Modeling mixture transport at the nanoscale: Departure from existing paradigms

We present a novel theory of mixture transport in nanopores, which represents wall effects via a species-specific friction coefficient determined by its low density diffusion coefficient. Onsager coefficients from the theory are in good agreement with those from molecular dynamics simulation, when the nonuniformity of the density distribution is included. It is found that the commonly used assumption of a uniform density in the momentum balance is in serious error, as is also the traditional use of a mixture center of mass based frame of reference

Effect of Hindlimb Unweighting on Tissue Blood Flow in the Rat

The purpose of this study was to characterize the distribution of blood flow in the rat during hindlimb unweighting (HU) and post-HU standing and exercise and examine whether the previously reported elevation in anaerobic metabolism observed with contractile activity in the atrophied soleus muscle was caused by a reduced hindlimb blood flow. After either 15 days of HU or cage control, blood flow was measured with radioactive microspheres during unweighting, normal standing, and running on a treadmill (15 m/min). In another group of control and experimental animals, blood flow was measured during preexercise (PE) treadmill standing and treadmill running (15 m/min). Soleus muscle blood flow was not different between groups during unweighting, PE standing, and running at 15 m/min. Chronic unweighting resulted in the tendency for greater blood flow to muscles composed of predominantly fast-twitch glycolytic fibers. With exercise, blood flow to visceral organs was reduced compared with PE values in the control rats, whereas flow to visceral organs in 15-day HU animals was unaltered by exercise. These higher flows to the viscera and to muscles composed of predominantly fast-twitch glycolytic fibers suggest an apparent reduction in the ability of the sympathetic nervous system to distribute cardiac output after chronic HU. In conclusion, because 15 days of HU did not affect blood flow to the soleus during exercise, the increased dependence of the atrophied soleus on anerobic energy production during contractile activity cannot be explained by a reduced muscle blood flow

The effect of distance on reaction time in aiming movements

Target distance affects movement duration in aiming tasks but its effect on reaction time (RT) is poorly documented. RT is a function of both preparation and initiation. Experiment 1 pre-cued movement (allowing advanced preparation) and found no influence of distance on RT. Thus, target distance does not affect initiation time. Experiment 2 removed pre-cue information and found that preparing a movement of increased distance lengthens RT. Experiment 3 explored movements to targets of cued size at non-cued distances and found size altered peak speed and movement duration but RT was influenced by distance alone. Thus, amplitude influences preparation time (for reasons other than altered duration) but not initiation time. We hypothesise that the RT distance effect might be due to the increased number of possible trajectories associated with further targets: a hypothesis that can be tested in future experiments

SIDM on FIRE: Hydrodynamical Self-Interacting Dark Matter simulations of low-mass dwarf galaxies

We compare a suite of four simulated dwarf galaxies formed in 10$^{10} M_{\odot}$ haloes of collisionless Cold Dark Matter (CDM) with galaxies simulated in the same haloes with an identical galaxy formation model but a non-zero cross-section for dark matter self-interactions. These cosmological zoom-in simulations are part of the Feedback In Realistic Environments (FIRE) project and utilize the FIRE-2 model for hydrodynamics and galaxy formation physics. We find the stellar masses of the galaxies formed in Self-Interacting Dark Matter (SIDM) with $\sigma/m= 1\, cm^2/g$ are very similar to those in CDM (spanning $M_{\star} \approx 10^{5.7 - 7.0} M_{\odot}$) and all runs lie on a similar stellar mass -- size relation. The logarithmic dark matter density slope ($\alpha=d\log \rho / d\log r$) in the central $250-500$ pc remains steeper than $\alpha= -0.8$ for the CDM-Hydro simulations with stellar mass $M_{\star} \sim 10^{6.6} M_{\odot}$ and core-like in the most massive galaxy. In contrast, every SIDM hydrodynamic simulation yields a flatter profile, with $\alpha >-0.4$. Moreover, the central density profiles predicted in SIDM runs without baryons are similar to the SIDM runs that include FIRE-2 baryonic physics. Thus, SIDM appears to be much more robust to the inclusion of (potentially uncertain) baryonic physics than CDM on this mass scale, suggesting SIDM will be easier to falsify than CDM using low-mass galaxies. Our FIRE simulations predict that galaxies less massive than $M_{\star} < 3 \times 10^6 M_{\odot}$ provide potentially ideal targets for discriminating models, with SIDM producing substantial cores in such tiny galaxies and CDM producing cusps.Comment: 10 Pages, 7 figures, submitted to MNRA

Mapping between dissipative and Hamiltonian systems

Theoretical studies of nonequilibrium systems are complicated by the lack of a general framework. In this work we first show that a transformation introduced by Ao recently (J. Phys. A {\bf 37}, L25 (2004)) is related to previous works of Graham (Z. Physik B {\bf 26}, 397 (1977)) and Eyink {\it et al.} (J. Stat. Phys. {\bf 83}, 385 (1996)), which can also be viewed as the generalized application of the Helmholtz theorem in vector calculus. We then show that systems described by ordinary stochastic differential equations with white noise can be mapped to thermostated Hamiltonian systems. A steady-state of a dissipative system corresponds to the equilibrium state of the corresponding Hamiltonian system. These results provides a solid theoretical ground for corresponding studies on nonequilibrium dynamics, especially on nonequilibrium steady state. The mapping permits the application of established techniques and results for Hamiltonian systems to dissipative non-Hamiltonian systems, those for thermodynamic equilibrium states to nonequilibrium steady states. We discuss several implications of the present work.Comment: 18 pages, no figure. final version for publication on J. Phys. A: Math & Theo

