Max Planck Institute for Medical Research

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    561975 research outputs found

    Wenn Politik an Glaubwürdigkeit verliert

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    Parlamentarischer Abend des Centre Marc Bloch: Die Politiker François Hollande und Armin Laschet diskutieren mit den Wissenschaftler*innen Isabelle Guinaudeau und Steffen Mau, wie Politik verlorenes Vertrauen zurückgewinnen kann

    Rethinking Catalysis: Interpretable AI and Description of Real-World Conditions via Materials Genes

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    Descriptors link basic physicochemical parameters that characterize the materials and the environment to the catalytic performance. Traditionally, descriptors are rooted in mechanistic understanding of elementary surface reactions gained from surface science and atomistic simulations on well-defined surfaces and vacuum. However, real-world catalysis operates under elevated pressures and temperatures, where an intricate interplay of multiple physical processes, including significant materials' restructuring and transport phenomena, governs performance. To bridge this gap, we introduced an interpretable artificial intelligence (AI) approach that identifies key physicochemical parameters correlated with the measured catalytic performance. Analogous to genes in biology and medicine, these “materials genes” provide a statistical description of catalysis without requiring the explicit description of the underlying physical processes. Here, we combine the sure-independence-screening-and-sparsifying-operator (SISSO) symbolic-regression AI approach with a sensitivity analysis based on partial derivatives to determine the most influential genes needed to describe the selectivity of supported palladium-based metal alloy nanoparticles in the hydrogenation of concentrated acetylene streams. The identified genes include the calculated average d-band center and the measured average particle diameter, indicating a crucial role of adsorption and structure sensitivity on the formation of ethylene

    The choice-wide behavioral association study: data-driven identification of interpretable behavioral components

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    Behavior contains rich structure across many timescales, but there is a dearth of methods to identify relevant components, especially over the longer periods required for learning and decision-making. Inspired by the goals and techniques of genome-wide association studies, we present a data-driven method—the choice-wide behavioral association study: CBAS—that systematically identifies such behavioral features. CBAS uses powerful, resampling-based, methods of multiple comparisons correction to identify sequences of actions or choices that either differ significantly between groups or significantly correlate with a covariate of interest. We apply CBAS to different tasks and species (flies, rats, and humans) and find, in all instances, that it provides interpretable information about each behavioral task

    Central motives on parahoric flag varieties

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    We construct a refinement of Gaitsgory’s central functor for integral motivic sheaves, and show it preserves stratified Tate motives. Towards this end, we develop a reformulation of unipotent motivic nearby cycles, which also works over higher-dimensional bases. We moreover introduce Wakimoto motives and use them to show that our motivic central functor is t-exact. A decategorification of these functors yields a new approach to generic Hecke algebras for general parahorics

    Theory-agnostic searches for non-gravitational modes in black hole ringdown

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    In any extension of General Relativity (GR), extra fundamental degrees offreedom couple to gravity. Besides deforming GR forecasts in a theory-dependentway, this coupling generically introduces extra modes in the gravitational-wavesignal. We propose a novel theory-agnostic test of gravity to search for thesenongravitational modes in black hole merger ringdown signals. To leading orderin the GR deviations, their frequencies and damping times match those of a testscalar or vector field in a Kerr background, with only amplitudes and phases asfree parameters. This test will be highly valuable for future detectors, whichwill achieve signal-to-noise ratios higher than 100 (and as high as 1000 forspace-based detectors such as LISA). Such sensitivity will allow measurement ofthese modes with amplitude ratios as low as 0.05 for ground-based detectors(and as low as 0.008 for LISA), relative to the fundamental mode, enablingstringent agnostic constraints or detection of scalar/vector modes. By applyingthis test to GW150914, GW190521, and GW200129, we find that the currentevidence for an extra mode is comparable to that for the first gravitationalovertone, but its inclusion modifies the inferred remnant spin.<br

    Spatial and social cognition jointly determine multimodal demonstrative reference: Experimental evidence from Turkish and Spanish

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    All languages in the world have demonstrative terms such as ‘this’ and ‘that’ in English, which have traditionally been treated as spatial words. Here we aim to provide experimental evidence that demonstrative choice is jointly determined by spatial considerations (e.g., whether the referent is near or far) and socio-cognitive factors (e.g.,the listener’s attention focus). We also test whether demonstrative choice varies depending on the speaker’s use of pointing, to provide evidence for a multimodal account of demonstrative systems. We focus on the Turkish system and compare it with the Spanish one to better understand the cross-linguistic variability of 3-term demonstrative systems. Corpus studies have suggested that the Turkish proximal ‘bu’ and distal ‘o’ mark a spatial contrast between near and far space, whereas the medial ‘s¸u’ is used to direct the listener’s attention to a new referent. Supporting this analysis, an online experiment using a picture-based demonstrative-choice task revealed that the medial form ‘s¸u’ was preferred when the listener was looking at the wrong object. The results of a second experiment using video stimuli further showed that the medial ‘s¸u’ was preferred when the speaker pointed to the referent to direct the listener’s attention, whereas the proximal demonstrative was used in near space and the distal in far space, mostly in joint attention and without pointing. The results of a third experiment in Spanish showed radically different patterns of demonstrative-pointing use. The medial ‘ese’ was preferred in joint attention, whereas the proximal ‘este’ and distal ‘aquel’ were selected to direct the listener’s attention towards the intended referent but without an effect of pointing. Our results confirm that demonstrative choice within a given system is determined by both spatial and socio-cognitive factors, interacting with pointing patterns and varying across languages. Leveraging recent experimental work in several languages, we interpret these findings as further evidence for the weighted parameters framework (e.g., referent position and listener attention), which explains demonstrative choice beyond previous categorical analyses

    The structure of Egalitarian in complex with the K10 mRNA localization signal reveals a modular binding surface required for function

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    Asymmetric localization of mRNAs is a prevalent mechanism for spatial control of protein function and typically involves active transport by cytoskeletal motors. The mechanisms of recognition of localizing mRNAs by motor complexes are poorly understood. Egalitarian is an adaptor protein that binds localization signals in specific RNAs in Drosophila and recruits them to the dynein-dynactin complex for microtubule-based transport. We determined the crystal structure of Egalitarian in complex with the localization signal of the K10 mRNA. Three structural units of Egalitarian, a 3’-5’exonuclease domain, a linker and a C-terminal domain form shape-specific, base-directed and backbone interactions with the RNA. Based on the structure we identified conserved residues recognizing RNA in vitro. Genome-edited flies with mutations in these residues have deficits in Egalitarian function that are congruent with changes in in vitro RNA binding affinities. Our work demonstrates how a minimal RNA localization signal is recognized by an RNA localization factor

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