Why indifference is the best reaction to President Obama’s executive actions on guns.

The recent executive actions on gun control announced by President Obama have been met with both applause and criticism. Any response other than indifference is probably an overreaction, writes Matthew Lang. If the President’s actions are eventually carried out, background checks will rise as more private firearm sellers become legally viewed as dealers. The increase in background checks is unlikely to have any effect on gun-related deaths. Instead, he argues, President Obama’s announcement will most likely increase the number of firearms purchased by gun advocates, as is typically the case whenever gun owners perceive a possible threat to the Second Amendment. According to recent research, firearm-related deaths are unlikely to respond to an increase in the number of guns per household. Reducing gun violence will take more than redefining what it means to be a firearms dealer

Tighter gun laws may lead to fewer suicides

Monthly firearm background checks have been recorded in every US state since 1998, making it possible to explore whether changes in the availability of firearms in a state are related to its suicide rate. This relationship has been difficult to research in the past, as the fraction of suicides using firearms are a commonly used measure of firearms. Matthew Lang finds that increases in state background checks are associated with slight increases in the total suicide rate, suggesting that the increased availability of particular suicide method can lead to more suicides

Quantifying the latitudinal representivity of in situ solar wind observations

Advanced space-weather forecasting relies on the ability to accurately predict near-Earth solar wind conditions. For this purpose, physics-based, global numerical models of the solar wind are initialized with photospheric magnetic field and coronagraph observations, but no further observation constraints are imposed between the upper corona and Earth orbit. Data assimilation (DA) of the available in situ solar wind observations into the models could potentially provide additional constraints, improving solar wind reconstructions, and forecasts. However, in order to effectively combine the model and observations, it is necessary to quantify the error introduced by assuming point measurements are representative of the model state. In particular, the range of heliographic latitudes over which in situ solar wind speed measurements are representative is of primary importance, but particularly difficult to assess from observations alone. In this study we use 40+ years of observation-driven solar wind model results to assess two related properties: the latitudinal representivity error introduced by assuming the solar wind speed measured at a given latitude is the same as that at the heliographic equator, and the range of latitudes over which a solar wind measurement should influence the model state, referred to as the observational localisation. These values are quantified for future use in solar wind DA schemes as a function of solar cycle phase, measurement latitude, and error tolerance. In general, we find that in situ solar wind speed measurements near the ecliptic plane at solar minimum are extremely localised, being similar over only 1° or 2° of latitude. In the uniform polar fast wind above approximately 40° latitude at solar minimum, the latitudinal representivity error drops. At solar maximum, the increased variability of the solar wind speed at high latitudes means that the latitudinal representivity error increases at the poles, though becomes greater in the ecliptic, as long as moderate speed errors can be tolerated. The heliospheric magnetic field and solar wind density and temperature show very similar behaviour

A systematic method of parameterisation estimation using data assimilation

In numerical weather prediction, parameterisations are used to simulate missing physics in the model. These can be due to a lack of scientific understanding or a lack of computing power available to address all the known physical processes. Parameterisations are sources of large uncertainty in a model as parameter values used in these parameterisations cannot be measured directly and hence are often not well known; and the parameterisations themselves are also approximations of the processes present in the true atmosphere. Whilst there are many efficient and effective methods for combined state/parameter estimation in data assimilation (DA), such as state augmentation, these are not effective at estimating the structure of parameterisations. A new method of parameterisation estimation is proposed that uses sequential DA methods to estimate errors in the numerical models at each space-time point for each model equation. These errors are then fitted to pre-determined functional forms of missing physics or parameterisations that are based upon prior information. We applied the method to a one-dimensional advection model with additive model error, and it is shown that the method can accurately estimate parameterisations, with consistent error estimates. Furthermore, it is shown how the method depends on the quality of the DA results. The results indicate that this new method is a powerful tool in systematic model improvement

Geodesic Warps by Conformal Mappings

In recent years there has been considerable interest in methods for diffeomorphic warping of images, with applications e.g.\ in medical imaging and evolutionary biology. The original work generally cited is that of the evolutionary biologist D'Arcy Wentworth Thompson, who demonstrated warps to deform images of one species into another. However, unlike the deformations in modern methods, which are drawn from the full set of diffeomorphism, he deliberately chose lower-dimensional sets of transformations, such as planar conformal mappings. In this paper we study warps of such conformal mappings. The approach is to equip the infinite dimensional manifold of conformal embeddings with a Riemannian metric, and then use the corresponding geodesic equation in order to obtain diffeomorphic warps. After deriving the geodesic equation, a numerical discretisation method is developed. Several examples of geodesic warps are then given. We also show that the equation admits totally geodesic solutions corresponding to scaling and translation, but not to affine transformations

Towards construction of a solar wind “reanalysis” dataset: application to the first perihelion pass of parker solar probe

