Long Duration Exposure Facility (LDEF). Mission 1 Experiments

Spaceborne experiments using the space shuttle payload known as the Long Duration Exposure Facility are described. Experiments in the fields of materials, coatings, thermal systems, power and propulsion, electronic, and optics are discussed

Recent results and new hardware developments for protein crystal growth in microactivity

Protein crystal growth experiments have been performed on 16 space shuttle missions since April, 1985. The initial experiments utilized vapor diffusion crystallization techniques similar to those used in laboratories for earth-based experiments. More recent experiments have utilized temperature induced crystallization as an alternative method for growing high quality protein crystals in microgravity. Results from both vapor diffusion and temperature induced crystallization experiments indicate that proteins grown in microgravity may be larger, display more uniform morphologies, and yield diffraction data to significantly higher resolutions than the best crystals of these proteins grown on earth

Oscillations of General Relativistic Multi-fluid/Multi-layer Compact Stars

We develop the formalism for determining the quasinormal modes of general relativistic multi-fluid compact stars in such a way that the impact of superfluid gap data can be assessed. Our results represent the first attempt to study true multi-layer dynamics, an important step towards considering realistic superfluid/superconducting compact stars. We combine a relativistic model for entrainment with model equations of state that explicity incorporate the symmetry energy. Our analysis emphasises the many different parameters that are required for this kind of modelling, and the fact that standard tabulated equations of state are grossly incomplete in this respect. To make progress, future equations of state need to provide the energy density as a function of the various nucleon number densities, the temperature (i.e. entropy), and the entrainment among the various components

Using assignment data to analyse a blended information literacy intervention: a quantitative approach

This research sought to determine whether a blended information literacy learning and teaching intervention could statistically significantly enhance undergraduates’ information discernment compared to standard face-to-face delivery. A mixture of face-to-face and online activities, including online social media learning, was used. Three interventions were designed to develop the information literacies of first-year undergraduates studying Sport and Exercise at Staffordshire University and focused on one aspect of information literacy: the ability to evaluate source material effectively. An analysis was devised where written evaluations of found information for an assessment were converted into numerical scores and then measured statistically. This helped to evaluate the efficacy of the interventions and provided data for further analysis. An insight into how the information literacy pedagogical intervention and the cognitive processes involved in enabling participants to interact critically with information is provided. The intervention which incorporated social media learning proved to be the most successful learning and teaching approach. The data indicated that undergraduate students’ information literacy can be developed. However, additional long-term data is required to establish whether this intervention would have a lasting impact

Proton NMR measurements of the local magnetic field in the paramagnetic metal and antiferromagnetic insulator phases of λ\lambda-(BETS)2_{2}FeCl4_{4}

Measurements of the $^{1}$H-NMR spectrum of a small ($\sim$ 4 $\mu$g) single crystal of the organic conductor $\lambda$-(BETS)$_{2}$FeCl$_{4}$ are reported with an applied magnetic field $\bf{B}$$_{0}$ = 9 T parallel to the a-axis in the $ac$-plane over a temperature $(T)$ range 2.0 $-$ 180 K. They provide the distribution of the static local magnetic field at the proton sites in the paramagnetic metal (PM) and antiferromagnetic insulator (AFI) phases, along with the changes that occur at the PM$-$AFI phase transition. The spectra have six main peaks that are significantly broadened and shifted at low $T$. The origin of these features is attributed to the large dipolar field from the 3d Fe$^{3+}$ ion moments (spin $S_{\rm{d}}$ = 5/2). Their amplitude and $T-$dependence are modeled using a modified Brillouin function that includes a mean field approximation for the total exchange interaction ($J_{0}$) between one Fe$^{3+}$ ion and its two nearest neighbors. A good fit is obtained using $J_{0}$ = $-$ 1.7 K. At temperatures below the PM$-$AFI transition temperature $T_{MI}$ = 3.5 K, an extra peak appears on the high frequency side of the spectrum and the details of the spectrum become smeared. Also, the rms linewidth and the frequency shift of the spectral distribution are discontinuous, consistent with the transition being first-order. These measurements verify that the dominant local magnetic field contribution is from the Fe$^{3+}$ ions and indicate that there is a significant change in the static local magnetic field distribution at the proton sites on traversing the PM to AFI phase transition.Comment: 11 pages, 7 figures. Revised version of cond-mat/0605044 resubmitted to Phys. Rev. B in response to comments of Editor and reviewer

