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Atmospheric rivers (ARs) are filamentary structures within the atmosphere that account for a substantial portion of poleward moisture transport and play an important role in Earth's hydroclimate. However, there is no one quantitative definition for what constitutes an atmospheric river, leading to uncertainty in quantifying how these systems respond to global change. This study seeks to better understand how different AR detection tools (ARDTs) respond to changes in climate states utilizing single‐forcing climate model experiments under the aegis of the Atmospheric River Tracking Method Intercomparison Project (ARTMIP). We compare a simulation with an early Holocene orbital configuration and another with CO₂levels of the Last Glacial Maximum to a preindustrial control simulation to test how the ARDTs respond to changes in seasonality and mean climate state, respectively. We find good agreement among the algorithms in the AR response to the changing orbital configuration, with a poleward shift in AR frequency that tracks seasonal poleward shifts in atmospheric water vapor and zonal winds. In the low CO₂simulation, the algorithms generally agree on the sign of AR changes, but there is substantial spread in their magnitude, indicating that mean‐state changes lead to larger uncertainty. This disagreement likely arises primarily from differences between algorithms in their thresholds for water vapor and its transport used for identifying ARs. These findings warrant caution in ARDT selection for paleoclimate and climate change studies in which there is a change to the mean climate state, as ARDT selection contributes substantial uncertainty in such cases. 

Les proveedores de salud en Puerto Rico se han convertido en expertos en brindar atención médica de manera ética en el contexto de desastres múltiples. A lo largo de las consecuencias devastadoras del Huracán María en el 2017, un enjambre sísmico que comenzó en el 2019 y la pandemia de SARS-COV-2 a partir del 2020, les trabajadores de la salud en Puerto Rico han servido a sus pacientes, colegas, familiares, vecinos y amistades de una forma basada en el cuidado mutuo. Basado en el análisis de ciento cincuenta y una (151) entrevistas etnográficas y nueve (9) grupos focales, este informe documenta el desgaste emocional y físico que han vivido les trabajadores de salud durante esta cascada de desastres. Señalar los problemas institucionales que causan el desgaste y la herida moral entre les trabajadores de la salud en Puerto Rico pudiese contribuir a mejorar la seguridad, sustentabilidad y resiliencia del sistema de salud puertorriqueño. En este informe enumeramos los desafíos sistémicos que causan y contribuyen al agotamiento y la herida moral en les trabajadores de la salud en Puerto Rico, como lo son: los salarios bajos, las reducciones de personal, los abusos de las compañías de seguro y la falta de preparación y planificación institucional y estatal para los desastres. Además, constatamos que muchas personas que entrevistamos identificaron desafíos en sus vidas laborales y personales vinculados al desgaste y a la presencia de una herida moral. Algunos de estos desafíos incluyen: la dificultad para regular sus emociones, el reto de balancear el trabajo con la vida personal, el manejo de estrés, la tensión en sus relaciones personales, incluyendo la demanda incremental de personas queridas con necesidades de salud y una gran dificultad para poder relajarse. En este informe enfatizamos las experiencias de agotamiento de les trabajadores de salud, así como los cambios políticos y protocolarios recomendados por elles mismes. Los cambios sugeridos y descritos aquí pudieran mejorar las condiciones laborales de este sector tan importante y mejorar la salud de todes les puertorriqueñes. Frente a la crisis prolongada existente, nuestra investigación evidencia la existencia de propuestas concretas y del deseo de aprovechar la sabiduría acumulada del pueblo. 

Hypothesis The interaction of active particles with walls can explain discrepancies between experiments and theory derived for particles in the bulk. For an electric field driven metallodielectric Janus particle (JP) adjacent to an electrode, interaction between the asymmetric particle and the partially screened electrode yields a net electrostatic force – termed self-dielectrophoresis (sDEP) - that competes with induced-charge electrophoresis (ICEP) to reverse particle direction. Experiments The potential contribution of hydrodynamic flow to the reversal is evaluated by visualizing flow around a translating particle via micro-particle image velocimetry and chemically suppressing ICEP with poly(l-lysine)-g-poly(ethylene glycol) (PLL-PEG). Mobility of Polystyrene-Gold JPs is measured in KCl electrolytes of varying concentration and with a capacitive SiO2 coating at the metallic JP surface or electrode. Results are compared with theory and numerical simulations accounting for electrode screening. Findings PLL-PEG predominantly suppresses low-frequency mobility where propulsive electro-hydrodynamic jetting is observed; supporting the hypothesis of an electrostatic driving force at high frequencies. Simulations and theory show the magnitude, direction and frequency dispersion of JP mobility are obtained by superposition of ICEP and sDEP using the JP height and capacitance as fitting parameters. Wall proximity enhances ICEP and sDEP and manifests a secondary ICEP charge relaxation time dominating in the contact limit. 

