Inequality and Electoral Accountability: Class-Biased Economic Voting in Comparative Perspective

Do electorates hold governments accountable for the distribution of economic welfare? Building on the finding of “class-biased economic voting” in the United States, we exam- ine how OECD electorates respond to alternative distributions of income gains and losses. Drawing on individual-level electoral data and aggregate election results across 15 advanced democracies, we examine whether lower- and middle-income voters defend their distributive interests by punishing governments for concentrating income gains among the rich. We find no indication that non-rich voters punish rising inequality, and substantial evidence that electorates positively reward the concentration of aggregate income growth at the top. Our results suggest that governments commonly face political incentives systematically skewed in favor of inegalitarian economic outcomes. At the same time, we find that the electorate’s tolerance of rising inequality has its limits: class biases in economic voting diminish as the income shares of the rich grow in magnitude

Whose News? Class-Biased Economic News in the United States

There is substantial evidence that voters’ choices are shaped by assessments of the state of the economy and that these assessments, in turn, are influenced by the news. But how does the economic news track the welfare of different income groups in an era of rising inequality? Whose economy does the news cover? Drawing on a large new dataset of US news content, we demonstrate that the tone of the economic news strongly and disproportionately tracks the fortunes of the richest households, with little sensitivity to income changes among the non-rich. Further, we present evidence that this pro-rich bias emerges not from pro-rich journalistic preferences but, rather, from the interaction of the media’s focus on economic aggregates with structural features of the relationship between economic growth and distribution. The findings yield a novel explanation of distributionally perverse electoral patterns and demonstrate how distributional biases in the economy condition economic accountability

Ab-initio solution of the many-electron Schrödinger equation with deep neural networks

Given access to accurate solutions of the many-electron Schr\"odinger equation, nearly all chemistry could be derived from first principles. Exact wavefunctions of interesting chemical systems are out of reach because they are NP-hard to compute in general, but approximations can be found using polynomially-scaling algorithms. The key challenge for many of these algorithms is the choice of wavefunction approximation, or Ansatz, which must trade off between efficiency and accuracy. Neural networks have shown impressive power as accurate practical function approximators and promise as a compact wavefunction Ansatz for spin systems, but problems in electronic structure require wavefunctions that obey Fermi-Dirac statistics. Here we introduce a novel deep learning architecture, the Fermionic Neural Network, as a powerful wavefunction Ansatz for many-electron systems. The Fermionic Neural Network is able to achieve accuracy beyond other variational quantum Monte Carlo Ans\"atze on a variety of atoms and small molecules. Using no data other than atomic positions and charges, we predict the dissociation curves of the nitrogen molecule and hydrogen chain, two challenging strongly-correlated systems, to significantly higher accuracy than the coupled cluster method, widely considered the most accurate scalable method for quantum chemistry at equilibrium geometry. This demonstrates that deep neural networks can improve the accuracy of variational quantum Monte Carlo to the point where it outperforms other ab-initio quantum chemistry methods, opening the possibility of accurate direct optimisation of wavefunctions for previously intractable molecules and solids

The JCMT Legacy Survey of the Gould Belt: Mapping 13CO and C 18O in Orion A

The Gould Belt Legacy Survey will map star-forming regions within 500 pc, using Heterodyne Array Receiver Programme (HARP), Submillimetre Common-User Bolometer Array 2 (SCUBA-2) and Polarimeter 2 (POL-2) on the James Clerk Maxwell Telescope (JCMT). This paper describes HARP observations of the J= 3 → 2 transitions of 13CO and C18O towards Orion A. The 15 arcsec resolution observations cover 5 pc of the Orion filament, including OMC 1 (including BN–KL and Orion bar), OMC 2/3 and OMC 4, and allow a comparative study of the molecular gas properties throughout the star-forming cloud. The filament shows a velocity gradient of ∼1 km s−1 pc−1 between OMC 1, 2 and 3, and high-velocity emission is detected in both isotopologues. The Orion Nebula and Bar have the largest masses and linewidths, and dominate the mass and energetics of the high-velocity material. Compact, spatially resolved emission from CH3CN, 13CH3OH, SO, HCOOCH3, CH3CHO and CH3OCHO is detected towards the Orion Hot Core. The cloud is warm, with a median excitation temperature of ∼24 K; the Orion Bar has the highest excitation temperature gas, at >80 K. The C18O excitation temperature correlates well with the dust temperature (to within 40 per cent). The C18O emission is optically thin, and the 13CO emission is marginally optically thick; despite its high mass, OMC 1 shows the lowest opacities. A virial analysis indicates that Orion A is too massive for thermal or turbulent support, but is consistent with a model of a filamentary cloud that is threaded by helical magnetic fields. The variation of physical conditions across the cloud is reflected in the physical characteristics of the dust cores. We find similar core properties between starless and protostellar cores, but variations in core properties with position in the filament. The OMC 1 cores have the highest velocity dispersions and masses, followed by OMC 2/3 and OMC 4. The differing fragmentation of these cores may explain why OMC 1 has formed clusters of high-mass stars, whereas OMC 4 produces fewer, predominantly low-mass stars