Accurate reconstruction of global solar-wind structure is essential for connecting remote and in situ observations of solar plasma, and hence understanding formation and release of solar wind. Information can routinely be obtained from photospheric magnetograms, via coronal and solar-wind modelling, and directly from in situ observations, typically at large heliocentric distances (most commonly near 1 AU). Magnetogram-constrained modelling has the benefit of reconstructing global solar-wind structure, but with relatively large spatial and/or temporal errors. In situ observations, on the other hand, make accurate temporal measurements of solar-wind structure, but are highly localised. We here use a data assimilative (DA) approach to combine these two sources of information as a first step towards producing a solar-wind “reanalysis” dataset that optimally combines model and observation. The physics of solar wind stream interaction is used to extrapolate in heliocentric distance, while the assumption of steady-state solar-wind structure enables extrapolation in longitude. The major challenge is extrapolating in latitude. Using solar-wind speed during the interval of the first perihelion pass of Parker Solar Probe (PSP) in November 2018 as a test bed, we investigate two approaches. The first is to assume the solar wind is two-dimensional and thus has no latitudinal structure within the ±7∘ bounded by the heliographic equatorial and ecliptic planes. The second assumes in situ solar-wind observations are representative of some (small) latitudinal range. We show how observations of the inner heliosphere, such as will be provided by PSP, can be exploited to constrain the latitudinal representivity of solar-wind observations to improve future solar-wind reconstruction and space-weather forecasting

Neck linker docking is critical for Kinesin-1 force generation in cells but at a cost to motor speed and processivity.

Kinesin force generation involves ATP-induced docking of the neck linker (NL) along the motor core. However, the roles of the proposed steps of NL docking, cover-neck bundle (CNB) and asparagine latch (N-latch) formation, during force generation are unclear. Furthermore, the necessity of NL docking for transport of membrane-bound cargo in cells has not been tested. We generated kinesin-1 motors impaired in CNB and/or N-latch formation based on molecular dynamics simulations. The mutant motors displayed reduced force output and inability to stall in optical trap assays but exhibited increased speeds, run lengths, and landing rates under unloaded conditions. NL docking thus enhances force production but at a cost to speed and processivity. In cells, teams of mutant motors were hindered in their ability to drive transport of Golgi elements (high-load cargo) but not peroxisomes (low-load cargo). These results demonstrate that the NL serves as a mechanical element for kinesin-1 transport under physiological conditions

The evolution of inverted magnetic fields through the inner heliosphere

Local inversions are often observed in the heliospheric magnetic field (HMF), but their origins and evolution are not yet fully understood.Parker Solar Probe has recently observed rapid, Alfvénic, HMF inversions in the inner heliosphere, known as ‘switchbacks’, which have been interpreted as the possible remnants of coronal jets. It has also been suggested that inverted HMF may be produced by near-Sun interchange reconnection; a key process in mechanisms proposed for slow solar wind release. These cases suggest that the source of inverted HMF is near the Sun, and it follows that these inversions would gradually decay and straighten as they propagate out through the heliosphere. Alternatively, HMF inversions could form during solar wind transit, through phenomena such velocity shears, draping over ejecta, or waves and turbulence. Such processes are expected to lead to a qualitatively radial evolution of inverted HMF structures. Using Helios measurements spanning 0.3–1 AU, we examine the occurrence rate of inverted HMF, as well as other magnetic field morphologies, as a function of radial distance r, and find that it continually increases. This trend may be explained by inverted HMF observed between 0.3–1 AU being primarily driven by one or more of the above in-transit processes, rather than created at the Sun. We make suggestions as to the relative importance of these different processes based on the evolution of the magnetic field properties associated with inverted HMF. We also explore alternative explanations outside of our suggested driving processes which may lead to the observed trend

Passive and active microrheology for cross-linked F-actin networks in vitro

Actin filament (F-actin) is one of the dominant structural constituents in the cytoskeleton. Orchestrated by various actin-binding proteins (ABPs), F-actin is assembled into higher-order structures such as bundles and networks that provide mechanical support for the cell and play important roles in numerous cellular processes. Although mechanical properties of F-actin networks have been extensively studied, the underlying mechanisms for network elasticity are not fully understood, in part because different measurements probe different length and force scales. Here, we developed both passive and active microrheology techniques using optical tweezers to estimate the mechanical properties of F-actin networks at a length scale comparable to cells. For the passive approach we tracked the motion of a thermally fluctuating colloidal sphere to estimate the frequency-dependent complex shear modulus of the network. In the active approach, we used an optical trap to oscillate an embedded microsphere and monitored the response in order to obtain network viscoelasticity over a physiologically relevant force range. While both active and passive measurements exhibit similar results at low strain, the F-actin network subject to high strain exhibits non-linear behavior which is analogous to the strain-hardening observed in macroscale measurements. Using confocal and total internal reflection fluorescent microscopy, we also characterize the microstructure of reconstituted F-actin networks in terms of filament length, mesh size and degree of bundling. Finally, we propose a model of network connectivity by investigating the effect of filament length on the mechanical properties and structure.Singapore-MIT Alliance for Research and Technology (SMART)National Institute of General Medical Sciences (U.S.) (NIGMS (GM076689))National Science Foundation (U.S.) (NSF Career Award (0643745))Nicholas Hobson Wheeles, Jr. (Fellowship)W. M. Keck FoundationWestaway Research Fun