Massive stars in the giant molecular cloud G23.3−0.3 and W41

Context. Young massive stars and stellar clusters continuously form in the Galactic disk, generating new Hii regions within their natal giant molecular clouds and subsequently enriching the interstellar medium via their winds and supernovae.Aims. Massive stars are among the brightest infrared stars in such regions; their identification permits the characterisation of the star formation history of the associated cloud as well as constraining the location of stellar aggregates and hence their occurrence as a function of global environment.Methods. We present a stellar spectroscopic survey in the direction of the giant molecular cloud G23.3−0.3. This complex is located at a distance of ~4–5 kpc, and consists of several Hii regions and supernova remnants.Results. We discovered 11 OfK+ stars, one candidate luminous blue variable, several OB stars, and candidate red supergiants. Stars with K-band extinction from ~1.3–1.9 mag appear to be associated with the GMC G23.3−0.3; O and B-types satisfying this criterion have spectrophotometric distances consistent with that of the giant molecular cloud. Combining near-IR spectroscopic and photometric data allowed us to characterize the multiple sites of star formation within it. The O-type stars have masses from ~25–45 M⊙, and ages of 5–8 Myr. Two new red supergiants were detected with interstellar extinction typical of the cloud; along with the two RSGs within the cluster GLIMPSE9, they trace an older burst with an age of 20–30 Myr. Massive stars were also detected in the core of three supernova remnants – W41, G22.7−0.2, and G22.7583−0.4917.Conclusions. A large population of massive stars appears associated with the GMC G23.3−0.3, with the properties inferred for them indicative of an extended history of stars formation

The narrative self, distributed memory, and evocative objects

In this article, I outline various ways in which artifacts are interwoven with autobiographical memory systems and conceptualize what this implies for the self. I first sketch the narrative approach to the self, arguing that who we are as persons is essentially our (unfolding) life story, which, in turn, determines our present beliefs and desires, but also directs our future goals and actions. I then argue that our autobiographical memory is partly anchored in our embodied interactions with an ecology of artifacts in our environment. Lifelogs, photos, videos, journals, diaries, souvenirs, jewelry, books, works of art, and many other meaningful objects trigger and sometimes constitute emotionally-laden autobiographical memories. Autobiographical memory is thus distributed across embodied agents and various environmental structures. To defend this claim, I draw on and integrate distributed cognition theory and empirical research in human-technology interaction. Based on this, I conclude that the self is neither defined by psychological states realized by the brain nor by biological states realized by the organism, but should be seen as a distributed and relational construct

The institutional shaping of management: in the tracks of English individualism

Globalisation raises important questions about the shaping of economic action by cultural factors. This article explores the formation of what is seen by some as a prime influence on the formation of British management: individualism. Drawing on a range of historical sources, it argues for a comparative approach. In this case, the primary comparison drawn is between England and Scotland. The contention is that there is a systemic approach to authority in Scotland that can be contrasted to a personal approach in England. An examination of the careers of a number of Scottish pioneers of management suggests the roots of this systemic approach in practices of church governance. Ultimately this systemic approach was to take a secondary role to the personal approach engendered by institutions like the universities of Oxford and Cambridge, but it found more success in the different institutional context of the USA. The complexities of dealing with historical evidence are stressed, as is the value of taking a comparative approach. In this case this indicates a need to take religious practice as seriously as religious belief as a source of transferable practice. The article suggests that management should not be seen as a simple response to economic imperatives, but as shaped by the social and cultural context from which it emerges

Under pressure: Response urgency modulates striatal and insula activity during decision-making under risk

When deciding whether to bet in situations that involve potential monetary loss or gain (mixed gambles), a subjective sense of pressure can influence the evaluation of the expected utility associated with each choice option. Here, we explored how gambling decisions, their psychophysiological and neural counterparts are modulated by an induced sense of urgency to respond. Urgency influenced decision times and evoked heart rate responses, interacting with the expected value of each gamble. Using functional MRI, we observed that this interaction was associated with changes in the activity of the striatum, a critical region for both reward and choice selection, and within the insula, a region implicated as the substrate of affective feelings arising from interoceptive signals which influence motivational behavior. Our findings bridge current psychophysiological and neurobiological models of value representation and action-programming, identifying the striatum and insular cortex as the key substrates of decision-making under risk and urgency

Mapping habitat indices across river networks using spatial statistical modelling of River Habitat Survey data

Freshwater ecosystems are declining faster than their terrestrial and marine counterparts because of physical pressures on habitats. European legislation requires member states to achieve ecological targets through the effective management of freshwater habitats. Maps of habitats across river networks would help diagnose environmental problems and plan for the delivery of improvement work. Existing habitat mapping methods are generally time consuming, require experts and are expensive to implement. Surveys based on sampling are cheaper but provide patchy representations of habitat distribution. In this study, we present a method for mapping habitat indices across networks using semi-quantitative data and a geostatistical technique called regression kriging. The method consists of the derivation of habitat indices using multivariate statistical techniques that are regressed on map-based covariates such as altitude, slope and geology. Regression kriging combines the Generalised Least Squares (GLS) regression technique with a spatial analysis of model residuals. Predictions from the GLS model are ‘corrected’ using weighted averages of model residuals following an analysis of spatial correlation. The method was applied to channel substrate data from the River Habitat Survey in Great Britain. A Channel Substrate Index (CSI) was derived using Correspondence Analysis and predicted using regression kriging. The model explained 74% of the main sample variability and 64% in a test sample. The model was applied to the English and Welsh river network and a map of CSI was produced. The proposed approach demonstrates how existing national monitoring data and geostatistical techniques can be used to produce continuous maps of habitat indices at the national scale