Particle types and sources associated with LDEF

The particulate contamination history of the Long Duration Exposure Facility (LDEF) can be resolved by careful analysis of particle types, the LDEF time line, evidence of the relationship between particles and the surface of the LDEF, and a consideration of probable sources. This work is far from complete but was initiated as part of the characterization of the condition of experimental trays that were returned to principle investigators for their analysis. The work presented in this photo-essay is continuing and will be updated in subsequent reports to NASA and at future technical meetings

Quantification of contaminants associated with LDEF

The quantification of contaminants on the Long Duration Exposure Facility (LDEF) and associated hardware or tools is addressed. The purpose of this study was to provide a background data base for the evaluation of the surface of the LDEF and the effects of orbital exposure on that surface. This study necessarily discusses the change in the distribution of contaminants on the LDEF with time and environmental exposure. Much of this information may be of value for the improvement of contamination control procedures during ground based operations. The particulate data represents the results of NASA contractor monitoring as well as the results of samples collected and analyzed by the authors. The data from the tapelifts collected in the Space Shuttle Bay at Edwards Air Force Base and KSC are also presented. The amount of molecular film distributed over the surface of the LDEF is estimated based on measurements made at specific locations and extrapolated over the surface area of the LDEF. Some consideration of total amount of volatile-condensible materials available to form the resultant deposit is also presented. All assumptions underlying these estimates are presented along with the rationale for the conclusions. Each section is presented in a subsection for particles and another for molecular films

Migration and generation of contaminants from launch through recovery: LDEF case history

It is possible to recreate the contamination history of the Long Duration Exposure Facility (LDEF) through an analysis of its contaminants and selective samples that were collected from surfaces with better documented exposure histories. This data was then used to compare estimates based on monitoring methods that were selected for the purpose of tracking LDEF's exposure to contaminants. The LDEF experienced much more contamination than would have been assumed based on the monitors. Work is still in progress but much of what was learned so far is already being used in the selection of materials and in the design of systems for space. Now experiments are being prepared for flight to resolve questions created by the discoveries on the LDEF. A summary of what was learned about LDEF contaminants over the first year since recovery and deintegration is presented. Over 35 specific conclusions in 5 contamination related categories are listed

Decoding of cognitive processes involved in the continuous performance task

Decoding of electroencephalogram brain representations is a powerful data driven technique to assess the stream of cognitive information processing. It could promote a more thorough understanding of cognitive control networks. For many years, the continuous performance task has been utilized to investigate impaired proactive and reactive cognitive functions. So far, mainly task performance and univariate electroencephalogram were involved in such investigations. In this study, we benefit from multi-variate pattern analysis of continuous performance task variations to provide a more complete spatio-temporal outline of information processing flow involved in sustained and transient attention and response preparation. Besides effects that are well in line with previous EEG research but could be described in more spatial and temporal detail by the used methods, our results could suggest the presence of a higher order feedback control system when expectations are violated. Such a feedback control is related to modulations of behavior both intra- and inter-individually

Removing the cardiac field artefact from the EEG using neural network regression.

When EEG recordings are used to reveal interactions between central-nervous and cardiovascular processes, the cardiac field artifact (CFA) poses a major challenge. Because the electric field generated by cardiac activity is also captured by scalp electrodes, the CFA arises as a heavy contaminant whenever EEG data are analyzed time-locked to cardio-electric events. A typical example is measuring stimulus-evoked potentials elicited at different phases of the cardiac cycle. Here, we present a nonlinear regression method deploying neural networks that allows to remove the CFA from the EEG signal in such scenarios. We train neural network models to predict R-peak centered EEG episodes based on the ECG and additional CFA-related information. In a second step, these trained models are used to predict and consequently remove the CFA in EEG episodes containing visual stimulation occurring time-locked to the ECG. We show that removing these predictions from the signal effectively removes the CFA without affecting the intertrial phase coherence of stimulus-evoked activity. In addition, we provide the results of an extensive grid search suggesting a set of appropriate model hyperparameters. The proposed method offers a replicable way of removing the CFA on the single-trial level, without affecting stimulus-related variance occurring time-locked to cardiac events. Disentangling the cardiac field artifact (CFA) from the EEG signal is a major challenge when investigating the neurocognitive impact of cardioafferent traffic by means of the EEG. When stimuli are presented time-locked to the cardiac cycle, both sources of variance are systematically confounded. Here, we propose a regression-based approach deploying neural network models to remove the CFA from the EEG. This approach effectively removes the CFA on a single-trial level and is purely data-driven, providing replicable results

