How Much Information Can Be Extracted from Galaxy Clustering at the Field Level?

We present optimal Bayesian field-level cosmological constraints from nonlinear tracers of cosmic large-scale structure, specifically the amplitude σ_{8} of linear matter fluctuations inferred from rest-frame simulated dark matter halos in a comoving volume of 8  (h^{-1} Gpc)^{3}. Our constraint on σ_{8} is entirely due to nonlinear information, and obtained by explicitly sampling the initial conditions along with tracer bias and noise parameters via a Lagrangian effective field theory-based forward model, leftfield. The comparison with a simulation-based inference of the power spectrum and bispectrum-likewise using the leftfield forward model-shows that, when including precisely the same modes of the same data up to k_{max}=0.

Developmental changes in the perceived moral standing of robots.

Emerging evidence suggests that children may think of robots-and artificial intelligence, more generally-as having moral standing. In this paper, we trace the developmental trajectory of this belief. Over three developmental studies (combined N = 415) and one adult study (N = 156), we compared participants' judgments (Experiments 1-3) and donation choices (Experiment 4) towards a human boy, a humanoid robot, and control targets.

Chemical proteomics reveals the target landscape of 1,000 kinase inhibitors.

Medicinal chemistry has discovered thousands of potent protein and lipid kinase inhibitors. These may be developed into therapeutic drugs or chemical probes to study kinase biology. Because of polypharmacology, a large part of the human kinome currently lacks selective chemical probes.

The Puzzle of Evaluating Moral Cognition in Artificial Agents.

In developing artificial intelligence (AI), researchers often benchmark against human performance as a measure of progress. Is this kind of comparison possible for moral cognition? Given that human moral judgment often hinges on intangible properties like "intention" which may have no natural analog in artificial agents, it may prove difficult to design a "like-for-like" comparison between the moral behavior of artificial and human agents. What would a measure of moral behavior for both humans and AI look like? We unravel the complexity of this question by discussing examples within reinforcement learning and generative AI, and we examine how the puzzle of evaluating artificial agents' moral cognition remains open for further investigation within cognitive science.

Decrypting drug actions and protein modifications by dose- and time-resolved proteomics.

Although most cancer drugs modulate the activities of cellular pathways by changing posttranslational modifications (PTMs), little is known regarding the extent and the time- and dose-response characteristics of drug-regulated PTMs. In this work, we introduce a proteomic assay called decryptM that quantifies drug-PTM modulation for thousands of PTMs in cells to shed light on target engagement and drug mechanism of action. Examples range from detecting DNA damage by chemotherapeutics, to identifying drug-specific PTM signatures of kinase inhibitors, to demonstrating that rituximab kills CD20-positive B cells by overactivating B cell receptor signaling.