REFORMING PILLAR 2 –TOWARDS SIGNIFICANT AND SUSTAINABLE RURAL DEVELOPMENT?

With the ongoing “Health Check” and the decisions needed for after 2013, the Common Agricultural Policy is likely to see another major reform and an increase in compulsory modulation. By employing a regional model, this paper compares the long-term impact of spending along the Pillar 2 Axes in NUTS3 areas on selected indicators of sustainability in several peripheral areas across Europe. The four case study areas are: Pinzgau-Pongau (a tourism-dominated alpine area in Austria), the Wetterau (an urbanised industrial area in Germany), Gorenjska (a tourism and manufacturing dominated area in Slovenia) and Caithness-Sutherland (a remote area in Scotland). The results suggest although devolution in European rural development policy has taken over the last 10 years, there is further need to restore place-based stewardship of public goods and services as well as private investments across rural areas in the European Union. Increasing the importance of Axis 2 and Axis 3 measures (part of CAP Pillar 2) therefore seems an obvious choice for the future. Furthermore, it is clear that the effects of wider societal trends such as the decreasing importance of agriculture, commuting and migration, can be weakened or amplified by EU funding but can not be reversed or significantly changed.CAP, Pillar 2, rural development, Agricultural and Food Policy, R15, Q18, Q01,

Graph Q-Learning for Combinatorial Optimization

Graph-structured data is ubiquitous throughout natural and social sciences, and Graph Neural Networks (GNNs) have recently been shown to be effective at solving prediction and inference problems on graph data. In this paper, we propose and demonstrate that GNNs can be applied to solve Combinatorial Optimization (CO) problems. CO concerns optimizing a function over a discrete solution space that is often intractably large. To learn to solve CO problems, we formulate the optimization process as a sequential decision making problem, where the return is related to how close the candidate solution is to optimality. We use a GNN to learn a policy to iteratively build increasingly promising candidate solutions. We present preliminary evidence that GNNs trained through Q-Learning can solve CO problems with performance approaching state-of-the-art heuristic-based solvers, using only a fraction of the parameters and training time

Group equivariant neural posterior estimation

Simulation-based inference with conditional neural density estimators is a powerful approach to solving inverse problems in science. However, these methods typically treat the underlying forward model as a black box, with no way to exploit geometric properties such as equivariances. Equivariances are common in scientific models, however integrating them directly into expressive inference networks (such as normalizing flows) is not straightforward. We here describe an alternative method to incorporate equivariances under joint transformations of parameters and data. Our method -- called group equivariant neural posterior estimation (GNPE) -- is based on self-consistently standardizing the "pose" of the data while estimating the posterior over parameters. It is architecture-independent, and applies both to exact and approximate equivariances. As a real-world application, we use GNPE for amortized inference of astrophysical binary black hole systems from gravitational-wave observations. We show that GNPE achieves state-of-the-art accuracy while reducing inference times by three orders of magnitude

Water molecules mediate zinc mobility in the bacterial zinc diffusion channel ZIPB.

Regulated ion diffusion across biological membranes is vital for cell function. In a nanoscale ion channel, the active role of discrete water molecules in modulating hydrodynamic behaviors of individual ions is poorly understood because of the technical challenge of tracking water molecules through the channel. Here we report the results of a hydroxyl radical footprinting analysis of the zinc-selective channel ZIPB from the Gram-negative bacterium, Bordetella bronchiseptica Irradiating ZIPB by microsecond X-ray pulses activated water molecules to form covalent hydroxyl radical adducts at nearby residues, which were identified by bottom-up proteomics to detect residues that interact either with zinc or water in response to zinc binding. We found a series of residues exhibiting reciprocal changes in water accessibility attributed to alternating zinc and water binding. Mapping these residues to the previously reported crystal structure of ZIPB, we identified a water-reactive pathway that superimposed on a zinc translocation pathway consisting of two binuclear metal centers and an interim zinc-binding site. The cotranslocation of zinc and water suggested that pore-lining residues undergo a mode switch between zinc coordination and water binding to confer zinc mobility. The unprecedented details of water-mediated zinc transport identified here highlight an essential role of solvated waters in driving zinc coordination dynamics and transmembrane crossing

Synthesis and rearrangements of ortho-selenonium phenoxides

A new class of selenonium zwitterions is prepared from the ortho- substitution of phenols with diphenylselenium bis(trifluoroacetate) 1. The zwitterions undergo a novel thermal rearrangement to produce diaryl ethers.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/27012/1/0000579.pd

Measurement of the charged pion mass using X-ray spectroscopy of exotic atoms

The $5g-4f$ transitions in pionic nitrogen and muonic oxygen were measured simultaneously by using a gaseous nitrogen-oxygen mixture at 1.4\,bar. Due to the precise knowledge of the muon mass the muonic line provides the energy calibration for the pionic transition. A value of (139.57077\,$\pm$\,0.00018)\,MeV/c$^{2}$ ($\pm$\,1.3ppm) is derived for the mass of the negatively charged pion, which is 4.2ppm larger than the present world average

Chorioamnionitis: Association of Nonreassuring Fetal Heart-rate Patterns and Interval From Diagnosis to Delivery on Neonatal Outcome

Objective: The purpose of this study was to determine whether selected fetal heart-rate (FHR) patterns and the interval from diagnosis to delivery in pregnancies complicated by chorioamnionitis could predict neonatal outcome

nuance: Efficient Detection of Planets Transiting Active Stars

The detection of planetary transits in the light curves of active stars, featuring correlated noise in the form of stellar variability, remains a challenge. Depending on the noise characteristics, we show that the traditional technique that consists of detrending a light curve before searching for transits alters their signal-to-noise ratio and hinders our capability to discover exoplanets transiting rapidly rotating active stars. We present nuance, an algorithm to search for transits in light curves while simultaneously accounting for the presence of correlated noise, such as stellar variability and instrumental signals. We assess the performance of nuance on simulated light curves as well as on the Transiting Exoplanet Survey Satellite light curves of 438 rapidly rotating M dwarfs. For each data set, we compare our method to five commonly used detrending techniques followed by a search with the Box-Least-Squares algorithm. Overall, we demonstrate that nuance is the most performant method in 93% of cases, leading to both the highest number of true positives and the lowest number of false-positive detections. Although simultaneously searching for transits while modeling correlated noise is expected to be computationally expensive, we make our algorithm tractable and available as the JAX-powered Python package nuance, allowing its use on distributed environments and GPU devices. Finally, we explore the prospects offered by the nuance formalism and its use to advance our knowledge of planetary systems around active stars, both using space-based surveys and sparse ground-based observations