Context. Rubidium is one of the few elements produced by the neutron capture s - and r -processes in almost equal proportions. Recently, a Rb deficiency ([Rb/Fe] < 0.0), amounting to a factor of about two with respect to the Sun, has been found in M dwarfs of near-solar metallicity. This stands in contrast to the close-to-solar [Sr, Zr/Fe] ratios derived in the same stars. This deficiency is difficult to understand from the point of view of observations and of nucleosynthesis. Aims. To test the reliability of this Rb deficiency, we study the Rb and Zr abundances in a sample of KM-type giant stars across a similar metallicity range, extracted from the AMBRE Project. Methods. We used high-resolution and high signal-to-noise spectra to derive Rb and Zr abundances in a sample of 54 bright giant stars with metallicities in the range of −0.6 ≲ [Fe/H] ≲ +0.4 dex, via spectral synthesis in both local and non-local thermodynamic equilibrium (LTE and NLTE, respectively). We also studied the impact of the Zeeman broadening in the profile of the Rb  I at λ 7800 Å line. Results. The LTE analysis also results in a Rb deficiency in giant stars, however, it is considerably lower than that obtained in M dwarfs. However, once NLTE corrections are performed, the [Rb/Fe] ratios are very close to solar (average −0.01 ± 0.09 dex) in the full metallicity range studied here. This stands in contrast to the value found for M dwarfs. The [Zr/Fe] ratios derived are in excellent agreement with those obtained in previous studies in FGK dwarf stars with a similar metallicity. We investigate the effect of gravitational settling and magnetic activity as possible causes of the Rb deficiency found in M dwarfs. Although the former phenomenon has a negligible impact on the surface Rb abundance, the presence of an average magnetic field with an intensity that is typical of that observed in M dwarfs may result in systematic Rb abundance underestimations if the Zeeman broadening is not considered in the spectral synthesis. This may explain the Rb deficiency in M dwarfs, but not fully. On the other hand, the new [Rb/Fe] and [Rb/Zr] versus [Fe/H] relationships can be explained when the Rb production by rotating massive stars and low-to-intermediate mass stars (these latter also producing Zr) are considered, without the need to deviate from the standard s -process nucleosynthesis in asymptotic giant branch stars, as suggested previously. 

Abstract SBND is the near detector of the Short-Baseline Neutrino program at Fermilab. Its location near to the Booster Neutrino Beam source and relatively large mass will allow the study of neutrino interactions on argon with unprecedented statistics. This paper describes the expected performance of the SBND photon detection system, using a simulated sample of beam neutrinos and cosmogenic particles. Its design is a dual readout concept combining a system of 120 photomultiplier tubes, used for triggering, with a system of 192 X-ARAPUCA devices, located behind the anode wire planes. Furthermore, covering the cathode plane with highly-reflective panels coated with a wavelength-shifting compound recovers part of the light emitted towards the cathode, where no optical detectors exist. We show how this new design provides a high light yield and a more uniform detection efficiency, an excellent timing resolution and an independent 3D-position reconstruction using only the scintillation light. Finally, the whole reconstruction chain is applied to recover the temporal structure of the beam spill, which is resolved with a resolution on the order of nanoseconds. 

Abstract The Pandora Software Development Kit and algorithm libraries perform reconstruction of neutrino interactions in liquid argon time projection chamber detectors. Pandora is the primary event reconstruction software used at the Deep Underground Neutrino Experiment, which will operate four large-scale liquid argon time projection chambers at the far detector site in South Dakota, producing high-resolution images of charged particles emerging from neutrino interactions. While these high-resolution images provide excellent opportunities for physics, the complex topologies require sophisticated pattern recognition capabilities to interpret signals from the detectors as physically meaningful objects that form the inputs to physics analyses. A critical component is the identification of the neutrino interaction vertex. Subsequent reconstruction algorithms use this location to identify the individual primary particles and ensure they each result in a separate reconstructed particle. A new vertex-finding procedure described in this article integrates a U-ResNet neural network performing hit-level classification into the multi-algorithm approach used by Pandora to identify the neutrino interaction vertex. The machine learning solution is seamlessly integrated into a chain of pattern-recognition algorithms. The technique substantially outperforms the previous BDT-based solution, with a more than 20% increase in the efficiency of sub-1 cm vertex reconstruction across all neutrino flavours.