Cognitive aging at work and in daily life—a narrative review on challenges due to age-related changes in central cognitive functions

Demographic change is leading to an increasing proportion of older employees in the labor market. At the same time, work activities are becoming more and more complex and require a high degree of flexibility, adaptability, and cognitive performance. Cognitive control mechanism, which is subject to age-related changes and is important in numerous everyday and work activities, plays a special role. Executive functions with its core functions updating, shifting, and inhibition comprises cognitive control mechanisms that serve to plan, coordinate, and achieve higher-level goals especially in inexperienced and conflicting actions. In this review, influences of age-related changes in cognitive control are demonstrated with reference to work and real-life activities, in which the selection of an information or response in the presence of competing but task-irrelevant stimuli or responses is particularly required. These activities comprise the understanding of spoken language under difficult listening conditions, dual-task walking, car driving in critical traffic situations, and coping with work interruptions. Mechanisms for compensating age-related limitations in cognitive control and their neurophysiological correlates are discussed with a focus on EEG measures. The examples illustrate how to access influences of age and cognitive control on and in everyday and work activities, focusing on its functional role for the work ability and well-being of older people

Measuring societal awareness of the rural agrarian landscape: indicators and scale issues

The work presented in this report is part of the effort to define the landscape state and diversity indicator in the frame of COM (2006) 508 “Development of agri-environmental indicators for monitoring the integration of environmental concerns into the common agricultural policy”. The Communication classifies the indicators according to their level of development, which, for the landscape indicator is “in need of substantial improvements in order to become fully operational”. For this reason a full re-definition of the indicator has been carried out, following the initial proposal presented in the frame of the IRENA operation (“Indicator Reporting on the Integration of Environmental Concerns into Agricultural Policy”). The new proposal for the landscape state and diversity indicator is structured in three components: the first concerns the degree of naturalness, the second landscape structure, the third the societal appreciation of the rural landscape. While the first two components rely on a strong bulk of existing literature, the development of the methodology has made evident the need for further analysis of the third component, which is based on a newly proposed top-down approach. This report presents an in-depth analysis of such component of the indicator, and the effort to include a social dimension in large scale landscape assessment

The EU societal awareness of landscape indicator: a review of its meaning, utility and performance across different scales

There is increasing recognition that agricultural landscapes meet multiple societal needs and demands beyond provision of economic and environmental goods and services. Accordingly, there have been significant calls for the inclusion of societal, amenity and cultural values in agri-environmental landscape indicators to assist policy makers in monitoring the wider impacts of land-based policies. However, capturing the amenity and cultural values that rural agrarian areas provide, by use of such indicators, presents significant challenges. The EU social awareness of landscape indicator represents a new class of generalized social indicator using a top-down methodology to capture the social dimensions of landscape without reference to the specific structural and cultural characteristics of individual landscapes. This paper reviews this indicator in the context of existing agri-environmental indicators and their differing design concepts. Using a stakeholder consultation approach in five case study regions, the potential and limitations of the indicator are evaluated, with a particular focus on its perceived meaning, utility and performance in the context of different user groups and at different geographical scales. This analysis supplements previous EU-wide assessments, through regional scale assessment of the limitations and potentialities of the indicator and the need for further data collection. The evaluation finds that the perceived meaning of the indicator does not vary with scale, but in common with all mapped indicators, the usefulness of the indicator, to different user groups, does change with scale of presentation. This indicator is viewed as most useful when presented at the scale of governance at which end users operate. The relevance of the different sub-components of the indicator are also found to vary across regions