Analysis of the Herschel DEBRIS Sun-like star sample

This paper presents a study of circumstellar debris around Sun-like stars using data from the Herschel DEBRIS Key Programme. DEBRIS is an unbiased survey comprising the nearest ∼90 stars of each spectral type A-M. Analysis of the 275 F-K stars shows that excess emission from a debris disc was detected around 47 stars, giving a detection rate of 17.1 +2.6−2.3  per cent, with lower rates for later spectral types. For each target a blackbody spectrum was fitted to the dust emission to determine its fractional luminosity and temperature. The derived underlying distribution of fractional luminosity versus blackbody radius in the population showed that most detected discs are concentrated at f ∼ 10−5 and at temperatures corresponding to blackbody radii 7–40 au, which scales to ∼40 au for realistic dust properties (similar to the current Kuiper belt). Two outlying populations are also evident; five stars have exceptionally bright emission ( f > 5 × 10−5), and one has unusually hot dust <4 au. The excess emission distributions at all wavelengths were fitted with a steady-state evolution model, showing that these are compatible with all stars being born with a narrow belt that then undergoes collisional grinding. However, the model cannot explain the hot dust systems – likely originating in transient events – and bright emission systems – arising potentially from atypically massive discs or recent stirring. The emission from the present-day Kuiper belt is predicted to be close to the median of the population, suggesting that half of stars have either depleted their Kuiper belts (similar to the Solar system) or had a lower planetesimal formation efficiency.This work was supported by the European Union through European Research Council grant number 279973 (MCW, GMK). GMK was also supported by the Royal Society as a Royal Society University Research Fellow

A randomised controlled trial of cognitive behavioural treatment for obsessive compulsive disorder in children and adolescents

Cognitive behaviour therapy (CBT) for young people with obsessive compulsive disorder (OCD) has become the treatment of first choice. However, the literature is largely based on studies emphasising exposure and response prevention. In this study, we report on a randomised controlled trial of CBT for young people carried out in typical outpatient clinic conditions which focused on cognitions. A randomised controlled trial compares 10 sessions of manualised cognitive behavioural treatment with a 12-week waiting list for adolescents and children with OCD. Assessors were blind to treatment allocation. 21 consecutive patients with OCD aged between 9 and 18 years were recruited. The group who received treatment improved more than a comparison group who waited for 3 months. The second group was treated subsequently using the same protocol and made similar gains. In conclusion, CBT can be delivered effectively to young people with OCD in typical outpatient settings

Molecular dynamics simulations of oscillatory Couette flows with slip boundary conditions

The effect of interfacial slip on steady-state and time-periodic flows of monatomic liquids is investigated using non-equilibrium molecular dynamics simulations. The fluid phase is confined between atomically smooth rigid walls, and the fluid flows are induced by moving one of the walls. In steady shear flows, the slip length increases almost linearly with shear rate. We found that the velocity profiles in oscillatory flows are well described by the Stokes flow solution with the slip length that depends on the local shear rate. Interestingly, the rate dependence of the slip length obtained in steady shear flows is recovered when the slip length in oscillatory flows is plotted as a function of the local shear rate magnitude. For both types of flows, the friction coefficient at the liquid-solid interface correlates well with the structure of the first fluid layer near the solid wall.Comment: 31 pages, 11 figure

Muscle MRI reveals distinct abnormalities in genetically proven non-dystrophic myotonias.

