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Preclinical amyloid pathology is associated with anxiety but not depression in cognitively normal older adults: Evidence for differential neuropsychiatric pathways
No full texthttp://dx.doi.org/10.13039/100000957 Alzheimer's Associatio
Evaluation of a quantitative method for measuring the spatial resolution of a gamma camera using a bar phantom
No full textResminostat for maintenance treatment in patients with advanced-stage mycosis fungoides or Sézary syndrome: a multicentre, double-blind, randomised, placebo-controlled, phase 2 trial
No full textTime-Resolved Photoelectrochemical Measurements To Study Band Bending of BiVO 4 Photoanodes
No full textTransforming jet flavour tagging at ATLAS
No full textAbstract Jet flavour tagging enables the identification of jets originating from heavy-flavour quarks in proton–proton collisions at the Large Hadron Collider, playing a critical role in its physics programmes. This paper presents GN2, a transformer-based flavour tagging algorithm deployed by the ATLAS Collaboration that represents a different methodology compared to previous approaches. Designed to classify jets based on the flavour of their constituent particles, GN2 processes low-level tracking information in an end-to-end architecture and incorporates physics-informed auxiliary training objectives to enhance both interpretability and performance. Its performance is validated in both simulation and collision data. The measured c -jet (light-jet) rejection in data is improved by a factor of 3.5 (1.8) for a 70% b -jet tagging efficiency, compared to the previous algorithm. GN2 provides substantial benefits for physics analyses involving heavy-flavour jets, such as measurements of Higgs boson pair production and the couplings of bottom and charm quarks to the Higgs boson, and demonstrates the impact of advanced machine learning methods in experimental particle physics
Author Correction: Structural basis for translational control by the human 48S initiation complex
No full textThe potential effect of albumin replacement on immune modulation and sphingosine 1-phosphate dynamics
No full textElemental abundance pattern and temperature inversion on the dayside of HAT-P-70b observed with CARMENES and PEPSI
No full textGround-based high-resolution spectroscopic observations have identified various chemical species in the atmosphere of numerous ultra-hot Jupiters (UHJs), including neutral and ionized metals. These detections have offered valuable insights into planet formation mechanisms via abundance measurements of refractory elements. We observed the dayside thermal emission spectrum of UHJ HAT-P-70b using the high-resolution spectrographs CARMENES and PEPSI. Through our cross-correlation analysis, we detected emission signals for Al I , AlH, Ca II , Cr I , Fe I , Fe II , Mg I , Mn I , and Ti I , marking the first detection of Al I and AlH in an exoplanetary atmosphere. Tentative signals of C I , Ca I , Na I , NaH, and Ni i were also identified. Based on those detections, we were able to perform atmospheric retrievals to constrain the thermal profile and elemental abundances of the planet’s dayside hemisphere. The retrieved temperature-pressure profile reveals a strong temperature inversion layer. The chemical free retrieval yielded a metallicity of [Fe/H] = 0.38 −1.11 +0.74 , while the chemical equilibrium retrieval resulted in [Fe/H] = 0.23 −0.98 +1.08 , with both values consistent with the solar metallicity. We also tentatively found an enriched abundance of Ni, which could result from the accretion of Ni-rich planetesimals during the planet’s formation. On the other hand, elements with condensation temperatures above 1400 K(e.g., Ca, Ti, and V) appear to be slightly depleted, possibly due to cold-trapping on the planet’s nightside. However, Al, with the highest condensation temperature at 1653 K, displays a solar-like abundance, which might reflect the formation-related enrichment of Al. Our retrieval indicates extremely high volume mixing ratios of metal ions (Fe II and Ca II ), which are significantly inconsistent with predictions from chemical equilibrium models. This disequilibrium suggests that the atmosphere is likely undergoing significant hydrodynamic escaping, which enhances the atmospheric density at high altitudes where the ionic lines are formed
Firm-level innovation, productivity, and efficiency in riskful business environments: A case study of agribusiness in El Salvador
No full textAbstract Agribusinesses contribute 40–70 percent of the total value added in the food value chain of developing countries; however, they remain under-researched. We investigate whether firm-level innovation improves economic performance using World Bank Enterprise Surveys for El Salvador. We extend the Crépon–Duguet–Mairesse model with a selectivity-corrected stochastic frontier and a metafrontier framework. We find that innovation increases potential total sales and reduces the technology gap, but does not improve technical efficiency. This suggests that, without complementary managerial and institutional support—particularly in contexts where insecurity imposes high operational and opportunity costs—the benefits of innovation do not necessarily lead to productivity gains