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There are many examples of cases where access to improved models of human behavior and cognition has allowed the creation of robots that can better interact with humans, and not least in road vehicle automation, this is a rapidly growing area of research. Human–robot interaction (HRI) therefore provides an important applied setting for human behavior modeling—but given the vast complexity of human behavior, how complete and accurate do these models need to be? Here, we outline some possible ways of thinking about this problem, starting from the suggestion that modelers need to keep the right end goal in sight: a successful HRI, in terms of safety, performance, and human satisfaction. Efforts toward model completeness and accuracy should be focused on those aspects of human behavior to which interaction success is most sensitive.

Increasing attention has been drawn to computational pedestrian behavior models aimed at understanding the interaction mechanisms between pedestrians and vehicles. Nevertheless, existing research lacks exploration of the underlying behavioral mechanisms of pedestrian crossing decisions, which leads to unrealistic modeling results. In particular, when dealing with continuous traffic flow scenarios, the concept of waiting time is frequently used to account for all intricate traffic flow effects. Moreover, very few studies considered the time-dynamic nature of crossing decisions. To address these research limitations, this study deconstructs pedestrian crossing decisions at uncontrolled intersections with continuous traffic flow through a cognitive process and proposes an anthropomorphic crossing decision model. Specifically, we propose a novel visual collision cue-based crossing decision-initiation model to characterize time-dynamic crossing decisions. In light of the risk-aversion theory, a traffic gap comparison strategy is put forward to explain and model pedestrian waiting behavior in traffic flow. Two datasets collected from a CAVE-based immersive pedestrian simulator are applied to calibrate and validate the model. The proposed model accurately predicts pedestrian crossing decisions across all traffic scenarios. The modeling performance is significantly enhanced by considering the proposed traffic gap comparison strategy. Moreover, the model accurately captures the timing of crossing decisions. This work concisely demonstrates how pedestrians dynamically adapt their crossings in continuous traffic based on visual collision cues, potentially offering insights into modeling pedestrian-vehicle interactions or serving as a tool to realize anthropomorphic pedestrian crossing decisions in simulators.

Traffic as an important part of the energy sector significantly contributes to global air pollution. To mitigate the hazardous components of traffic emissions regulations have been implemented resulting in technological solutions such as exhaust after-treatment systems. However, fuels also play a crucial role in emissions and components such as the aromatic compounds in fuel have been linked to increased exhaust emissions. Several current emissions regulations neglect environmental factors, such as cold operating temperatures, that can significantly increase emissions. Moreover, the effect of fuel aromatics and cold temperature on emissions toxicity has not been adequately studied. This study evaluates the impact of after-treatment systems, aromatic fuel content, and cold operating temperature on emission toxicity. To achieve this, four different light-duty vehicles were used in a temperature-controlled dynamometer room, with a co-culture of A549 and THP-1 cell lines exposed to online exhaust emissions using a thermophoresis-based air–liquid interface (ALI) system. The results demonstrate that the aromatic content of both diesel and gasoline fuels increases exhaust toxicity. The study additionally emphasises the potential of particulate filters as after-treatment systems to reduce the toxicity of emissions and highlights how cold running temperatures result in higher exhaust toxicity. The study also assessed the diesel particulate filter (DPF) active regeneration event, which leads to multi-fold emissions and higher toxicological responses. Overall, the study provides crucial novel results on how various factors affect the toxicity of exhaust emissions from modern light-duty vehicles, providing insights into decreasing the emissions from this energy sector.

