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Binarity at LOw Metallicity (BLOeM): The multiplicity properties and evolution of BAF-type supergiants
No full textGiven the uncertain evolutionary status of blue supergiant stars, their multiplicity properties hold vital clues to better understand their origin and evolution. As part of The Binarity at LOw Metallicity (BLOeM) campaign in the Small Magellanic Cloud, we present a multi-epoch spectroscopic survey of 128 supergiant stars of spectral type B5–F5, which roughly correspond to initial masses in the 6–30 M⊙ range. The observed binary fraction for the B5–9 supergiants is 25 ± 6% (10 ± 4%) and 5 ± 2% (0%) for the A–F stars, which were found using a radial-velocity (RV) variability threshold of 5 km s−1 (10 km s−1) as a criterion for binarity. Accounting for observational biases, we find an intrinsic multiplicity fraction of less than 18% for the B5–9 stars and 8−7+9% for the AF stars, for the orbital periods up to 103.5 days and mass ratios (q) in the 0.1 < q < 1 range. The large stellar radii of these supergiant stars prevent short orbital periods, but we demonstrate that this effect alone cannot explain our results. We assessed the spectra and RV time series of the detected binary systems and find that only a small fraction display convincing solutions. We conclude that the multiplicity fractions are compromised by intrinsic stellar variability, such that the true multiplicity fraction may be significantly smaller. Our main conclusions from comparing the multiplicity properties of the B5–9- and AF-type supergiants to that of their less evolved counterparts is that such stars cannot be explained by a direct evolution from the main sequence. Furthermore, by comparing their multiplicity properties to red supergiant stars, we conclude that the AF supergiant stars are neither progenitors nor descendants of red supergiants
Fully independent response in disordered solids
No full textUnlike in crystals, it is difficult to trace emergent material properties of amorphous solids to their underlying structure. Nevertheless, one can tune features of a disordered spring network, ranging from bulk elastic constants to specific allosteric responses, through highly precise alterations of the structure. This has been understood through the notion of independent bond-level response—the observation that, in many cases, different springs have different effects on different properties. While this idea has motivated inverse design in numerous contexts, it has not been formalized and quantified in a general context that not just informs but enables and predicts inverse design. Here, we show how to quantify independent response by linearizing the simultaneous change in multiple emergent features, and introduce the much stronger notion of fully independent response. Remarkably, we find that the mechanical properties of disordered solids are always fully independent across a wide array of scenarios, regardless of the target features, tunable parameters, system size, dimensionality, and class of interactions. Furthermore, our formulation quantifies the susceptibility of features to parameter changes, which is correlated with the maximum linear tunability. We also demonstrate the implications for multifeature inverse design beyond the linear regime. These results formalize our understanding of a key fundamental difference between ordered and disordered solids while also creating a practical tool to both understand and perform inverse design
Empirical analysis of binding precedent efficiency in Brazilian Supreme Court via case classification
No full textBinding precedents (súmulas vinculantes) constitute a juridical instrument unique to the Brazilian legal system and whose objectives include the protection of the Federal Supreme Court against repetitive demands. Studies of the effectiveness of these instruments in decreasing the Court’s exposure to similar cases, however, indicate that they tend to fail in such a direction, with some of the binding precedents seemingly creating new demands. We empirically assess the legal impact of five binding precedents, 11, 14, 17, 26, and 37, at the highest Court level through their effects on the legal subjects they address. This analysis is only possible through the comparison of the Court’s ruling about the precedents’ themes before they are created, which means that these decisions should be detected through techniques of Similar Case Retrieval, which we tackle from the angle of Case Classification. The contributions of this article are therefore twofold: on the mathematical side, we compare the use of different methods of Natural Language Processing — TF-IDF, LSTM, Longformer, and regex — for Case Classification, whereas on the legal side, we contrast the inefficiency of these binding precedents with a set of hypotheses that may justify their repeated usage. We observe that the TF-IDF models performed slightly better than LSTM and Longformer when compared through common metrics; however, the deep learning models were able to detect certain important legal events that TF-IDF missed. On the legal side, we argue that the reasons for binding precedents to fail in responding to repetitive demand are heterogeneous and case-dependent, making it impossible to single out a specific cause. We identify five main hypotheses, which are found in different combinations in each of the precedents studied
Color-avoiding percolation on the Erdős–Rényi random graph
No full textWe consider a recently introduced model of color-avoiding percolation (abbreviated CA-percolation) defined as follows. Every edge in a graph G is colored in some of k>=2 colors. Two vertices u and v in G are said to be CA-connected if u and v may be connected using any subset of k-1 colors. CA-connectivity defines an equivalence relation on the vertex set of G whose classes are called CA-components.
