A behavioral macroeconomic model with endogenous boom-bust cycles and leverage dynamcis

We merge a financial market model with leverage-constrained, heterogeneous agents with a reduced-form version of the New-Keynesian standard model. Agents in both submodels are assumed to be boundedly rational. The fi nancial market model produces endogenously arising boom-bust cycles. It is also capable to generate highly non-linear deleveraging processes, fi re sales and ultimately a default scenario. Asset price booms are triggered via self-fulfilling prophecies. Asset price busts are induced by agents' choice of an increasingly fragile balance sheet structure during good times. Their vulnerability is inevitably revealed by small, randomly occurring shocks. Our transmission channel of financial market activity to the real sector embraces a recent strand of literature shedding light on the link between the active balance sheet management of financial market participants, the induced procyclical fluctuations of desired risk compensations and their final impact on the real economy. We show that a systematic central bank reaction on financial market developments dampens macroeconomic volatility considerably. Furthermore, restricting leverage in a countercyclical fashion limits the magnitude of financial cycles and hence their impact on the real economy. --behavioral economics,New-Keynesian macroeconomics,monetary policy,agent-based financial market model,leverage,macroprudential regulation,financial stability,asset price bubbles,systemic risk

Origins of Extragalactic Cosmic Ray Nuclei by Contracting Alignment Patterns induced in the Galactic Magnetic Field

We present a novel approach to search for origins of ultra-high energy cosmic rays. These particles are likely nuclei that initiate extensive air showers in the Earth's atmosphere. In large-area observatories, the particle arrival directions are measured together with their energies and the atmospheric depth at which their showers maximize. The depths provide rough measures of the nuclear charges. In a simultaneous fit to all observed cosmic rays we use the galactic magnetic field as a mass spectrometer and adapt the nuclear charges such that their extragalactic arrival directions are concentrated in as few directions as possible. Using different simulated examples we show that, with the measurements on Earth, reconstruction of extragalactic source directions is possible. In particular, we show in an astrophysical scenario that source directions can be reconstructed even within a substantial isotropic background.Comment: 14 pages, 15 figure

Sparsity Invariant CNNs

In this paper, we consider convolutional neural networks operating on sparse inputs with an application to depth upsampling from sparse laser scan data. First, we show that traditional convolutional networks perform poorly when applied to sparse data even when the location of missing data is provided to the network. To overcome this problem, we propose a simple yet effective sparse convolution layer which explicitly considers the location of missing data during the convolution operation. We demonstrate the benefits of the proposed network architecture in synthetic and real experiments with respect to various baseline approaches. Compared to dense baselines, the proposed sparse convolution network generalizes well to novel datasets and is invariant to the level of sparsity in the data. For our evaluation, we derive a novel dataset from the KITTI benchmark, comprising 93k depth annotated RGB images. Our dataset allows for training and evaluating depth upsampling and depth prediction techniques in challenging real-world settings and will be made available upon publication

Directed invasion of cancer cell spheroids inside 3D collagen matrices oriented by microfluidic flow in experiment and simulation

Invasion is strongly influenced by the mechanical properties of the extracellular matrix. Here, we use microfluidics to align fibers of a collagen matrix and study the influence of fiber orientation on invasion from a cancer cell spheroid. The microfluidic setup allows for highly oriented collagen fibers of tangential and radial orientation with respect to the spheroid, which can be described by finite element simulations. In invasion experiments, we observe a strong bias of invasion towards radial as compared to tangential fiber orientation. Simulations of the invasive behavior with a Brownian diffusion model suggest complete blockage of migration perpendicularly to fibers allowing for migration exclusively along fibers. This slows invasion toward areas with tangentially oriented fibers down, but does not prevent it

Colorful Collar-Covers and Bells Reduce Wildlife Predation by Domestic Cats in a Continental European Setting

In many areas, domestic cats are the most abundant predators of small vertebrates. Due to the potential impact on prey populations by cats, there are calls to investigate the effectiveness of visual and acoustic cues as measures to reduce the cat’s hunting efficiency. In this study, we complement previous studies on the efficacy of Birdsbesafe collar-covers (BBScc) in a so far not investigated Continental European setting and explore the effectiveness in combination with a bell. We also evaluate the tolerability of these devices by the cat and the acceptance by their owners. With a randomized and comparative citizen science-based approach we collected data from 26 households with 31 study cats, which were wearing either a BBScc or both a BBScc and a bell. The BBScc reduced the number of birds brought home by 37% (probability of reduction of 88%). The number of mammals brought home was reduced by 54–62%, but only with the additional bell (probability of reduction of >99%). About one fourth of the birds that could be dissected were found to have collided with a hard object prior to having been brought home by the cats. Our results are in line with previous findings from Australia, the United States, and the United Kingdom and highlight the great potential of visual and acoustic cues in reducing hunting success in domestic cats also in Continental Europe. On the other hand, our result show that the number of prey brought home by cats overestimates their hunting bag, if scavenging is not considered. The majority of cat owners reported that their cats habituated quickly to the BBScc. However, frequent scratching in some cats indicates that some individuals may not habituate. Most participating cat owners had a positive attitude toward the BBScc and said that they were willing to use it after the study. However, cat owners reported that their social environment (e.g., neighbors, family, friends) was relatively skeptical, which indicates a need for communication. To conclude, commercially available devices with visual and acoustic stimuli are straightforward and effective ways to mitigate the potentially harmful effect of domestic cats on wildlife

Deep learning in the wild

Invited paperDeep learning with neural networks is applied by an increasing number of people outside of classic research environments, due to the vast success of the methodology on a wide range of machine perception tasks. While this interest is fueled by beautiful success stories, practical work in deep learning on novel tasks without existing baselines remains challenging. This paper explores the specific challenges arising in the realm of real world tasks, based on case studies from research & development in conjunction with industry, and extracts lessons learned from them. It thus fills a gap between the publication of latest algorithmic and methodical developments, and the usually omitted nitty-gritty of how to make them work. Specifically, we give insight into deep learning projects on face matching, print media monitoring, industrial quality control, music scanning, strategy game playing, and automated machine learning, thereby providing best practices for deep learning in practice

Democratic research: Setting up a research commons for a qualitative, comparative, longitudinal interview study during the COVID-19 pandemic

The sudden and dramatic advent of the COVID-19 pandemic led to urgent demands for timely, relevant, yet rigorous research. This paper discusses the origin, design, and execution of the SolPan research commons, a large-scale, international, comparative, qualitative research project that sought to respond to the need for knowledge among researchers and policymakers in times of crisis. The form of organization as a research commons is characterized by an underlying solidaristic attitude of its members and its intrinsic organizational features in which research data and knowledge in the study is shared and jointly owned. As such, the project is peer-governed, rooted in (idealist) social values of academia, and aims at providing tools and benefits for its members. In this paper, we discuss challenges and solutions for qualitative studies that seek to operate as research commons