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The RABBITT setup is theoretically studied for various combinations of XUV and IR field components polarization: 'linear+linear', `linear+circular' with crossed propagation directions, and `circular+circular' with parallel propagation directions. The general properties of photoelectron angular distributions and their responses to the variation of the IR pulse delay are studied. Numerical simulations are performed for the neon valence shell ionization into the region of structureless continuum using two approaches based on time dependent perturbation theory and solution of rate equations. To distinguish between "geometrical" governed by fields' polarization and spectroscopic features, additional analysis for the case of $s$-shell ionization is presented., Comment: 10 pages, 5 figures; some references were misplaced in the first version + minor polishing

The Milky Way's Central Molecular Zone (CMZ) differs dramatically from our local solar neighbourhood, both in the extreme interstellar medium conditions it exhibits (e.g. high gas, stellar, and feedback density) and in the strong dynamics at play (e.g. due to shear and gas influx along the bar). Consequently, it is likely that there are large-scale physical structures within the CMZ that cannot form elsewhere in the Milky Way. In this paper, we present new results from the Atacama Large Millimeter/submillimeter Array (ALMA) large programme ACES (ALMA CMZ Exploration Survey) and conduct a multi-wavelength and kinematic analysis to determine the origin of the M0.8$-$0.2 ring, a molecular cloud with a distinct ring-like morphology. We estimate the projected inner and outer radii of the M0.8$-$0.2 ring to be 79" and 154", respectively (3.1 pc and 6.1 pc at an assumed Galactic Centre distance of 8.2 kpc) and calculate a mean gas density $> 10^{4}$ cm$^{-3}$, a mass of $\sim$ $10^6$ M$_\odot$, and an expansion speed of $\sim$ 20 km s$^{-1}$, resulting in a high estimated kinetic energy ($> 10^{51}$ erg) and momentum ($> 10^7$ M$_\odot$ km s$^{-1}$). We discuss several possible causes for the existence and expansion of the structure, including stellar feedback and large-scale dynamics. We propose that the most likely cause of the M0.8$-$0.2 ring is a single high-energy hypernova explosion. To viably explain the observed morphology and kinematics, such an explosion would need to have taken place inside a dense, very massive molecular cloud, the remnants of which we now see as the M0.8$-$0.2 ring. In this case, the structure provides an extreme example of how supernovae can affect molecular clouds., Comment: 17 pages, 13 figures, and 2 tables. Published in Astronomy & Astrophysics

Recent mid-infrared observations with JWST/MIRI have resulted in the first direct detections of absorption features from silicate clouds in the transmission spectra of two transiting exoplanets, WASP-17 b and WASP-107 b. In this paper, we measure the mid-infrared ($5-12$ $\mu$m) dayside emission spectrum of the benchmark hot Jupiter HD 189733 b with MIRI LRS by combining data from two secondary eclipse observations. We confirm the previous detection of H$_2$O absorption at 6.5 $\mu$m from Spitzer/IRS and additionally detect H$_2$S as well as an absorption feature at 8.7 $\mu$m in both secondary eclipse observations. The excess absorption at 8.7 $\mu$m can be explained by the presence of small ($\sim$0.01 $\mu$m) grains of SiO$_2$[s] in the uppermost layers of HD 189733 b's dayside atmosphere. This is the first direct detection of silicate clouds in HD 189733 b's atmosphere, and the first detection of a distinct absorption feature from silicate clouds on the day side of any hot Jupiter. We find that models including SiO$_2$[s] are preferred by $6-7\sigma$ over clear models and those with other potential cloud species. The high altitude location of these silicate particles is best explained by formation in the hottest regions of HD 189733 b's dayside atmosphere near the substellar point. We additionally find that HD 189733 b's emission spectrum longward of 9 $\mu$m displays residual features not well captured by our current atmospheric models. When combined with other JWST observations of HD 189733 b's transmission and emission spectrum at shorter wavelengths, these observations will provide us with the most detailed picture to date of the atmospheric composition and cloud properties of this benchmark hot Jupiter., Comment: 21 pages, 7 Figures, 3 Tables, Accepted to ApJL

We propose and computationally implement a dynamic neural model of lexical meaning, and experimentally test its behavioral predictions. We demonstrate the architecture and behavior of the model using as a test case the English lexical item 'have', focusing on its polysemous use. In the model, 'have' maps to a semantic space defined by two continuous conceptual dimensions, connectedness and control asymmetry, previously proposed to parameterize the conceptual system for language. The mapping is modeled as coupling between a neural node representing the lexical item and neural fields representing the conceptual dimensions. While lexical knowledge is modeled as a stable coupling pattern, real-time lexical meaning retrieval is modeled as the motion of neural activation patterns between metastable states corresponding to semantic interpretations or readings. Model simulations capture two previously reported empirical observations: (1) contextual modulation of lexical semantic interpretation, and (2) individual variation in the magnitude of this modulation. Simulations also generate a novel prediction that the by-trial relationship between sentence reading time and acceptability should be contextually modulated. An experiment combining self-paced reading and acceptability judgments replicates previous results and confirms the new model prediction. Altogether, results support a novel perspective on lexical polysemy: that the many related meanings of a word are metastable neural activation states that arise from the nonlinear dynamics of neural populations governing interpretation on continuous semantic dimensions.

