Simulating UAS: How Much Fidelity and Why?

The physical, functional, and operational fidelity of a simulation can impact design assessments, training device effectiveness, and the validity of research results done with desk-top simulators (or synthetic tasks). While difficult to quantify, fidelity issues need to be considered in each of these contexts as attempts are made to improve human system integration. This paper reviews some of the implications of fidelity, discusses current efforts to model the impacts training can have on performance, and outlines the kinds of empirical testing that could be done to compare Improved Performance Research Integration Tool (IMPRINT) model predictions of training impacts to actual performance

Speeding up to keep up: exploring the use of AI in the research process.

There is a long history of the science of intelligent machines and its potential to provide scientific insights have been debated since the dawn of AI. In particular, there is renewed interest in the role of AI in research and research policy as an enabler of new methods, processes, management and evaluation which is still relatively under-explored. This empirical paper explores interviews with leading scholars on the potential impact of AI on research practice and culture through deductive, thematic analysis to show the issues affecting academics and universities today. Our interviewees identify positive and negative consequences for research and researchers with respect to collective and individual use. AI is perceived as helpful with respect to information gathering and other narrow tasks, and in support of impact and interdisciplinarity. However, using AI as a way of 'speeding up-to keep up' with bureaucratic and metricised processes, may proliferate negative aspects of academic culture in that the expansion of AI in research should assist and not replace human creativity. Research into the future role of AI in the research process needs to go further to address these challenges, and ask fundamental questions about how AI might assist in providing new tools able to question the values and principles driving institutions and research processes. We argue that to do this an explicit movement of meta-research on the role of AI in research should consider the effects for research and researcher creativity. Anticipatory approaches and engagement of diverse and critical voices at policy level and across disciplines should also be considered

Expert views about missing AI narratives: is there an AI story crisis?

Stories are an important indicator of our vision of the future. In the case of artificial intelligence (AI), dominant stories are polarized between notions of threat and myopic solutionism. The central storytellers-big tech, popular media, and authors of science fiction-represent particular demographics and motivations. Many stories, and storytellers, are missing. This paper details the accounts of missing AI narratives by leading scholars from a range of disciplines interested in AI Futures. Participants focused on the gaps between dominant narratives and the untold stories of the capabilities, issues, and everyday realities of the technology. One participant proposed a "story crisis" in which these narratives compete to shape the public discourse on AI. Our findings indicate that dominant narratives distract and mislead public understandings and conceptions of AI. This suggests a need to pay closer attention to missing AI narratives. It is not simply about telling new stories, it is about listening to existing stories and asking what is wanted from AI. We call for realistic, nuanced, and inclusive stories, working with and for diverse voices, which consider (1) story-teller; (2) genre, and (3) communicative purpose. Such stories can then inspire the next generation of thinkers, technologists, and storytellers

Multiple cell and population-level interactions with mouse embryonic stem cell heterogeneity

Much of development and disease concerns the generation of gene expression differences between related cells sharing similar niches. However, most analyses of gene expression only assess population and time-averaged levels of steady-state transcription. The mechanisms driving differentiation are buried within snapshots of the average cell, lacking dynamic information and the diverse regulatory history experienced by individual cells. Here, we use a quantitative imaging platform with large time series data sets to determine the regulation of developmental gene expression by cell cycle, lineage, motility and environment. We apply this technology to the regulation of the pluripotency gene Nanog in mouse embryonic stem cells. Our data reveal the diversity of cell and population-level interactions with Nanog dynamics and heterogeneity, and how this regulation responds to triggers of pluripotency. Cell cycles are highly heterogeneous and cycle time increases with Nanog reporter expression, with longer, more variable cycle times as cells approach ground-state pluripotency. Nanog reporter expression is highly stable over multiple cell generations, with fluctuations within cycles confined by an attractor state. Modelling reveals an environmental component to expression stability, in addition to any cell-autonomous behaviour, and we identify interactions of cell density with both cycle behaviour and Nanog. Rex1 expression dynamics showed shared and distinct regulatory effects. Overall, our observations of multiple partially overlapping dynamic heterogeneities imply complex cell and environmental regulation of pluripotent cell behaviour, and suggest simple deterministic views of stem cell states are inappropriate

Three-component modelling of O-rich AGB star winds I. Effects of drift using forsterite

