NRW 2025: Vom Hort der alten Industrien zum Magnet der Moderne?

Die Arbeitsgruppe Beschäftigung der von NRW-Ministerpräsident Jürgen Rüttgers eingesetzten "Zukunftskommission" hat umfassende Empfehlungen für die künftige Wirtschafts- und Arbeitsmarktpolitik in Nordrhein-Westfalen vorgelegt. Das Papier der von IZA-Direktor Klaus F. Zimmermann geleiteten Expertengruppe schlägt unter anderem eine Standortoffensive zugunsten von Bildungsreformen und mehr Weiterbildung vor. Zudem wird empfohlen, die Position von NRW als führender Hochschul- und Energieinnovationsstandort systematisch auszubauen. Darüber hinaus misst die Arbeitsgruppe Initiativen für mehr strukturelle Familienfreundlichkeit große strategische Bedeutung zu. Unter dem Eindruck der aktuellen Wirtschaftskrise gewinnen die Vorschläge der Arbeitsgruppe besonderes Gewicht.Standortentwicklung, Bildung, Arbeitsmarktpolitik, Nordrhein-Westfalen

Exploiting the Temporal Logic Hierarchy and the Non-Confluence Property for Efficient LTL Synthesis

The classic approaches to synthesize a reactive system from a linear temporal logic (LTL) specification first translate the given LTL formula to an equivalent omega-automaton and then compute a winning strategy for the corresponding omega-regular game. To this end, the obtained omega-automata have to be (pseudo)-determinized where typically a variant of Safra's determinization procedure is used. In this paper, we show that this determinization step can be significantly improved for tool implementations by replacing Safra's determinization by simpler determinization procedures. In particular, we exploit (1) the temporal logic hierarchy that corresponds to the well-known automata hierarchy consisting of safety, liveness, Buechi, and co-Buechi automata as well as their boolean closures, (2) the non-confluence property of omega-automata that result from certain translations of LTL formulas, and (3) symbolic implementations of determinization procedures for the Rabin-Scott and the Miyano-Hayashi breakpoint construction. In particular, we present convincing experimental results that demonstrate the practical applicability of our new synthesis procedure

Kessler : A machine learning library for spacecraft collision avoidance

As megaconstellations are launched and the space sector grows, space debris pollution is posing an increasing threat to operational spacecraft. Low Earth orbit is a junkyard of dead satellites, rocket bodies, shrapnels, and other debris that travel at very high speed in an uncontrolled manner. Collisions at orbital speeds can generate fragments and potentially trigger a cascade of more collisions endangering the whole population, a scenario known since the late 1970s as the Kessler syndrome. In this work we present Kessler: an open-source Python package for machine learning (ML) applied to collision avoidance. Kessler provides functionalities to import and export conjunction data messages (CDMs) in their standard format and predict the evolution of conjunction events based on explainable ML models. In Kessler we provide Bayesian recurrent neural networks that can be trained with existing collections of CDM data and then deployed in order to predict the contents of future CDMs in a given conjunction event, conditioned on all CDMs received up to now, with associated uncertainty estimates about all predictions. Furthermore Kessler includes a novel generative model of conjunction events and CDM sequences implemented using probabilistic programming, simulating the CDM generation process of the Combined Space Operations Center (CSpOC). The model allows Bayesian inference and also the generation of large datasets of realistic synthetic CDMs that we believe will be pivotal to enable further ML approaches given the sensitive nature and public unavailability of real CDM data

Virtual faces as a tool to study emotion recognition deficits in schizophrenia

Studies investigating emotion recognition in patients with schizophrenia predominantly presented photographs of facial expressions. Better control and higher flexibility of emotion displays could be afforded by virtual reality (VR). VR allows the manipulation of facial expression and can simulate social interactions in a controlled and yet more naturalistic environment. However, to our knowledge, there is no study that systematically investigated whether patients with schizophrenia show the same emotion recognition deficits when emotions are expressed by virtual as compared to natural faces. Twenty schizophrenia patients and 20 controls rated pictures of natural and virtual faces with respect to the basic emotion expressed (happiness, sadness, anger, fear, disgust, and neutrality). Consistent with our hypothesis, the results revealed that emotion recognition impairments also emerged for emotions expressed by virtual characters. As virtual in contrast to natural expressions only contain major emotional features, schizophrenia patients already seem to be impaired in the recognition of basic emotional features. This finding has practical implication as it supports the use of virtual emotional expressions for psychiatric research: the ease of changing facial features, animating avatar faces, and creating therapeutic simulations makes validated artificial expressions perfectly suited to study and treat emotion recognition deficits in schizophrenia