Autonomous vehicles use a variety of sensors and machine-learned models to predict the behavior of surrounding road users. Most of the machine-learned models in the literature focus on quantitative error metrics like the root mean square error (RMSE) to learn and report their models’ capabilities. This focus on quantitative error metrics tends to ignore the more important behavioral aspect of the models, raising the question of whether these models really predict human-like behavior. Thus, we propose to analyze the output of machine-learned models much like we would analyze human data in conventional behavioral research. We introduce quantitative metrics to demonstrate presence of three different behavioral phenomena in a naturalistic highway driving dataset: 1) The kinematics-dependence of who passes a merging point first 2) Lane change by an on-highway vehicle to accommodate an on-ramp vehicle 3) Lane changes by vehicles on the highway to avoid lead vehicle conflicts. Then, we analyze the behavior of three machine-learned models using the same metrics. Even though the models’ RMSE value differed, all the models captured the kinematic-dependent merging behavior but struggled at varying degrees to capture the more nuanced courtesy lane change and highway lane change behavior. Additionally, the collision aversion analysis during lane changes showed that the models struggled to capture the physical aspect of human driving: leaving adequate gap between the vehicles. Thus, our analysis highlighted the inadequacy of simple quantitative metrics and the need to take a broader behavioral perspective when analyzing machine-learned models of human driving predictions.

Human behavior and interaction in road traffic is highly complex, with many open scientific questions of high applied importance, not least in relation to recent development efforts toward automated vehicles. In parallel, recent decades have seen major advances in cognitive neuroscience models of human decision-making, but these models have mainly been applied to simplified laboratory tasks. Here, we demonstrate how variable-drift extensions of drift diffusion (or evidence accumulation) models of decision-making can be adapted to the mundane yet non-trivial scenario of a pedestrian deciding if and when to cross a road with oncoming vehicle traffic. Our variable-drift diffusion models provide a mechanistic account of pedestrian road-crossing decisions, and how these are impacted by a variety of sensory cues: time and distance gaps in oncoming vehicle traffic, vehicle deceleration implicitly signaling intent to yield, as well as explicit communication of such yielding intentions. We conclude that variable-drift diffusion models not only hold great promise as mechanistic models of complex real-world decisions, but that they can also serve as applied tools for improving road traffic safety and efficiency.

The criticality of a rear end event depends on the brake reaction time (BRT) of the driver. Therefore, distracted driving poses greater threat in such events. Evidence accumulation model (EAM) that uses looming of the lead vehicle as main stimuli has shown significant success in estimating drivers’ BR Ts. It is often argued that drivers collect evidence for braking through peripheral vision, especially during off-road glances, and transition to forward. In this work, we have modeled evidence accumulation as a function of gaze eccentricity for off-road glances while approaching safety critical events. The model is tested with real world crash and near crash event data from SHRP2 naturalistic study. Our model shows that linear relation between gaze eccentricity and evidence accumulation rate during off road glances helps to improve EAM estimation in predicting BRT. We have also shown that brake-light onset does not influence EAM in presence of active looming.

ABSTRACTTechnological development and increasing personal data collection and utilization raise the importance of understanding individuals’ privacy behavior. Privacy behavior denotes the willingness to disclose personal data for services utilizing these data. The literature presents various privacy behavior models (PBMs). However, the research is incoherent, with inconsistencies among models. Therefore, the application and subsequent development of PBMs are challenging. Different background theories are used for model construction, and studies have been conducted in distinct application domains. We studied whether the models’ inconsistencies could be explained by these differences. Our in-depth analysis of PBMs was based on a systematic literature review of the most often cited key studies. Our findings indicate that the choice of theories and the application domains do not explain inconsistencies; instead, the models are often of an ad hoc type and constructed in an eclectic way. These results imply the need for more consistent research on privacy behavior.

The surface activity of hot-dip galvanized steel was evaluated after alkaline cleaning by exposing the cleaned specimens in humid supercritical carbon dioxide, followed by extraction and quantification of the formed corrosion products. Different free alkalinities of the cleaning bath were studied to obtain information on the evolution of zinc surface activity at different levels of surface etching. Surface reactivity of uncleaned galvanized steel is restricted and local, with major contributions from grain boundaries and intermetallic particles. Formation of zinc corrosion products took place in uncleaned samples exclusively on and around these sites. Al2O3removal by alkaline cleaning gradually increased the surface activity. The major increase in surface activity was achieved when increasing the free alkalinity from 0.5 to 4.0 mEq/L, which was shown by formation of zinc corrosion products within zinc grains. The surface activity was confirmed by applying a titanium hexafluoride pretreatment on the cleaned panels and measuring the lateral microscale uniformity of the formed layer. The uniformity increased when larger areas of galvanized steel became activated by alkaline cleaning. Reactivity of zinc is rather difficult to quantify when setting up an industrial cleaning sequence for galvanized steel. Controlled exposure of cleaned samples in humid supercritical carbon dioxide, followed by quantification of oxidized zinc, provides a straightforward method to evaluate zinc reactivity.