Stellar winds of cool and pulsating asymptotic giant branch (AGB) stars enrich the interstellar medium with large amounts of processed elements and various types of dust. We present the first study on the influence of gas-to-dust drift on ab initio simulations of stellar winds of M-type stars driven by radiation pressure on forsterite particles. Our study is based on our radiation hydrodynamic model code T-800 that includes frequency-dependent radiative transfer, dust extinction based on Mie scattering, grain growth and ablation, gas-to-dust drift using one mean grain size, a piston that simulates stellar pulsations, and an accurate high spatial resolution numerical scheme. To enable this study, we calculated new gas opacities based on the ExoMol database, and we extended the model code to handle the formation of minerals that may form in M-type stars. We determine the effects of drift by comparing drift models to our new and extant non-drift models. Three out of four new drift models show high drift velocities, 87-310 km/s. Our new drift model mass-loss rates are 1.7-13 per cent of the corresponding values of our non-drift models, but compared to the results of two extant non-drift models that use the same stellar parameters, these same values are 0.33-1.5 per cent. Meanwhile, a comparison of other properties such as the expansion velocity and grain size show similar values. Our results, which are based on single-component forsterite particles, show that the inclusion of gas-to-drift is of fundamental importance in stellar wind models driven by such transparent grains. Assuming that the drift velocity is insignificant, properties such as the mass-loss rate may be off from more realistic values by a factor of 50 or more.Comment: 15 pages, 6 figures, accepted and in pres

Infrared spectra of TiO2 clusters for hot Jupiter atmospheres

Context. Clouds seem unavoidable in cool and dense environments, and hence, are necessary to explain observations of exoplanet atmospheres, most recently of WASP 96b with JWST. Understanding the formation of cloud condensation nuclei in non-terrestrial environments is therefore crucial to develop accurate models to interpret present and future observations. Aims. The goal of the paper is to support observations with infrared spectra for (TiO2)N clusters in order to study cloud formation in exoplanet atmospheres. Methods. Vibrational frequencies are derived from quantum-chemical calculations for 123 (TiO2)-clusters and their isomers, and line-broadening mechanisms are evaluated. Cluster spectra are calculated for several atmospheric levels for two example exoplanet atmospheres (WASP 121b-like and WASP 96b-like) to identify possible spectral fingerprints for cloud formation. Results. Rotational motion of and transitions in the clusters cause significant line broadening, so that individual vibrational lines are broadened beyond the spectral resolution of the medium resolution mode of the JWST mid-infrared instrument MIRI at R = 3000. However, each individual cluster isomer exhibits a "fingerprint" IR spectrum. In particular, larger (TiO2)-clusters have distinctly different spectra from smaller clusters. Morning and evening terminator for the same planet can exhibit different total absorbances due to different cluster sizes being more abundant. Conclusions. The largest (TiO2)-clusters are not necessarily the most abundant (TiO2)-clusters in the high-altitude regions of ultra-hot Jupiters, and the different cluster isomers will contribute to the local absorbance. Planets with a considerable day-night asymmetry will be most suitable to search for (TiO2)-cluster isomers in order to improve cloud formation modelling.Comment: 8 pages, 8 figures, 1 table, accepted for publication in A&

Alpha voltaic batteries and methods thereof

An alpha voltaic battery includes at least one layer of a semiconductor material comprising at least one p/n junction, at least one absorption and conversion layer on the at least one layer of semiconductor layer, and at least one alpha particle emitter. The absorption and conversion layer prevents at least a portion of alpha particles from the alpha particle emitter from damaging the p/n junction in the layer of semiconductor material. The absorption and conversion layer also converts at least a portion of energy from the alpha particles into electron-hole pairs for collection by the one p/n junction in the layer of semiconductor material

C-reactive protein binds to alphaIIbbeta3.

C-reactive protein binds to alphaIIbbeta3

Rare Earth Doped High Temperature Ceramic Selective Emitters

As a result of their electron structure, rare earth ions in crystals at high temperature emit radiation in several narrow bands rather than in a continuous blackbody manner. This study develops a spectral emittance model for films of rare earth containing materials. Although there are several possible rare earth doped high temperature materials, this study was confined to rare earth aluminum garnets. Good agreement between experimental and theoretical spectral emittances was found for erbium, thulium and erbium-holmium aluminum garnets. Spectral emittances of these films are sensitive to temperature differences across the film. Emitter efficiency is also a sensitive function of temperature. For thulium aluminum garnet the efficiency is 0.38 at 1700 K but only 0.19 at 1262 K