Consistent Probabilistic Social Choice

Two fundamental axioms in social choice theory are consistency with respect to a variable electorate and consistency with respect to components of similar alternatives. In the context of traditional non-probabilistic social choice, these axioms are incompatible with each other. We show that in the context of probabilistic social choice, these axioms uniquely characterize a function proposed by Fishburn (Rev. Econ. Stud., 51(4), 683--692, 1984). Fishburn's function returns so-called maximal lotteries, i.e., lotteries that correspond to optimal mixed strategies of the underlying plurality game. Maximal lotteries are guaranteed to exist due to von Neumann's Minimax Theorem, are almost always unique, and can be efficiently computed using linear programming

Turn-key module for neutron scattering with sub-micro-eV resolution

We report the development of a compact turn-key module that boosts the resolution in quasi-elastic neutron scattering by several orders of magnitude down to the low sub-micro-eV range. It is based on a pair of neutron resonance spin flippers that generate a well defined temporal intensity modulation, also known as MIEZE (Modulation of IntEnsity by Zero Effort). The module may be used under versatile conditions, in particular in applied magnetic fields and for depolarising and incoherently scattering samples. We demonstrate the power of MIEZE in studies of the helimagnetic order in MnSi under applied magnetic fields

Advanced Testing Chain Supporting the Validation of Smart Grid Systems and Technologies

New testing and development procedures and methods are needed to address topics like power system stability, operation and control in the context of grid integration of rapidly developing smart grid technologies. In this context, individual testing of units and components has to be reconsidered and appropriate testing procedures and methods need to be described and implemented. This paper addresses these needs by proposing a holistic and enhanced testing methodology that integrates simulation/software- and hardware-based testing infrastructure. This approach presents the advantage of a testing environment, which is very close to f i eld testing, includes the grid dynamic behavior feedback and is risks-free for the power system, for the equipment under test and for the personnel executing the tests. Furthermore, this paper gives an overview of successful implementation of the proposed testing approach within different testing infrastructure available at the premises of different research institutes in Europe.Comment: 2018 IEEE Workshop on Complexity in Engineering (COMPENG

Fukushima-derived radionuclides in sediments of the Japanese Pacific Ocean coast and various Japanese water samples (seawater, tap water, and coolant water of Fukushima Daiichi reactor unit 5)

We investigated Ocean sediments and seawater from inside the Fukushima exclusion zone and found radiocesium (134Cs and 137Cs) up to 800 Bq kg-1 as well as 90Sr up to 5.6 Bq kg-1. This is one of the first reports on radiostrontium in sea sediments from the Fukushima exclusion zone. Seawater exhibited contamination levels up to 5.3 Bq kg-1 radiocesium. Tap water from Tokyo from weeks after the accident exhibited detectable but harmless activities of radiocesium (well below the regulatory limit). Analysis of the Unit 5 reactor coolant (finding only 3H and even low 129I) leads to the conclusion that the purification techniques for reactor coolant employed at Fukushima Daiichi are very effective.JSPS KAKENHI/25870158CDC NIOSH Mountain and Plains Education and Research Center/T42OH009229-07NRC/NRC-HQ-12-G-38-004

Asynchronous Integration of Real-Time Simulators for HIL-based Validation of Smart Grids

As the landscape of devices that interact with the electrical grid expands, also the complexity of the scenarios that arise from these interactions increases. Validation methods and tools are typically domain specific and are designed to approach mainly component level testing. For this kind of applications, software and hardware-in-the-loop based simulations as well as lab experiments are all tools that allow testing with different degrees of accuracy at various stages in the development life-cycle. However, things are vastly different when analysing the tools and the methodology available for performing system-level validation. Until now there are no available well-defined approaches for testing complex use cases involving components from different domains. Smart grid applications would typically include a relatively large number of physical devices, software components, as well as communication technology, all working hand in hand. This paper explores the possibilities that are opened in terms of testing by the integration of a real-time simulator into co-simulation environments. Three practical implementations of such systems together with performance metrics are discussed. Two control-related examples are selected in order to show the capabilities of the proposed approach.Comment: IECON 2019 - 45th Annual Conference of the IEEE Industrial Electronics Societ

Log-Gaussian processes for AI-assisted TAS experiments

To understand the origins of materials properties, neutron scattering experiments at three-axes spectrometers (TAS) investigate magnetic and lattice excitations in a sample by measuring intensity distributions in its momentum (Q) and energy (E) space. The high demand and limited availability of beam time for TAS experiments however raise the natural question whether we can improve their efficiency or make better use of the experimenter's time. In fact, using TAS, there are a number of scientific questions that require searching for signals of interest in a particular region of Q-E space, but when done manually, it is time consuming and inefficient since the measurement points may be placed in uninformative regions such as the background. Active learning is a promising general machine learning approach that allows to iteratively detect informative regions of signal autonomously, i.e., without human interference, thus avoiding unnecessary measurements and speeding up the experiment. In addition, the autonomous mode allows experimenters to focus on other relevant tasks in the meantime. The approach that we describe in this article exploits log-Gaussian processes which, due to the log transformation, have the largest approximation uncertainties in regions of signal. Maximizing uncertainty as an acquisition function hence directly yields locations for informative measurements. We demonstrate the benefits of our approach on outcomes of a real neutron experiment at the thermal TAS EIGER (PSI) as well as on results of a benchmark in a synthetic setting including numerous different excitations.Comment: Main: 22 pages, 5 figures | Extended Data: 8 figures | Supplementary Information: 5 pages, 2 figure