With the development of increasingly automated vehicles (AVs) comes the increasingly difficult challenge of comprehensively validating these for acceptable, and ideally beneficial, impacts on the transport system. There is a growing consensus that virtual testing, where simulated AVs are deployed in simulated traffic, will be key for cost-effective testing and optimization. The least mature model components in such simulations are those generating the behavior of human agents in or around the AVs. In this paper, human models and virtual testing applications are presented for two example scenarios: (i) a human pedestrian deciding whether to cross a street in front of an approaching automated vehicle, with or without external human–machine interface elements, and (ii) an AV handing over control to a human driver in a critical rear-end situation. These scenarios have received much recent research attention, yet simulation-ready human behavior models are lacking. They are discussed here in the context of existing models of perceptual decision-making, situational awareness, and traffic interactions. It is argued that the human behavior in question might be usefully conceptualized as a number of interrelated decision processes, not all of which are necessarily directly associated with externally observable behavior. The results show that models based on this type of framework can reproduce qualitative patterns of behavior reported in the literature for the two addressed scenarios, and it is demonstrated how computer simulations based on the models, once these have been properly validated, could allow prediction and optimization of AV impacts on traffic flow and traffic safety.

For a driving simulator to be a valid tool for research, vehicle development, or driver training, it is crucial that it elicits similar driver behavior as the corresponding real vehicle. To assess such behavioral validity, the use of quantitative driver models has been suggested but not previously reported. Here, a task-general conceptual driver model is proposed, along with a taxonomy defining levels of behavioral validity. Based on these theoretical concepts, it is argued that driver models without explicit representations of sensory or neuromuscular dynamics should be sufficient for a model-based assessment of driving simulators in most contexts. As a task-specific example, two parsimonious driver steering models of this nature are developed and tested on a dataset of real and simulated driving in near-limit, low-friction circumstances, indicating a clear preference of one model over the other. By means of closed-loop simulations, it is demonstrated that the parameters of this preferred model can generally be accurately estimated from unperturbed driver steering data, using a simple, open-loop fitting method, as long as the vehicle positioning data are reliable. Some recurring patterns between the two studied tasks are noted in how the model's parameters, fitted to human steering, are affected by the presence or absence of steering torques and motion cues in the simulator.

Zinc carbonate and a mixed-phase zinc carbonate were precipitated selectively on hot dip galvanized steel in the presence of CO2and water. The zinc carbonate was precipitated as a uniform layer with cubic superficial appearance, while the mixed-phase zinc carbonate was precipitated as nanowires. The distinct structures could be formed separately or as a dual structure with nanowires on the outermost surface. The barrier properties were improved by the both patina forms; a significant increase in surface hydrophobicity was obtained. The dual patina structure was successfully coated with an organic coating, and the intact wet CO2-induced patina with both structures was confirmed within the coating. The formed carbonates can be further converted to zinc oxide by calcination, preserving the delicate structures, which opens a wide range of potential applications for the nanostructured ZnO in a variety of future electronic and optoelectronic devices.

