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The two-particle momentum correlation functions between charm mesons (D∗± and D±) and charged light-flavor mesons (π± and K±) in all charge-combinations are measured for the first time by the ALICE Collaboration in high-multiplicity proton-proton collisions at a center-of-mass energy of s√=13 TeV. For DK and D∗K pairs, the experimental results are in agreement with theoretical predictions of the residual strong interaction based on quantum chromodynamics calculations on the lattice and chiral effective field theory. In the case of Dπ and D∗π pairs, tension between the calculations including strong interactions and the measurement is observed. For all particle pairs, the data can be adequately described by Coulomb interaction only, indicating a shallow interaction between charm and light-flavor mesons. Finally, the scattering lengths governing the residual strong interaction of the Dπ and D∗π systems are determined by fitting the experimental correlation functions with a model that employs a Gaussian potential. The extracted values are small and compatible with zero.
Here, we introduce racoon_clip, a sustainable and fully automated pipeline for the complete processing of iCLIP and eCLIP data to extract RNA binding signal at single-nucleotide resolution. racoon_clip is easy to install and execute, with multiple pre-settings and fully customizable parameters, and outputs a conclusive summary report with visualizations and statistics for all analysis steps.
Studying the neural basis of human dynamic visual perception requires extensive experimental data to evaluate the large swathes of functionally diverse brain neural networks driven by perceiving visual events. Here, we introduce the BOLD Moments Dataset (BMD), a repository of whole-brain fMRI responses to over 1,000 short (3s) naturalistic video clips of visual events across ten human subjects. We use the videos’ extensive metadata to show how the brain represents word- and sentence-level descriptions of visual events and identify correlates of video memorability scores extending into the parietal cortex. Furthermore, we reveal a match in hierarchical processing between cortical regions of interest and video-computable deep neural networks, and we showcase that BMD successfully captures temporal dynamics of visual events at second resolution. With its rich metadata, BMD offers new perspectives and accelerates research on the human brain basis of visual event perception.
Highlights
• Family structure transitions decrease academic school track attendance among children of less educated parents.
• Children of highly educated fathers in single-mother families also have lower outcomes.
• Reduced income and increased exposure to poverty are relevant mediators.
• There is no cumulative disadvantage linked to a further transition to a stepfamily.
• Previous parental separation does not affect educational outcomes for children residing with a highly educated stepfather.
Abstract
Recent research has documented that the effect of parental separation on children’s educational outcomes depends on socioeconomic background. Yet, parental separation could lead to a stable single-parent family or to a further transition to a stepfamily. Little is known about how the effect of family structure transitions on educational outcomes depends on the education of parents and stepparents, and there has been limited empirical research into the mechanisms that explain heterogeneity in the effects of family transitions. Using longitudinal data from the German Socio-Economic Panel and models with entropy balancing and sibling fixed effects, I explore the heterogeneous effects of family transitions during early and middle childhood on academic secondary school track attendance, grades and aspirations. I find that family transitions only reduce the academic school track attendance among children of less educated parents living in stepfamilies or with a single mother after parental separation, and among children of highly educated fathers living in single-mother families. The mechanisms that partly explain these effects relate to reduced income and exposure to poverty after parental separation. The findings underscore the importance of considering the stepparent's educational level, indicating that the adverse consequences of parental separation on educational outcomes are mitigated when a highly educated stepfather becomes part of the family. Overall, these findings align more closely with the resource perspective than the family stability perspective.
Although iron-based catalysts are regarded as a promising alternative to precious metal catalysts, their precise electronic structures during catalysis still pose challenges for computational descriptions. A particularly urgent question is the influence of the environment on the electronic structure, and how to describe this properly with computational methods. Here, we study an iron porphyrin chloride complex adsorbed on a graphene sheet using density functional theory calculations to detail how much the electronic structure is influenced by the presence of a graphene layer. Our results indicate that weak interactions due to van der Waals forces dominate between the porphyrin complex and graphene, and only a small amount of charge is transferred between the two entities. Furthermore, the interplay of the ligand field environment, strong p − d hybridization, and correlation effects within the complex are strongly involved in determining the spin state of the iron ion. By bridging molecular chemistry and solid state physics, this study provides first steps towards a joint analysis of the properties of iron-based catalysts from first principles.
We prove that the projectivized strata of differentials are not contained in pointed Brill-Noether divisors, with only a few exceptions. For a generic element in a stratum of differentials, we show that many of the associated pointed Brill-Noether loci are of expected dimension. We use our results to study the Auel-Haburcak Conjecture: We obtain new non-containments between maximal Brill-Noether loci in Mg. Our results regarding quadratic differentials imply that the quadratic strata in genus 6 are uniruled.
For genus g=r(r+1)2+1, we prove that via the forgetful map, the universal Prym-Brill-Noether locus Rrg has a unique irreducible component dominating the moduli space Rg of Prym curves.
Can prediction error explain predictability effects on the N1 during picture-word verification?
(2024)
Do early effects of predictability in visual word recognition reflect prediction error? Electrophysiological research investigating word processing has demonstrated predictability effects in the N1, or first negative component of the event-related potential (ERP). However, findings regarding the magnitude of effects and potential interactions of predictability with lexical variables have been inconsistent. Moreover, past studies have typically used categorical designs with relatively small samples and relied on by-participant analyses. Nevertheless, reports have generally shown that predicted words elicit less negative-going (i.e., lower amplitude) N1s, a pattern consistent with a simple predictive coding account. In our preregistered study, we tested this account via the interaction between prediction magnitude and certainty. A picture-word verification paradigm was implemented in which pictures were followed by tightly matched picture-congruent or picture-incongruent written nouns. The predictability of target (picture-congruent) nouns was manipulated continuously based on norms of association between a picture and its name. ERPs from 68 participants revealed a pattern of effects opposite to that expected under a simple predictive coding framework.
The hippocampal-dependent memory system and striatal-dependent memory system modulate reinforcement learning depending on feedback timing in adults, but their contributions during development remain unclear. In a 2-year longitudinal study, 6-to-7-year-old children performed a reinforcement learning task in which they received feedback immediately or with a short delay following their response. Children’s learning was found to be sensitive to feedback timing modulations in their reaction time and inverse temperature parameter, which quantifies value-guided decision-making. They showed longitudinal improvements towards more optimal value-based learning, and their hippocampal volume showed protracted maturation. Better delayed model-derived learning covaried with larger hippocampal volume longitudinally, in line with the adult literature. In contrast, a larger striatal volume in children was associated with both better immediate and delayed model-derived learning longitudinally. These findings show, for the first time, an early hippocampal contribution to the dynamic development of reinforcement learning in middle childhood, with neurally less differentiated and more cooperative memory systems than in adults.
Isothermal titration calorimetry (ITC) is a widely used technique for the characterization of protein-protein and protein-ligand interactions. It provides information on the stoichiometry, affinity, and the thermodynamic driving forces of interactions. This chapter exemplifies the use of ITC to investigate interactions between human autophagy modifiers (LC3/GABARAP proteins) and their interaction partners, the LIR motif containing sequences. The purpose of this report is to present a detailed protocol for the production of LC3/GABARAP-interacting LIR peptides using E. coli expression systems. In addition, we outline the design of ITC experiments using the LC3/GABARAP:peptide interactions as an example. Comprehensive troubleshooting notes are provided to facilitate the adaptation of these protocols to different ligand-receptor systems. The methodology outlined for studying protein-ligand interactions will help to avoid common errors and misinterpretations of experimental results.