Possibilities and Limitations of Spatially Explicit Site Index Modelling for Spruce Based on National Forest Inventory Data and Digital Maps of Soil and Climate in Bavaria (SE Germany)

Combining national forest inventory (NFI) data with digital site maps of high resolution enables spatially explicit predictions of site productivity. The aim of this study is to explore the possibilities and limitations of this database to analyze the environmental dependency of height-growth of Norway spruce and to predict site index (SI) on a scale that is relevant for local forest management. The study region is the German federal state of Bavaria. The exploratory methods comprise significance tests and hypervolume-analysis. SI is modeled with a Generalized Additive Model (GAM). In a second step the residuals are modeled using Boosted Regression Trees (BRT). The interaction between temperature regime and water supply strongly determined height growth. At sites with very similar temperature regime and water supply, greater heights were reached if the depth gradient of base saturation was favorable. Statistical model criteria (Double Penalty Selection, AIC) preferred composite variables for water supply and the supply of basic cations. The ability to predict SI on a local scale was limited due to the difficulty to integrate soil variables into the model

Optical floating zone growth of high-quality Cu2MnAl single crystals

We report the growth of large single-crystals of Cu2MnAl, a ferromagnetic Heusler compound suitable for polarizing neutron monochromators, by means of optical floating zone under ultra-high vacuum compatible conditions. Unlike Bridgman or Czochralsky grown Cu2MnAl, our floating zone grown single-crystals show highly reproducible magnetic properties and an excellent crystal quality with a narrow and homogeneous mosaic spread as examined by neutron diffraction. An investigation of the polarizing properties in neutron scattering suggests a high polarization efficiency, limited by the relatively small sample dimensions studied. Our study identifies optical floating zone under ultra-high vacuum compatible conditions as a highly reproducible method to grow high-quality single-crystals of Cu2MnAl.Comment: 19 pages, 11 figure

Human threat circuits: Threats of pain, aggressive conspecific, and predator elicit distinct BOLD activations in the amygdala and hypothalamus

IntroductionThreat processing, enabled by threat circuits, is supported by a remarkably conserved neural architecture across mammals. Threatening stimuli relevant for most species include the threat of being attacked by a predator or an aggressive conspecific and the threat of pain. Extensive studies in rodents have associated the threats of pain, predator attack and aggressive conspecific attack with distinct neural circuits in subregions of the amygdala, the hypothalamus and the periaqueductal gray. Bearing in mind the considerable conservation of both the anatomy of these regions and defensive behaviors across mammalian species, we hypothesized that distinct brain activity corresponding to the threats of pain, predator attack and aggressive conspecific attack would also exist in human subcortical brain regions.MethodsForty healthy female subjects underwent fMRI scanning during aversive classical conditioning. In close analogy to rodent studies, threat stimuli consisted of painful electric shocks, a short video clip of an attacking bear and a short video clip of an attacking man. Threat processing was conceptualized as the expectation of the aversive stimulus during the presentation of the conditioned stimulus.ResultsOur results demonstrate differential brain activations in the left and right amygdala as well as in the left hypothalamus for the threats of pain, predator attack and aggressive conspecific attack, for the first time showing distinct threat-related brain activity within the human subcortical brain. Specifically, the threat of pain showed an increase of activity in the left and right amygdala and the left hypothalamus compared to the threat of conspecific attack (pain > conspecific), and increased activity in the left amygdala compared to the threat of predator attack (pain > predator). Threat of conspecific attack revealed heightened activity in the right amygdala, both in comparison to threat of pain (conspecific > pain) and threat of predator attack (conspecific > predator). Finally, for the condition threat of predator attack we found increased activity in the bilateral amygdala and the hypothalamus when compared to threat of conspecific attack (predator > conspecific). No significant clusters were found for the contrast predator attack > pain.ConclusionResults suggest that threat type-specific circuits identified in rodents might be conserved in the human brain

The B-cell inhibitory receptor CD22 is a major factor in host resistance to Streptococcus pneumoniae infection

Streptococcus pneumoniae is a major human pathogen, causing pneumonia and sepsis. Genetic components strongly influence host responses to pneumococcal infections, but the responsible loci are unknown. We have previously identified a locus on mouse chromosome 7 from a susceptible mouse strain, CBA/Ca, to be crucial for pneumococcal infection. Here we identify a responsible gene, Cd22, which carries a point mutation in the CBA/Ca strain, leading to loss of CD22 on B cells. CBA/Ca mice and gene-targeted CD22-deficient mice on a C57BL/6 background are both similarly susceptible to pneumococcal infection, as shown by bacterial replication in the lungs, high bacteremia and early death. After bacterial infections, CD22-deficient mice had strongly reduced B cell populations in the lung, including GM-CSF producing, IgM secreting innate response activator B cells, which are crucial for protection. This study provides striking evidence that CD22 is crucial for protection during invasive pneumococcal disease.info:eu-repo/semantics/publishedVersio