The General Data Protection Regulation (GDPR) will come into force in the European Union (EU) in May 2018 to meet current challenges related to personal data protection and to harmonise data protection across the EU. Although the GDPR is anticipated to benefit companies by offering consistency in data protection activities and liabilities across the EU countries and by enabling more integrated EU-wide data protection policies, it poses new challenges to companies. They are not necessarily prepared for the changes and may lack awareness of the upcoming requirements and the GDPR's coercive measures. The implementation of the GDPR requirements demands substantial financial and human resources, as well as training of employees; hence, companies need guidance to support them in this transition. The purposes of this study were to compare the current Data Protection Directive 95/46/EC with the GDPR by systematically analysing their differences and to identify the GDPR's practical implications, specifically for companies that provide services based on personal data. This study aimed to identify and discuss the changes introduced by the GDPR that would have the most practical relevance to these companies and possibly affect their data management and usage practices. Therefore, a review and a thematic analysis and synthesis of the article-level changes were carried out. Through the analysis, the key practical implications of the changes were identified and classified. As a synthesis of the results, a framework was developed, presenting 12 aspects of these implications and the corresponding guidance on how to prepare for the new requirements. These aspects cover business strategies and practices, as well as organisational and technical measures.

An existing modelling framework is leveraged to create a driver braking model for use in simulations of critical longitudinal scenarios with a slower or braking lead vehicle. The model applies intermittent brake adjustments to minimize accumulated looming prediction error. It is here applied to the simulation of a set of lead vehicle scenarios. The simulation results in terms of brake initiation timing and brake jerk are demonstrated to capture well the specific types of kinematics-dependencies that have been recently reported from naturalistic near-crashes and crashes.

The objective of the study was to examine the causes of stillbirth in the district of Southwest Finland and to assess the importance of postmortem examination and the selection of a suitable classification system for classifying stillbirths. This study is a cohort study where the fetal autopsies were performed in the Department of Pathology at Turku University Hospital, Finland, 2001–2011. Stillbirths from singleton pregnancies at the gestational age of?=?24?+?0 weeks (if unknown, gestational weight?=?500?g) (n?=?98) were selected. In addition, stillbirths from multiple gestations (n?=?6) were also analyzed. The causes of stillbirths were classified according to the Relevant Condition at Death classification system. Maternal risk factors and the role of fetal gestational age and weight for the causes of stillbirth were assessed. The most common causes of singleton stillbirth were lethal congenital anomalies, placental insufficiencies, and constricting loops and knots of the umbilical cord. The cause of singleton stillbirth could be determined for 78% of the cases, leaving 22% unclassified. There were no significant differences in the causes of stillbirth by gestational age or weight. Smoking may increase the incidence of placental abruption (P?

Specialized metabolic sensors in the hypothalamus regulate blood glucose levels by influencing hepatic glucose output and hypoglycemic counterregulatory responses. Hypothalamic reactive oxygen species (ROS) may act as a metabolic signal-mediating responses to changes in glucose, other substrates and hormones. The role of ROS in the brain's control of glucose homeostasis remains unclear. We hypothesized that hydrogen peroxide (H2O2), a relatively stable form of ROS, acts as a sensor of neuronal glucose consumption and availability and that lowering brain H2O2with the enzyme catalase would lead to systemic responses increasing blood glucose. During hyperinsulinemic euglycemic clamps in rats, intracerebroventricular catalase infusion resulted in increased hepatic glucose output, which was associated with reduced neuronal activity in the arcuate nucleus of the hypothalamus. Electrophysiological recordings revealed a subset of arcuate nucleus neurons expressing proopiomelanocortin that were inhibited by catalase and excited by H2O2. During hypoglycemic clamps, intracerebroventricular catalase increased glucagon and epinephrine responses to hypoglycemia, consistent with perceived lower glucose levels. Our data suggest that H2O2represents an important metabolic cue, which, through tuning the electrical activity of key neuronal populations such as proopiomelanocortin neurons, may have a role in the brain's influence of glucose homeostasis and energy balance.