Towards automated satellite conjunction management with Bayesian deep learning

After decades of space travel, low Earth orbit is a junkyard of discarded rocket bodies, dead satellites, and millions of pieces of debris from collisions and explosions.Objects in high enough altitudes do not re-enter and burn up in the atmosphere, but stay in orbit around Earth for a long time. With a speed of 28,000 km/h, collisions in these orbits can generate fragments and potentially trigger a cascade of more collisions known as the Kessler syndrome. This could pose a planetary challenge, because the phenomenon could escalate to the point of hindering future space operations and damaging satellite infrastructure critical for space and Earth science applications. As commercial entities place mega-constellations of satellites in orbit, the burden on operators conducting collision avoidance manoeuvres will increase.For this reason, development of automated tools that predict potential collision events (conjunctions) is critical. We introduce a Bayesian deep learning approach to this problem, and develop recurrent neural network architectures (LSTMs) that work with time series of conjunction data messages (CDMs), a standard data format used by the space community. We show that our method can be used to model all CDM features simultaneously, including the time of arrival of future CDMs, providing predictions of conjunction event evolution with associated uncertainties

Haloes gone MAD: The Halo-Finder Comparison Project

[abridged] We present a detailed comparison of fundamental dark matter halo properties retrieved by a substantial number of different halo finders. These codes span a wide range of techniques including friends-of-friends (FOF), spherical-overdensity (SO) and phase-space based algorithms. We further introduce a robust (and publicly available) suite of test scenarios that allows halo finder developers to compare the performance of their codes against those presented here. This set includes mock haloes containing various levels and distributions of substructure at a range of resolutions as well as a cosmological simulation of the large-scale structure of the universe. All the halo finding codes tested could successfully recover the spatial location of our mock haloes. They further returned lists of particles (potentially) belonging to the object that led to coinciding values for the maximum of the circular velocity profile and the radius where it is reached. All the finders based in configuration space struggled to recover substructure that was located close to the centre of the host halo and the radial dependence of the mass recovered varies from finder to finder. Those finders based in phase space could resolve central substructure although they found difficulties in accurately recovering its properties. Via a resolution study we found that most of the finders could not reliably recover substructure containing fewer than 30-40 particles. However, also here the phase space finders excelled by resolving substructure down to 10-20 particles. By comparing the halo finders using a high resolution cosmological volume we found that they agree remarkably well on fundamental properties of astrophysical significance (e.g. mass, position, velocity, and peak of the rotation curve).Comment: 27 interesting pages, 20 beautiful figures, and 4 informative tables accepted for publication in MNRAS. The high-resolution version of the paper as well as all the test cases and analysis can be found at the web site http://popia.ft.uam.es/HaloesGoingMA

DEGUM, ÖGUM, SGUM and FMF Germany Recommendations for the Implementation of First-Trimester Screening, Detailed Ultrasound, Cell-Free DNA Screening and Diagnostic Procedures

First-trimester screening between 11 + 0 and 13 + 6 weeks with qualified prenatal counseling, detailed ultrasound, biochemical markers and maternal factors has become the basis for decisions about further examinations. It detects numerous structural and genetic anomalies. The inclusion of uterine artery Doppler and PlGF screens for preeclampsia and fetal growth restriction. Low-dose aspirin significantly reduces the prevalence of severe preterm eclampsia. Cut-off values define groups of high, intermediate and low probability. Prenatal counseling uses detection and false-positive rates to work out the individual need profile and the corresponding decision: no further diagnosis/screening - cell-free DNA screening - diagnostic procedure and genetic analysis. In pre-test counseling it must be recognized that the prevalence of trisomy 21, 18 or 13 is low in younger women, as in submicroscopic anomalies in every maternal age. Even with high specificities, the positive predictive values of screening tests for rare anomalies are low. In the general population trisomies and sex chromosome aneuploidies account for approximately 70 % of anomalies recognizable by conventional genetic analysis. Screen positive results of cfDNA tests have to be proven by diagnostic procedure and genetic diagnosis. In cases of inconclusive results a higher rate of genetic anomalies is detected. Procedure-related fetal loss rates after chorionic biopsy and amniocentesis performed by experts are lower than 1 to 2 in 1000. Counseling should include the possible detection of submicroscopic anomalies by comparative genomic hybridization (array-CGH). At present, existing studies about screening for microdeletions and duplications do not provide reliable data to calculate sensitivities, false-positive rates and positive predictive values