We assessed the presence, frequency and pattern of MRI abnormalities in non-dystrophic myotonia patients. We reviewed T1-weighted and STIR (short-tau-inversion-recovery) 3T MRI sequences of lower limb muscles at thigh and calf level in 21 patients with genetically confirmed non-dystrophic myotonia: 11 with CLCN1 mutations and 10 with SCN4A mutations, and 19 healthy volunteers. The MRI examinations of all patients showed hyperintensity within muscles on either T1-weighted or STIR images. Mild extensive or marked T1-weighted changes were noted in 10/21 patients and no volunteers. Muscles in the thigh were equally likely to be affected but in the calf there was sparing of tibialis posterior. Oedema was common in calf musculature especially in the medial gastrocnemius with STIR hyperintensity observed in 18/21 patients. In 10/11 CLCN1 patients this included a previously unreported "central stripe", also present in 3/10 SCN4A patients but no volunteers. Degree of fatty infiltration correlated with age (rho=0.46, p<0.05). Muscle MRI is frequently abnormal in non-dystrophic myotonia providing evidence of fatty infiltration and/or oedema. The pattern is distinct from other myotonic disorders; in particular the "central stripe" has not been reported in other conditions. Correlations with clinical parameters suggest a potential role for MRI as a biomarker

From Nonspecific DNA–Protein Encounter Complexes to the Prediction of DNA–Protein Interactions

©2009 Gao, Skolnick. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.doi:10.1371/journal.pcbi.1000341DNA–protein interactions are involved in many essential biological activities. Because there is no simple mapping code between DNA base pairs and protein amino acids, the prediction of DNA–protein interactions is a challenging problem. Here, we present a novel computational approach for predicting DNA-binding protein residues and DNA–protein interaction modes without knowing its specific DNA target sequence. Given the structure of a DNA-binding protein, the method first generates an ensemble of complex structures obtained by rigid-body docking with a nonspecific canonical B-DNA. Representative models are subsequently selected through clustering and ranking by their DNA–protein interfacial energy. Analysis of these encounter complex models suggests that the recognition sites for specific DNA binding are usually favorable interaction sites for the nonspecific DNA probe and that nonspecific DNA–protein interaction modes exhibit some similarity to specific DNA–protein binding modes. Although the method requires as input the knowledge that the protein binds DNA, in benchmark tests, it achieves better performance in identifying DNA-binding sites than three previously established methods, which are based on sophisticated machine-learning techniques. We further apply our method to protein structures predicted through modeling and demonstrate that our method performs satisfactorily on protein models whose root-mean-square Ca deviation from native is up to 5 Å from their native structures. This study provides valuable structural insights into how a specific DNA-binding protein interacts with a nonspecific DNA sequence. The similarity between the specific DNA–protein interaction mode and nonspecific interaction modes may reflect an important sampling step in search of its specific DNA targets by a DNA-binding protein

An asymmetric junctional mechanoresponse coordinates mitotic rounding with epithelial integrity

Epithelia are continuously self-renewed, but how epithelial integrity is maintained during the morphological changes that cells undergo in mitosis is not well understood. Here, we show that as epithelial cells round up when they enter mitosis, they exert tensile forces on neighboring cells. We find that mitotic cell–cell junctions withstand these tensile forces through the mechanosensitive recruitment of the actin-binding protein vinculin to cadherin-based adhesions. Surprisingly, vinculin that is recruited to mitotic junctions originates selectively from the neighbors of mitotic cells, resulting in an asymmetric composition of cadherin junctions. Inhibition of junctional vinculin recruitment in neighbors of mitotic cells results in junctional breakage and weakened epithelial barrier. Conversely, the absence of vinculin from the cadherin complex in mitotic cells is necessary to successfully undergo mitotic rounding. Our data thus identify an asymmetric mechanoresponse at cadherin adhesions during mitosis, which is essential to maintain epithelial integrity while at the same time enable the shape changes of mitotic cells