Software companies that develop embedded systems following the principles of service-oriented architecture can anticipate various benefits from choreography modelling. Current choreography modelling languages, however, have a limited applicability in embedded systems development since they are not expressive enough to capture all the choreography-relevant aspects that are typical in this domain. This problem is addressed in this study with the analysis of the needs in embedded systems domain for choreography modelling language. The analysis was guided by design science and relied on expert interviews, company-specific documents, relevant scientific literature and the experts' evaluation of the redesigned choreography modelling language. The main results of the analysis presented in this paper are a) design requirements addressing the limitations of choreography modelling languages for embedded systems development and b) proposals for modelling language implementation technologies. The derived design requirements indicate on choreography-relevant embedded systems development aspects such as the constraint-based access and real-time execution. Modelling language implementation technology proposals include Eclipse modelling framework and Sirius. The feasibility of these results is evaluated by redesigning an existing choreography modelling language based on the derived design requirements, implementing a prototype editor for the redesigned language and by evaluating the redesigned language with experts.

Experimental data revealed that drivers performing a visual secondary task exhibited deteriorated lane keeping performance, but that the same drivers performing a cognitive secondary exhibited an improvement in lane keeping compared to baseline driving. In this paper we present a computational cybernetic driver model that characterizes the effect of difference in eye fixation durations between on and off road glances across the three task conditions on straight lane keeping performance. The model uses perceptual cues as control input, maintains internal representations of these cues across fixations through Bayesian updating, and each time a change in cue magnitude is perceived based on mechanisms akin to signal detection theory a change in control is applied. The model is shown to be able to capture the experimental results encouragingly well. The model also sheds light on the relative magnitude of lane keeping performance degradation caused by glancing away from the road and the fact that internal representations are degraded each time a saccade takes place. The adopted approach to modeling driver perception during and across fixations is expected to lead to new insights into the effects that various in-vehicle activities have on driving performance and risk.

Most daily driving tasks are of low bandwidth and therefore the relatively slow visual system provides enough cue information to perform the task in a manner that is statistically indistinguishable from reality. On the other hand, evasive maneuvers are of such a high bandwidth that waiting for the visual cues to change is too slow and skilled drivers use steering torques and vestibular motion cues to know how the car is responding in order to make rapid corrective actions. In this study we show for evasive maneuvers on snow and ice, for which we have real world data from skilled test drivers, that the choice of motion cuing algorithm (MCA) settings has a tremendous impact on the saliency of motion cues and their similarity with reality. We demonstrate this by introducing a novel optimization scheme to optimize the classic MCA in the context of an MCA-Simulator-Driver triplet of constraints. We incorporate the following four elements to tune the MCA for a particular maneuver: 1) acceleration profiles of the maneuver observed in reality, 2) vestibular motion perception model, 3) motion envelope constraints of the simulator, and 4) a set of heuristics extracted from the literature about human motion perception (i.e. coherence zones). Including these elements in the tuning process, notwithstanding the easiness of the tuning process, respects motion platform constraints and considers human perception. Moreover the inevitable phase and gain errors arising as a major consequence of MCA are always kept within the human coherence zones, and subsequently are not perceptible as false cues. It is expected that this approach to MCA tuning will increase the transfer of training from simulator to reality for evasive driving maneuvers where students need training most and are most dangerous to perform in reality.

Humidity resistance of pretreated and coil-coated panels was evaluated with a special emphasis on the process parameters that govern the uniformity and barrier properties of hexafluorotitanic acid-based pretreatment layers. Humidity resistance tests showed that good barrier effect was obtained with pretreatments in the coating weight range of about 2–17 mg Ti/m2. It was further verified by rinsing experiments that a fully reacted pretreatment layer is achieved at the very low end of the optimal coating weight range. Increasing the coating weight leads to the formation of precipitated, loosely bonded porous structure, which was detrimental to humidity resistance. In addition to the coating weight, the microscale pretreatment layer uniformity is of utmost importance for good barrier properties. Electron probe microanalysis measurements provide an efficient tool to assess the pretreatment layer uniformity and facilitate monitoring of process adjustments with clear correlation to humidity resistance properties of painted panels. The surface condition of the hot dip-galvanized steel and the material of the application rolls were found to strongly affect the uniformity of the pretreatment layers.

