located in the secondary (sn-2) position.     

Estimating nutrients and chlorophyll a relationships in Finnish Lakes

We model the response of chlorophyll a-a surrogate for the phytoplankton community volume-to variations in lake total phosphorus (TP) and total nitrogen (TN) concentrations. The model is fitted to a large cross-sectional data set from the Finnish Lake monitoring network. The objective is to support the Finnish Government in identifying management actions to achieve compliance of the chlorophyll a concentration standard with a given confidence level and to provide tools for the estimation of critical (target) loads for nutrients in monitored lakes. We develop a Bayesian hierarchical linear model which combines advantages of both the currently preferred non-hierarchical lake-type-specific linear model and lake-specific linear model fitted separately using data from a single lake. The hierarchical model is less biased at lake-level compared to the lake type model. In contrast to the lake model, it predicts the lake specific chlorophyll a response to nutrients outside the lake specific observational range. The hierarchical model is used to calculate probabilities of chlorophyll a concentration exceeding the standard under different nitrogen and phosphorus concentration combinations. These probabilities can be used to estimate acceptable nitrogen-phosphorus concentration combinations by a lake manager. We discuss how our study can be useful in implementing the European Water Framework Directive.     

On the relative significance of bacteria for the distribution of polychlorinated biphenyls in Arctic Ocean surface waters

This study presents the first field observations of polychlorinated biphenyls (PCB) in bacteria in oceanic waters. To contribute to the limited knowledge of what role bacteria play in the dynamics of hydrophobic organic contaminants (HOCs) in surface seawater, PCB concentrations were measured in bacteria (0.2-2 microm) collected at seven stations in the northern Barents Sea marginal ice zone (MIZ) and the central Arctic Ocean. Concentrations of individual PCB congeners in bacteria were 0.5-5 ng/g oc (organic carbon), which was as high as or higher than PCB concentrations in bulk particulate organic carbon (POC, "phytoplankton"; > 0.7 microm). Considering the relative biomasses of phytoplankton and bacteria, the amount of PCB in bacteria was generally 5-20% of that in phytoplankton, but at two stations the bacterial biomass contained more PCBs than the phytoplankton pool. This study further showed that efficient PCB uptake in bacteria may be described by an apparent equilibrium partitioning model with linear regressions between the organic-carbon-normalized partition coefficient and the octanol-water partition coefficient (log K(bact-oc)-log K(ow)).     

Dichromated Gelatin Reflection Gratings

Abstract

Reflection gratings were recorded in dichromated gelatin by using a non-symmetrical recording geometry. In addition to the primary grating, secondary gratings were also formed, as is generally known. It is found that the secondary gratings assist the structure stability during development in the exposure energy range (50–100) mJ cm^?2. The structure containing these secondary gratings is more rigid than those without and the reflection grating period is more stable during the development process in this exposure energy range, which is most suitable for the transmission grating formation. Secondary gratings also cause unwanted noise, but the noise level is low and the improved stability outweighs the extra noise.     

Estimating printed circuit board assembly times using neural networks

Several production planning tasks in the printed circuit board (PCB) assembly industry involve the estimation of the component placement times for different PCB types and placement machines. This kind of task may be, for example, the scheduling of jobs or line balancing for single or multiple jobs. The simplest approach to time estimation is to let the production time be a linear function of the number of components to be placed. To achieve more accurate results, the model should include more parameters (e.g. the number of different component types, the number of different component shapes, the dimensions of the PCBs, etc.). In this study we train multilayer neural networks to approximate the assembly times of two different types of assembly machines based on several parameter combinations. It turns out that conventional learning methods are prone to overfitting when the number of hidden units of the network is large in relation to the number of training cases. To avoid this and complicated training and testing, we use Bayesian regularisation to achieve efficient learning and good accuracy automatically.