The Integrated Medical Model: Statistical Forecasting of Risks to Crew Health and Mission Success

The Integrated Medical Model (IMM) helps capture and use organizational knowledge across the space medicine, training, operations, engineering, and research domains. The IMM uses this domain knowledge in the context of a mission and crew profile to forecast crew health and mission success risks. The IMM is most helpful in comparing the risk of two or more mission profiles, not as a tool for predicting absolute risk. The process of building the IMM adheres to Probability Risk Assessment (PRA) techniques described in NASA Procedural Requirement (NPR) 8705.5, and uses current evidence-based information to establish a defensible position for making decisions that help ensure crew health and mission success. The IMM quantitatively describes the following input parameters: 1) medical conditions and likelihood, 2) mission duration, 3) vehicle environment, 4) crew attributes (e.g. age, sex), 5) crew activities (e.g. EVA's, Lunar excursions), 6) diagnosis and treatment protocols (e.g. medical equipment, consumables pharmaceuticals), and 7) Crew Medical Officer (CMO) training effectiveness. It is worth reiterating that the IMM uses the data sets above as inputs. Many other risk management efforts stop at determining only likelihood. The IMM is unique in that it models not only likelihood, but risk mitigations, as well as subsequent clinical outcomes based on those mitigations. Once the mathematical relationships among the above parameters are established, the IMM uses a Monte Carlo simulation technique (a random sampling of the inputs as described by their statistical distribution) to determine the probable outcomes. Because the IMM is a stochastic model (i.e. the input parameters are represented by various statistical distributions depending on the data type), when the mission is simulated 10-50,000 times with a given set of medical capabilities (risk mitigations), a prediction of the most probable outcomes can be generated. For each mission, the IMM tracks which conditions occurred and decrements the pharmaceuticals and supplies required to diagnose and treat these medical conditions. If supplies are depleted, then the medical condition goes untreated, and crew and mission risk increase. The IMM currently models approximately 30 medical conditions. By the end of FY2008, the IMM will be modeling over 100 medical conditions, approximately 60 of which have been recorded to have occurred during short and long space missions

Macroscopic fluctuation theory

Stationary non-equilibrium states describe steady flows through macroscopic systems. Although they represent the simplest generalization of equilibrium states, they exhibit a variety of new phenomena. Within a statistical mechanics approach, these states have been the subject of several theoretical investigations, both analytic and numerical. The macroscopic fluctuation theory, based on a formula for the probability of joint space-time fluctuations of thermodynamic variables and currents, provides a unified macroscopic treatment of such states for driven diffusive systems. We give a detailed review of this theory including its main predictions and most relevant applications.Comment: Review article. Revised extended versio

Thermodynamic Field Theory with the Iso-Entropic Formalism

A new formulation of the thermodynamic field theory (TFT) is presented. In this new version, one of the basic restriction in the old theory, namely a closed-form solution for the thermodynamic field strength, has been removed. In addition, the general covariance principle is replaced by Prigogine's thermodynamic covariance principle (TCP). The introduction of TCP required the application of an appropriate mathematical formalism, which has been referred to as the iso-entropic formalism. The validity of the Glansdorff-Prigogine Universal Criterion of Evolution, via geometrical arguments, is proven. A new set of thermodynamic field equations, able to determine the nonlinear corrections to the linear ("Onsager") transport coefficients, is also derived. The geometry of the thermodynamic space is non-Riemannian tending to be Riemannian for hight values of the entropy production. In this limit, we obtain again the same thermodynamic field equations found by the old theory. Applications of the theory, such as transport in magnetically confined plasmas, materials submitted to temperature and electric potential gradients or to unimolecular triangular chemical reactions can be found at references cited herein.Comment: 35 page

Dwarf galaxy mass estimators versus cosmological simulations

We use a suite of high-resolution cosmological dwarf galaxy simulations to test the accuracy of commonly used mass estimators from Walker et al. (2009) and Wolf et al. (2010), both of which depend on the observed line-of-sight velocity dispersion and the 2D half-light radius of the galaxy, R_e. The simulations are part of the Feedback in Realistic Environments (FIRE) project and include 12 systems with stellar masses spanning 10^5–10^7 M⊙ that have structural and kinematic properties similar to those of observed dispersion-supported dwarfs. Both estimators are found to be quite accurate: M_(Wolf)/M_(true) = 0.98^(+0.19)_(−0.12) and M_(Walker)/M_(true) = 1.07^(+0.21)_(−0.15), with errors reflecting the 68 per cent range over all simulations. The excellent performance of these estimators is remarkable given that they each assume spherical symmetry, a supposition that is broken in our simulated galaxies. Though our dwarfs have negligible rotation support, their 3D stellar distributions are flattened, with short-to-long axis ratios c/a ≃ 0.4–0.7. The median accuracy of the estimators shows no trend with asphericity. Our simulated galaxies have sphericalized stellar profiles in 3D that follow a nearly universal form, one that transitions from a core at small radius to a steep fall-off ∝r^(−4.2) at large r; they are well fit by Sérsic profiles in projection. We find that the most important empirical quantity affecting mass estimator accuracy is R_e. Determining R_e by an analytic fit to the surface density profile produces a better estimated mass than if the half-light radius is determined via direct summation