Building on ideas from contemporary neuroscience, a framework is proposed in which drivers’ steering and pedal behavior is modeled as a series of individual control adjustments, triggered after accumulation of sensory evidence for the need of an adjustment, or evidence that a previous or ongoing adjustment is not achieving the intended results. Example simulations are provided. Specifically, it is shown that evidence accumulation can account for previously unexplained variance in looming detection thresholds and brake onset timing. It is argued that the proposed framework resolves a discrepancy in the current driver modeling literature, by explaining not only the short-latency, well-tuned, closed-loop type of control of routine driving, but also the degradation into long-latency, ill-tuned open-loop control in more rare, unexpected, and urgent situations such as near-accidents.

In this paper, a general and fundamental property of steering is demonstrated: It is shown that steering corrections generally follow bell-shaped profiles of steering rate. The finding is strongly related to what is already known about reachingmovements. Also, a strong linear relationship was found between the maximum steering wheel rate and the steering wheel deflection, something that indicates a constant movement time for the correction. Furthermore, by closer examination of those corrections that cannot be described by a single bell-shaped rate profile, it was found that they typically can be described using two or, in some cases three or four, overlapping profiles, something which relates to superposition of motor primitives.

This paper aims to determine how truck driver steering behaviour seen in repeated exposures to acritical event correlates to the behaviour resulting from an unexpected exposure to the same event. Test subjects were exposed to an unexpected critical event in a high-fidelity driving simulator. Next, a slightly modified version of the scenario was repeated several times for each subject. The driver behaviour was then analysed using standard statistical tests. It was found that, in general, drivers keep most of their steering behaviour characteristics between test settings (unexpected and repeated). This is particularly interesting sincea similar kind of behaviour preservation is generally not found in the case of brakingbehaviour. In fact, onlyone significant difference was found between the two test settings, namely regarding time-to-collision at steering initiation. In experiments involving both an unexpected event and several repeated events one can,at least in some cases, design the repeated event such that behavioural data collected from that setting can beused along with data from the unexpected setting. Using this procedure, one can significantly increase the amount of collected data, something that can strongly benefit, for example, driver modelling.

Aim: The aim of this systematic literature review, a meta-synthesis, was to understand and make visible the prevailing discourse of the school nurse within current nursing research published between 1999 and 2009;.Background: The school nurse's position in school health care is currently unclear and the school health care does not seem to live up to society's expectations of it. There is also a lack of collective strategies to achieve the objectives of school health services.Methods: The search for published studies was conducted in the databases Cinahl and Medline and by manual additions. Data set (24 included studies), were analyzed qualitatively (Discourse analysis) by careful reading, interpretation for deeper analysis and a synthesis.Findings: Three discursive concepts were formulated that together formed the discourse of the school nurse: (i) the discourse of caring, (ii) the professional discourse, and (iii) the institutional discourse.Conclusion: The discourse expresses ideas about the school nurse as in possession of skills and abilities that are not fully expressed. This indicates a dilemma between ambition and actual conditions. An implication for school health services is to clarify the school nurses tasks to facilitate the prioritization of time instead of vague terms of responsibility.

Chlamydiae are obligate intracellular pathogens replicating only inside the eukaryotic host. Here, we studied the effect of human flotillin-1 protein on Chlamydia pneumoniae growth in human line (HL) and A549 epithelial cell lines. RNA interference was applied to disrupt flotillin-1-mediated endocytosis. Host-associated bacteria were detected by quantitative PCR, and C. pneumoniae growth was evaluated by inclusion counts. C. pneumoniae attachment to host cells was unaffected, but bacterial intracellular growth was attenuated in the flotillin-1-silenced cells. By using confocal microscopy, we detected flotillin-1 colocalized with the inclusion membrane protein A (IncA) in the C. pneumoniae inclusion membranes. In addition, flotillin-1 was associated with IncA in detergent-resistant membrane microdomains (DRMs) in biochemical fractioning. These results suggest that flotillin-1 localizes to the C. pneumoniae inclusion membrane and plays an important role for intracellular growth of C. pneumoniae.