We study the component structure of a randomly colored Erdős–Rényi random graph of constant average degree. We distinguish three regimes for the size of the largest component: a supercritical regime, a so-called intermediate regime, and a subcritical regime, in which the largest CA-component has respectively linear, logarithmic, and bounded size. Interestingly, in the subcritical regime, the bound is deterministic and given by the number of colors
Data - Sustainable Development Key to Limiting Climate Change-Driven Wildfire Damages
No full textThis repository contains the data and scripts required to reproduce the results of the manuscript "Sustainable Development Key to Limiting Climate Change-Driven Wildfire Damages" submitted to the Environmental Research Climate Journal (ERCL)
High-dimensional analysis of knowledge distillation: Weak-to-Strong generalization and scaling laws
No full textA growing number of machine learning scenarios rely on knowledge distillation where one uses the output of a surrogate model as labels to supervise the training of a target model. In this work, we provide a sharp characterization of this process for ridgeless, high-dimensional regression, under two settings: (i) model shift, where the surrogate model is arbitrary, and (ii) distribution shift, where the surrogate model is the solution of empirical risk minimization with out-of-distribution data. In both cases, we characterize the precise risk of the target model through non-asymptotic bounds in terms of sample size and data distribution under mild conditions. As a consequence, we identify the form of the optimal surrogate model, which reveals the benefits and limitations of discarding weak features in a data-dependent fashion. In the context of weak-to-strong (W2S) generalization, this has the interpretation that (i) W2S training, with the surrogate as the weak model, can provably outperform training with strong labels under the same data budget, but (ii) it is unable to improve the data scaling law. We validate our results on numerical experiments both on ridgeless regression and on neural network architectures
Arginine dynamics probed by magic-angle spinning NMR with a specific isotope-labeling scheme
No full textThe specific introduction of ^1H-^13C or ^1H-^15N moieties into otherwise deuterated proteins holds great potential for high-resolution solution and magic-angle spinning (MAS) NMR studies of protein structure and dynamics. Arginine residues play key roles for example at active sites of enzymes. Taking advantage of a chemically synthesized Arg with a ^13C-^1H2 group in an otherwise deuterated backbone, we demonstrate here the usefulness of proton-detected MAS NMR approaches to probe arginine dynamics. In experiments with crystalline ubiquitin and the 134 kDa tetrameric enzyme malate dehydrogenase we detected a wide range of motions, from sites that are rigid on time scales of at least tens of milliseconds to residues undergoing predominantly nanosecond motions. Spin-relaxation and dipolar-coupling measurements enabled quantitative determination of these dynamics. We observed microsecond dynamics of residue Arg54 in crystalline ubiquitin, whose backbone is known to sample different β-turn conformations on this time scale. The labeling scheme and experiments presented here expand the toolkit for high-resolution proton-detected MAS NMR
Dual role of pectin methyl esterase activity in the regulation of plant cell wall biophysical properties
No full textIntroduction: Acid-growth theory has been postulated in the 70s to explain the rapid elongation of plant cells in response to the hormone auxin. More recently, it has been demonstrated that activation of the proton ATPs pump (H+-ATPs) promoting acidification of the apoplast is the principal mechanism by which auxin and other hormones such as brassinosteroids (BR) induce cell elongation. Despite these advances, the impact of this acidification on the mechanical properties of the cell wall remained largely unexplored.
Methods: Here, we use elongation assays of Arabidopsis thaliana hypocotyls and Atomic Force Microscopy (AFM) to correlate hormone-induced tissue elongation and local changes in cell wall mechanical properties. Furthermore, employing transgenic lines over-expressing Pectin Methyl Esterase (PME), along with calcium chelators, we investigate the effect of pectin modification in hormone-driven cell elongation.
Results: We demonstrate that acidification of apoplast is necessary and sufficient to induce cell elongation through promoting cell wall softening. Moreover, we show that enhanced PME activity can induce both cell wall softening or stiffening in extracellular calcium dependent-manner and that tight control of PME activity is required for proper hypocotyl elongation.
Discussion: Our results confirm a dual role of PME in plant cell elongation. However, further investigation is needed to assess the status of pectin following short- or long-term PME treatments in order to determine if pectin methyl-esterification might promote its degradation as well as the role of PME inhibitors upon PME induction
Ancestral origin and functional expression of a hyaluronic acid pathway complement in mussels
No full textHyaluronic acid (HA) is a key extracellular matrix component of vertebrates, where it mediates cell adhesion, immune regulation, and tissue remodeling through its interaction with specific receptors. Although HA has been detected in a few invertebrate species, the lack of fundamental components of the molecular HA pathway poses relevant objections about its functional role in these species. Mining genomic and transcriptomic data, we considered the conservation of the gene locus encoding for the extracellular link protein (XLINK) in marine mussels as well as its expression patterns. Structural and phylogenetic analyses were undertaken to evaluate possible similarities with vertebrate orthologs and to infer the origin of this gene in invertebrates. Biochemical analysis was used to quantify HA in tissues of Mytilus galloprovincialis. As a result, we confirm that the mussel can produce HA (up to 1.02 ng/mg in mantle) and that its genome encodes two XLINK gene loci. These loci are conserved in Mytilidae species and show a complex evolutionary path. Mussel XLINK genes appeared to be expressed during developmental stages in three mussel species, ranking in the top 100 expressed genes in M. trossulus at 17 h post-fertilization. In conclusion, the presence of HA and an active gene with the potential to bind HA suggests that mussels have the potential to synthesize and use HA and are among the few invertebrates encoding this gene
Germin-like protein 1 interacts with proteasome regulator 1 to regulate auxin signaling by controlling Aux/IAA homeostasis
No full textAuxin regulates various aspects of plant growth and development by modulating the transcription of target genes through the degradation of auxin/indole-3-acetic acid (Aux/IAA) repressors via the 26S proteasome. Proteasome regulator 1 (PTRE1), a positive regulator of proteasome activity, has been implicated in auxin-mediated proteasome suppression; however, the mechanism by which auxin modulates PTRE1 function remains unclear. Here, we demonstrate that auxin promotes the interaction between germin-like protein 1 (GLP1) and PTRE1, facilitating PTRE1 retention at the plasma membrane. The relocation of PTRE1 results in reduced nuclear 26S proteasome activity, and thus the attenuated Aux/IAA degradation and altered Aux/IAA homeostasis, ultimately resulting in suppressed auxin-mediated transcriptional regulation. Our findings uncover a previously uncharacterized regulatory axis in auxin signaling that controls Aux/IAA protein stability, functioning alongside the TIR1- and TRANSMEMBRANE KINASE 1 (TMK1)-mediated pathways, and highlight the coordination of auxin signaling from the cell surface to the nucleus via auxin-induced PTRE1 relocation, which fine-tunes Aux/IAA protein homeostasis and auxin responses