@article{21437,
  abstract     = {Altermagnets are a class of collinear magnets that exhibit non-relativistic spin splitting (NRSS) of electronic bands in the absence of net magnetization. Their potential to generate large spin polarization without spin-orbit coupling has created strong interest in probes that access the underlying order parameter directly. In this Perspective, we show that linear magneto-birefringence (LMB) provides a natural and broadly applicable route to detecting altermagnetic order. Building on the correspondence between the momentum-space structure of NRSS and the ferroic ordering of magnetic multipoles in real space, we demonstrate how $d$-wave and $g$-wave NRSS textures yield distinct LMB responses. We present a symmetry-based framework that identifies the optical geometries and field configurations required to isolate specific multipole components, enabling domain imaging and providing benchmarks for theoretical models of LMB.},
  author       = {Sunko, Veronika and Orenstein, J.},
  issn         = {2397-4648},
  journal      = {npj Quantum Materials},
  publisher    = {Springer Nature},
  title        = {{Linear magneto-birefringence as a probe of altermagnetism}},
  doi          = {10.1038/s41535-026-00901-8},
  year         = {2026},
}

@article{22101,
  abstract     = {Evolutionary biology examines how the genetic and phenotypic composition
of populations changes over time. An important goal is to determine the
fixation probability of a single advantageous mutant that arises in a homogeneous
population of N residents. Many real populations experience environmental
gradients that cause mutations to be beneficial in some spatial
regions but harmful in others. Here, we study the fixation probability of a
mutant placed on a simple one-dimensional spatial structure that experiences
such a gradient. The mutant’s fitness varies linearly from1 − s to 1 + s, whereas
the resident fitness is constant and equal to 1. The existing literature suggests
that such heterogeneity in the mutant’s fitness should lead to a decrease in its
fixation probability. However, in this work, we find that small, non-negligible
gradients (s < 1=√N) substantially increase the fixation probability,while larger
gradients (s > (log N)/√N) substantially decrease it.Moreover, we quantify the
strength of this phenomenon analytically and we precisely delimit the range of
the gradients for which it occurs. Our computer simulations closely match
those findings. Altogether, our results indicate that subjecting a simple
population structure to natural environmental conditions can produce strong
counterintuitive effects.},
  author       = {Svoboda, Jakub and Nemati, Hossein and Tkadlec, Josef and Kaveh, Kamran and Chatterjee, Krishnendu},
  issn         = {2041-1723},
  journal      = {Nature Communications},
  publisher    = {Springer Nature},
  title        = {{The effect of the fitness gradient on fixation probability}},
  doi          = {10.1038/s41467-026-71777-2},
  volume       = {17},
  year         = {2026},
}

@inproceedings{22103,
  abstract     = {Modern AI systems increasingly rely on opaque, highly complex models whose inner workings remain inaccessible even to experts. This opacity creates challenges for trust, accountability, and compliance with
emerging regulatory expectations such as the “right to an explanation”. While traditional explainability methods—feature attributions, counterfactuals, surrogate models—and interpretable model classes provide valuable insights for engineers, they often fall short of delivering the contextual, conversational explanations that
real users expect. Large Language Models (LLMs) offer a promising new avenue for explanation due to their
ability to engage interactively, adapt to user needs, and translate technical outputs into more accessible reasoning. However, their tendencies toward hallucination, conflict avoidance, and oversimplification introduce
serious risks when used as explanatory agents. This paper analyzes these opportunities and limitations, examines verification strategies for ensuring explanation fidelity, and situates LLM-generated explanations within
broader concerns about public trust. The paper concludes by outlining best practices and future research directions for building robust, verifiable, and human-aligned explanation systems.},
  author       = {Cano Cordoba, Filip},
  booktitle    = {Proceedings of the 18th International Conference on Agents and Artificial Intelligence},
  isbn         = {9789897587962},
  issn         = {2184-433X},
  keywords     = {Explainable AI, Large Language Models, Trust in AI},
  location     = {Marbella, Spain},
  pages        = {4689--4696},
  publisher    = {Science and Technology Publications},
  title        = {{Explaining decisions one conversation at a time: Opportunities and risks of LLMs as explainability assistants}},
  doi          = {10.5220/0014483200004052},
  volume       = {5},
  year         = {2026},
}

@article{22105,
  abstract     = {Protein conformational energy landscapes are shaped not only by intramolecular interactions but also by their environment. In protein crystals and protein–protein complexes, intermolecular contacts alter this energy landscape, but the exact nature of this alteration is difficult to decipher. Understanding how the crystal lattice affects protein dynamics is crucial for crystallography-based studies of motion, yet its influence on collective motions remains unclear. Aromatic ring flips in the hydrophobic core represent sensitive probes of such dynamics. Here, we compare the kinetics of aromatic ring flips in the protein GB1 in crystals, in complex with its binding partner IgG, and in solution, combining advanced isotope labelling with quantitative NMR methods. We show that rings in the core flip nearly a thousand times less frequently in crystals than in solution. Enhanced-sampling molecular dynamics simulations, based on a crystal structure of a GB1 variant reported in this work, reproduce these elevated barriers and reveal how the crystal restrains motions.},
  author       = {Becker, Lea Marie and Fu, Haohao and Tatman, Benjamin and Dreydoppel, Matthias and Kapitonova, Anna and Balazs, Daniel and Weininger, Ulrich and Engilberge, Sylvain and Chipot, Christophe and Schanda, Paul},
  issn         = {17554349},
  journal      = {Nature Chemistry},
  publisher    = {Springer Nature},
  title        = {{Aromatic ring flips reveal reshaping of protein dynamics in crystals and complexes}},
  doi          = {10.1038/s41557-026-02155-0},
  year         = {2026},
}

@misc{21145,
  abstract     = {Protein conformational energy landscapes are shaped not only by intramolecular interactions but also by their environment. In protein crystals and protein-protein complexes, intermolecular contacts alter this energy landscape, but the exact nature of this alteration is difficult to decipher. Understanding how the crystal lattice affects protein dynamics is crucial for crystallography-based studies of motion, yet its influence on collective motions remains unclear. Aromatic ring flips in the hydrophobic core represent sensitive probes of such dynamics. Here, we compare the kinetics of aromatic ring flips in the protein GB1 in crystals, in complex with its binding partner IgG, and in solution, combining advanced isotope labeling with quantitative NMR methods. We show that rings in the core flip nearly a thousand times less frequently in crystals than in solution. Enhanced-sampling molecular dynamics simulations, based on a new crystal structure, reproduce these elevated barriers and reveal how the crystal restrains motions. },
  author       = {Becker, Lea Marie and Schanda, Paul and Chipot, Christophe},
  publisher    = {Institute of Science and Technology Austria},
  title        = {{Additional Data for "Aromatic Ring Flips Reveal Reshaping of Protein Dynamics in Crystals and Complexes"}},
  doi          = {10.15479/AT-ISTA-21145},
  year         = {2026},
}