Chlamydiaeare obligate intracellular pathogens replicating only inside the eukaryotic host. Here, we studied the effect of human flotillin-1 protein on Chlamydia pneumoniaegrowth in human line (HL) and A549 epithelial cell lines. RNA interference was applied to disrupt flotillin-1-mediated endocytosis. Host-associated bacteria were detected by quantitative PCR, and C. pneumoniaegrowth was evaluated by inclusion counts. C. pneumoniaeattachment to host cells was unaffected, but bacterial intracellular growth was attenuated in the flotillin-1-silenced cells. By using confocal microscopy, we detected flotillin-1 colocalized with the inclusion membrane protein A (IncA) in the C. pneumoniaeinclusion membranes. In addition, flotillin-1 was associated with IncA in detergent-resistant membrane microdomains (DRMs) in biochemical fractioning. These results suggest that flotillin-1 localizes to the C. pneumoniaeinclusion membrane and plays an important role for intracellular growth of C. pneumoniae.

AbstractTo examine the serotype specificity of inlH, which encodes the virulence-associated surface protein InlH related to the intracellular survival of Listeria monocytogenesin mice, the presence of inlHin 337 L. monocytogenesstrains, representing 11 different serotypes, was studied. A total of 106 strains representing 3 serotypes and 14 pulsed-field gel electrophoresis (PFGE) types were positive for inlHby polymerase chain reaction. inlHwas present in all 99 serotype 1/2c and 3 serotype 3c strains. Moreover, 4 out of 129 (3%) serotype 1/2a strains carried inlH.All 106 strains representing serotypes 1/2b, 3a, 3b, 4a, 4b, 4c, 4d, and 7 and 125 out of 129 (97%) serotype 1/2a strains were inlH-negative. The coding sequences of the inlHgenes of eight L. monocytogenesstrains representing three serotypes and five PFGE types were identical. These results suggest that inlHis specifically present in serotype 1/2c, 3c, and a small fraction of 1/2a L. monocytogenesstrains and exists as a single allele.

ABSTRACTWe set up a polarized cell culture model to study the pathogenicity of a common respiratory tract pathogen, Chlamydia pneumoniae. Immunofluorescence staining of ZO-1 (a tight junction protein) and Na+K+ATPase (a protein pump localized at the basolateral membrane in the polarized epithelial cells), as well as TER measurements, suggested that the filter-grown Calu-3 cells, but not the A549 cells, were polarized when grown on collagen-coated membranes. Both the flat and the filter-grown cultures were infected with C. pneumoniae. Infection in the polarized Calu-3 cultures produced more C. pneumoniaegenome equivalents than infection in the flat cultures. However, this progeny was not as infective as that in the flat cultures. The maximum amount of C. pneumoniaewas detected at 6 days postinfection in the filter-grown A549 cells, indicating a slower developmental cycle than that observed in the flat A549 cultures. The effect of cycloheximide on the growth of C. pneumoniaein the polarized cells was negligible. Furthermore, the infection in the polarized Calu-3 cells was resistant to doxycycline, and several cytokines were released mainly on the apical side of the polarized cells in response to C. pneumoniaeinfection. These findings indicate that the growth of chlamydiae was altered in the filter-grown epithelial culture system. The diminished production of infective progeny of C. pneumoniae, together with the resistance to doxycycline and polarized secretion of cytokines from the infected Calu-3 cells, suggests that this model is useful for examining epithelial cell responses to C. pneumoniaeinfection, and it might better resemble in vivoinfection in respiratory epithelial cells.

