The Impact of Atmospheric Fluctuations on Optimal Boost Glide Hypersonic Vehicle Dynamics

A project under the management of Air Force Research Laboratory has begun development of a six degree of freedom model for use in hypersonic vehicle development and application. One area of interest is the perturbation of vehicle behavior based on atmospheric fluctuations – how the performance of the vehicle changes with respect to “hot”, “cold” and standard day conditions. The method developed to fill this need uses real-world data from the Global Forecast System to create a “hot” and “cold” day dataset to compare with the standard day model. The key parameter is atmospheric density, a value calculated over a series of given points around the globe for any given dataset on a given day, and which directly impacts the lift and drag acting on the hypersonic vehicle, primarily over its re-entry trajectory. The results from simulations demonstrate trends that contradict expectation – the colder day cases result in a further longitude being achieved on average and yet experience a higher average drag. The optimal solution fluctuated 5-10% of the total range, or approximately 1.5 degrees in longitude, with matching orders of magnitude in fluctuations in the force of drag acting on the vehicle. General trends are stable – the two key trends with respect to longitude and drag remain true overall – the “cold” day cases have both the largest average drag and the longest distance traveled. Some analysis of the results proves these are reasonable results. These results enhance the strategic picture, but more test cases and analysis must be done before this model is ready for use

Low Reynolds number hydrodynamics of asymmetric, oscillating dumbbell pairs

Active dumbbell suspensions constitute one of the simplest model system for collective swimming at low Reynolds number. Generalizing recent work, we derive and analyze stroke-averaged equations of motion that capture the effective hydrodynamic far-field interaction between two oscillating, asymmetric dumbbells in three space dimensions. Time-averaged equations of motion, as those presented in this paper, not only yield a considerable speed-up in numerical simulations, they may also serve as a starting point when deriving continuum equations for the macroscopic dynamics of multi-swimmer suspensions. The specific model discussed here appears to be particularly useful in this context, since it allows one to investigate how the collective macroscopic behavior is affected by changes in the microscopic symmetry of individual swimmers.Comment: 10 pages, to appear in EPJ Special Topic

Stationarity, soft ergodicity, and entropy in relativistic systems

Recent molecular dynamics simulations show that a dilute relativistic gas equilibrates to a Juettner velocity distribution if ensemble velocities are measured simultaneously in the observer frame. The analysis of relativistic Brownian motion processes, on the other hand, implies that stationary one-particle distributions can differ depending on the underlying time-parameterizations. Using molecular dynamics simulations, we demonstrate how this relativistic phenomenon can be understood within a deterministic model system. We show that, depending on the time-parameterization, one can distinguish different types of soft ergodicity on the level of the one-particle distributions. Our analysis further reveals a close connection between time parameters and entropy in special relativity. A combination of different time-parameterizations can potentially be useful in simulations that combine molecular dynamics algorithms with randomized particle creation, annihilation, or decay processes.Comment: 4 page

Cultures of success: Recruiting and retaining new live-in residence life professionals

A qualitative inquiry designed to understand entry-level, live-in, professional staff recruitment and retention practices perceived as successful revealed a link to elements of organizational culture. Several important areas of understanding emerged: the actual recruitment and retention practices, the impact of leadership, and the role of organizational culture in the success of the department. This article addresses the impact of culture on the organization and its contribution to success in hiring and retaining entry-level staff. The discussion of findings and practical implications broadens our understanding of culture and better informs practice

The Simple Non-degenerate Relativistic Gas: Statistical Properties and Brownian Motion

This paper shows a novel calculation of the mean square displacement of a classical Brownian particle in a relativistic thermal bath. The result is compared with the expressions obtained by other authors. Also, the thermodynamic properties of a non-degenerate simple relativistic gas are reviewed in terms of a treatment performed in velocity space.Comment: 6 pages, 2 figure

Identification of X-chromosomal genes that drive global X-dosage effects in mammals

X-chromosomal genes contribute to sex differences, in particular during early development, whenboth X chromosomes are active in females. Here, double X-dosage shifts female pluripotent cells towards the naive stem cell state by increasing pluripotency factor expression, inhibiting thedifferentiation-promoting MAP kinase (MAPK) signalling pathway and delaying differentiation. Toidentify the genetic basis of these sex differences, we have performed a series of CRISPR knockoutscreens in murine embryonic stem cells to comprehensively identify X-linked genes that cause thefemale pluripotency phenotype. We found multiple genes that act in concert, among which Klhl13plays a central role. We show that this E3 ubiquitin ligase substrate adaptor protein promotes pluripotency factor expression, delays differentiation and represses MAPK target genes, and weidentify putative substrates. We thus elucidate the mechanisms that drive sex-induced differences inpluripotent cells with implications for gender medicine in the context of induced pluripotent stem cellbased therapies

Learning dynamical information from static protein and sequencing data

Many complex processes, from protein folding to neuronal network dynamics, can be described as stochastic exploration of a high-dimensional energy landscape. While efficient algorithms for cluster detection in high-dimensional spaces have been developed over the last two decades, considerably less is known about the reliable inference of state transition dynamics in such settings. Here, we introduce a flexible and robust numerical framework to infer Markovian transition networks directly from time-independent data sampled from stationary equilibrium distributions. We demonstrate the practical potential of the inference scheme by reconstructing the network dynamics for several protein folding transitions, gene-regulatory network motifs and HIV evolution pathways. The predicted network topologies and relative transition time scales agree well with direct estimates from time-dependent molecular dynamics data, stochastic simulations and phylogenetic trees, respectively. Owing to its generic structure, the framework introduced here will be applicable to high-throughput RNA and protein sequencing datasets and future cryo-electronmicroscopy data