Implications of Saito's coronal density model on the polar solar wind flow and heavy ion abundances

A comparison of polar solar wind proton flux upper limits derived using a coronal density model, with Lyman alpha measurements of the length of the neutral H tail of comet Bennet at high latitudes, shows that either extended heating beyond 2 solar radii is necessary some of the time or that the model's polar densities are too low. Whichever possibility is the case, the fact that the solar wind particle flux does not appear to decrease with increasing latitude indicates that the heavy element content of the high latitude wind may be similar to that observed in the ecliptic. It was then shown that solar wind heavy ion observations at high latitudes allow a determination of the electron temperature at heights which bracket the nominal location of the coronal temperature maximum thus providing information concerning the magnitude and extent of mechanical dissipation in the intermediate corona

A Lunar Penetrator to Determine Solar-wind-implanted Resources at Depth in the Lunar Regolith

Several volatiles implanted into the lunar regolith by the solar wind are potentially important lunar resources. He-3 might be mined as a fuel for lunar nuclear fusion reactors. Even if the mining of He-3 turns out not to be feasible, several other elements commonly implanted by the solar wind (H,C, and N) could be important for life support and for propellant or fuel production for lunar bases. A simple penetrator-borne instrument package to measure the abundance of H at depth is proposed. Since solar-wind-implanted volatiles tend to correlate with one another, this can be used to estimate global inventories and to design extraction strategies for all of these species

A Rigorous Proof of Fermi Liquid Behavior for Jellium Two-Dimensional Interacting Fermions

Using the method of continuous constructive renormalization group around the Fermi surface, it is proved that a jellium two-dimensional interacting system of Fermions at low temperature $T$ remains analytic in the coupling constant $\lambda$ for $|\lambda| |\log T| \le K$ where $K$ is some numerical constant and $T$ is the temperature. Furthermore in that range of parameters, the first and second derivatives of the self-energy remain bounded, a behavior which is that of Fermi liquids and in particular excludes Luttinger liquid behavior. Our results prove also that in dimension two any transition temperature must be non-perturbative in the coupling constant, a result expected on physical grounds. The proof exploits the specific momentum conservation rules in two dimensions.Comment: 4 pages, no figure

Functional Equations and the Generalised Elliptic Genus

We give a new derivation and characterisation of the generalised elliptic genus of Krichever-H\"ohn by means of a functional equation.Comment: To be published in the collection honouring Francesco Calogero's 70-th birthda

Optimization Techniques for the Power Beaming Analysis of Microwave Transmissions from a Space-Based Solar Power Satellite

In the 21st century, the development of technologies to produce carbon free power sources remains paramount. In this paper, we study an optimal power transmission strategy from a space-based satellite generation station to Earth using scalar diffraction theory. The resulting model is then solved via a spectral method that guarantees a compactly supposed profile from the transmitting antenna. Finally, the problem is then solved via a more general pseudo-spectral method using control theory

Interstellar helium in interplanetary space

The velocity distribution function of He(+) in the solar wind at 1 AU is calculated with the assumption that the source is photoionization of a cold (T = 100 K), neutral interstellar wind. If the spiral magnetic field is noise free, the velocity distribution is diffuse and would not produce a peak at 4(E over Q) sub H in an E over Q particle spectrum. If the velocity of the interstellar wind with respect to the sun lies in the ecliptic, a large variation of the He(+) number density with respect to ecliptic longitude is expected

Situating emotional experience

Psychological construction approaches to emotion suggest that emotional experience is situated and dynamic. Fear, for example, is typically studied in a physical danger context (e.g., threatening snake), but in the real world, it often occurs in social contexts, especially those involving social evaluation (e.g., public speaking). Understanding situated emotional experience is critical because adaptive responding is guided by situational context (e.g., inferring the intention of another in a social evaluation situation vs. monitoring the environment in a physical danger situation). In an fMRI study, we assessed situated emotional experience using a newly developed paradigm in which participants vividly imagine different scenarios from a first-person perspective, in this case scenarios involving either social evaluation or physical danger. We hypothesized that distributed neural patterns would underlie immersion in social evaluation and physical danger situations, with shared activity patterns across both situations in multiple sensory modalities and in circuitry involved in integrating salient sensory information, and with unique activity patterns for each situation type in coordinated large-scale networks that reflect situated responding. More specifically, we predicted that networks underlying the social inference and mentalizing involved in responding to a social threat (in regions that make up the “default mode” network) would be reliably more active during social evaluation situations. In contrast, networks underlying the visuospatial attention and action planning involved in responding to a physical threat would be reliably more active during physical danger situations. The results supported these hypotheses. In line with emerging psychological construction approaches, the findings suggest that coordinated brain networks offer a systematic way to interpret the distributed patterns that underlie the diverse situational contexts characterizing emotional life

Effect of a machine learning-based severe sepsis prediction algorithm on patient survival and hospital length of stay: a randomised clinical trial.

IntroductionSeveral methods have been developed to electronically monitor patients for severe sepsis, but few provide predictive capabilities to enable early intervention; furthermore, no severe sepsis prediction systems have been previously validated in a randomised study. We tested the use of a machine learning-based severe sepsis prediction system for reductions in average length of stay and in-hospital mortality rate.MethodsWe conducted a randomised controlled clinical trial at two medical-surgical intensive care units at the University of California, San Francisco Medical Center, evaluating the primary outcome of average length of stay, and secondary outcome of in-hospital mortality rate from December 2016 to February 2017. Adult patients (18+) admitted to participating units were eligible for this factorial, open-label study. Enrolled patients were assigned to a trial arm by a random allocation sequence. In the control group, only the current severe sepsis detector was used; in the experimental group, the machine learning algorithm (MLA) was also used. On receiving an alert, the care team evaluated the patient and initiated the severe sepsis bundle, if appropriate. Although participants were randomly assigned to a trial arm, group assignments were automatically revealed for any patients who received MLA alerts.ResultsOutcomes from 75 patients in the control and 67 patients in the experimental group were analysed. Average length of stay decreased from 13.0 days in the control to 10.3 days in the experimental group (p=0.042). In-hospital mortality decreased by 12.4 percentage points when using the MLA (p=0.018), a relative reduction of 58.0%. No adverse events were reported during this trial.ConclusionThe MLA was associated with improved patient outcomes. This is the first randomised controlled trial of a sepsis surveillance system to demonstrate statistically significant differences in length of stay and in-hospital mortality.Trial registrationNCT03015454