We set up a polarized cell culture model to study the pathogenicity of a common respiratory tract pathogen, Chlamydia pneumoniae. Immunofluorescence staining of ZO-1 (a tight junction protein) and Na+K+ATPase (a protein pump localized at the basolateral membrane in the polarized epithelial cells), as well as TER measurements, suggested that the filter-grown Calu-3 cells, but not the A549 cells, were polarized when grown on collagen-coated membranes. Both the flat and the filter-grown cultures were infected with C. pneumoniae. Infection in the polarized Calu-3 cultures produced more C. pneumoniae genome equivalents than infection in the flat cultures. However, this progeny was not as infective as that in the flat cultures. The maximum amount of C. pneumoniae was detected at 6 days postinfection in the filter-grown A549 cells, indicating a slower developmental cycle than that observed in the flat A549 cultures. The effect of cycloheximide on the growth of C. pneumoniae in the polarized cells was negligible. Furthermore, the infection in the polarized Calu-3 cells was resistant to doxycycline, and several cytokines were released mainly on the apical side of the polarized cells in response to C. pneumoniae infection. These findings indicate that the growth of chlamydiae was altered in the filter-grown epithelial culture system. The diminished production of infective progeny of C. pneumoniae, together with the resistance to doxycycline and polarized secretion of cytokines from the infected Calu-3 cells, suggests that this model is useful for examining epithelial cell responses to C. pneumoniae infection, and it might better resemble in vivo infection in respiratory epithelial cells.

Fused deposition modeling combined with electroplating provides a novel manufacturing methodology for building low relative density engineered cellular topologies. Here the mechanical performance of tetrahedral, pyramidal, and strut‐reinforced tetrahedral cellular solids manufactured from multiphase nickel‐copper‐ABS is studied. The novel processing and geometric optimization places these engineered topologies into an unoccupied location in the material universe.

There is some research evidence which suggests that drinking habits among Swedish-speaking Finns differ from those of Finnish-speaking Finns. The limited literature on this subject routinely lumps the minority of Swedish-speaking Finns into one single group. The assumption is that drinking habits in the Swedish-speaking population are less damaging to health than drinking habits in the Finnish-speaking majority. In this study we use data from the nationwide School Health Promotion Study, which in principle covers all pupils in the 8th and 9th grade of comprehensive school and the 1st and 2nd grade of upper secondary school. We chose to focus on two areas with a sufficiently large number of Swedish-speaking residents and, by tradition, different drinking habits, i.e. Ostrobothnia and the metropolitan Helsinki area. All in all, the data consist of 5,698 Swedish-speaking and 29,708 Finnish-speaking adolescents aged Ca. 14-18. The results show that when the populations from the two areas are taken together, there are indeed differences between the two language groups. The almost ten-year downward trend in youthful drinking in Finland is clearly attributable to Finnish-speaking youth. This is also true for the reductions seen in frequent drinking and binge drinking. In a comparison of Ostrobothnia and the metropolitan Helsinki area, it turns out that the differences between Swedish-speaking youngsters are considerable: abstention, less frequent drinking and less binge drinking are clearly more prevalent in Ostrobothnia than in the Helsinki area. By comparison, the Finnish-speaking adolescents in the two regions differ less clearly from each other. Conspicuous subgroups within the Swedish-speaking minority are the binge drinking upper secondary students in the Helsinki area, the abstaining girls from comprehensive schools in the almost exclusively Swedish-speaking Ostrobothnian municipalities, and the abstaining youngsters from the "bible zone" in Ostrobothnia. In contrast to earlier findings, we found that in Ostrobothnia the drinking habits of the two language groups are quite similar. [ABSTRACT FROM AUTHOR]

A total of 257 raw fish samples at two different sites were examined for the presence of Listeria monocytogenes. The prevalence of L. monocytogeneswas 4%. From 11 positive samples, nine different L. monocytogenespulsed-field gel electrophoresis genotypes were recovered. From nine pulsotypes recovered from raw fish and 32 pulsotypes shown by 101 fish product isolates, two raw fish and fish product pulsotypes were indistinguishable from each other. Although the prevalence of L. monocytogenesin raw fish is low, the range of L. monocytogenesstrains entering the processing plant in large amounts of raw material is wide. This indicates that the raw material is an important initial contamination source of L. monocytogenesin fish processing plants. This postulation is supported by the identical pulsotypes recovered from both raw and processed fish. Some L. monocytogenesstrains entering a plant may thus contaminate and persist in the processing environment, causing recurrent contamination of the final products via processing machines.