We employ the phospholipid bilayer membranes of giant unilamellar vesicles as a free-standing environment for the growth of membrane-integrated ultrathin phospholipid crystals possessing a variety of shapes with 6-fold symmetry. Crystal growth within vesicle membranes, where more elaborate shapes grow on larger vesicles is dominated by the bending energy of the membrane itself, creating a means to manipulate crystal morphology. Here we demonstrate how cooling rate preconditions the membrane tension before nucleation, in turn regulating nucleation and growth, and directing the morphology of crystals by the time they are large enough to be visualized. The crystals retain their shapes during further growth through the two phase region. Experiments demonstrate this behavior for single crystals growing within the membrane of each vesicle, ultimately comprising up to 13% of the vesicle area and length scales of up to 50 microns. A model for stress evolution, employing only physical property data, reveals how the competition between thermal membrane contraction and water diffusion from tensed vesicles produces a size- and time-dependence of the membrane tension as a result of cooling history. The tension, critical in the contribution of bending energy in the fluid membrane regions, in turn selects for crystal shape for vesicles of a given size. The model reveals unanticipated behaviors including a low steady state tension on small vesicles that allows compact domains to develop, rapid tension development on large vesicles producing flower-shaped domains, and a stress relaxation through water diffusion across the membrane with a time constant scaling as the square of the vesicle radius, consistent with measurable tensions only in the largest vesicles., Comment: Main text 32 pages and 7 figures; SI 4 pages and 4 figures

When either privileged or under-resourced families navigate gray areas in the law, including federal laws related to students with disabilities such as Section 504 of the Rehabilitation Act, inequities are revealed. Research and emerging trends have raised increasing concerns about unfairness and abuses of disability policies, particularly with regard to intersectional disadvantages and advantages that may emerge in the implementation of Section 504, depending on a student's social identities. In this policy brief, the authors present research that should inform policymaking around Section 504. They also consider the trends documenting ongoing and even increasing inequities in how the law is being used. Because many of these inequities are systemic, they provide recommendations that include policy actions at the federal, state, and local levels.

Using low-energy muons, we map the charge carrier concentration as a function of depth and electric field across the \SiOSi interface up to a depth of \SI{100}{\nano\meter} in Si-based MOS capacitors. The results show that the formation of the anisotropic bond-centered muonium \MuBCz state in Si serves as a direct measure of the local changes in electronic structures. Different band-bending conditions could be distinguished, and the extension of the depletion width was directly extracted using the localized stopping and probing depth of the muons. Furthermore, electron build-up on the Si side of the \SiOO/Si interface, caused by the mirror charge induced by the fixed positive charge in the oxide and the image force effect, was observed. Our work represents a significant extension of the application of the muon spin rotation technique ($\mu$SR) and lays the foundation for further research on direct observation of charge carrier density manipulation at technologically important semiconductor device interfaces.

Motivated by recent studies of two-phase lipid vesicles possessing 2D solid domains integrated within a fluid bilayer phase, we study the shape equilibria of closed vesicles possessing a single planar, circular inclusion. While 2D solid elasticity tends to expel Gaussian curvature, topology requires closed vesicles to maintain an average, non-zero Gaussian curvature leading to an elementary mechanism of shape frustration that increases with inclusion size. We study elastic ground states of the Helfrich model of the planar-fluid composite vesicles, analytically and computationally, as a function of planar fraction and reduced volume. Notably, we show that incorporation of a planar inclusion of only a few percent dramatically shifts the ground state shapes of vesicles from predominantly {\it prolate} to {\it oblate}, and moreover, shifts the optimal surface to volume ratio far from spherical shapes. We show that for sufficiently small planar inclusions, the elastic ground states break symmetry via a complex variety of asymmetric oblate, prolate, and triaxial shapes, while inclusion sizes above about $8\%$ drive composite vesicles to adopt axisymmetric oblate shapes. These predictions cast useful light on the emergent shape and mechanical responses of fluid-solid composite vesicles., Comment: 15 pages, 13 figures, 3 appendices

Suspensions of colloidal microplates in contoured 2D elastic fluids sheets are dominated by the bending mechanics and shear rigidity of the plates and the contrasting in-plane shear flow of the 2D fluid. Using the phase separated phospholipid membranes of individual giant unilamellar vesicles as models of contoured 2D suspensions, where solid domains act as colloids in a fluid membrane, we explore bending elasticity-driven assembly. The plate-shaped domains are varied between 1-10 {\mu}m in diameter, with 4-100 plates per vesicle depending on size, contributing a solid area of 17 plus minus 3%. Three classes of reversible plate arrangements evidence inter-plate attractions and repulsions: persistent hexagonal vesicle-encompassing quasi-lattices, persistent closely associated configurations (chains or concentrated lattices), and a dynamic disordered state. The vesicle-encompassing quasi-lattice is stable to vesicle dehydration by 30% relative to an inflated sphere. Excess area or membrane slack, for a fixed composition, dominates the preferred configuration while domain size and number contribute pattern intricacy. Different from the gradual variations in domain interactions and tunable positions in two-colloid systems, multibody interactions vary sharply within a particular range of excess area, producing cooperative assembly reminiscent of a phase transition.

In this work, an extension of the Madrid-2019 force field is presented. We have added the cations Rb + and Cs + and the anions F$^-$, Br$^-$ and I$^-$. These ions were the remaining alkaline and halogen ions not previously considered in the Madrid-2019 force field. The force field, denoted as Madrid-2019-Extended, does not include polarizability, and uses the TIP4P/2005 model of water and scaled charges for the ions. A charge of 0.85 e is assigned to monovalent ions. The force field developed provides an accurate description of the aqueous solution densities over a wide range of concentrations up to the solubility limit of each salt studied. Good predictions of viscosity and diffusion coefficients are obtained for concentrations below 2 m. Structural properties obtained with this force field are also in reasonable agreement with the experiment. The number of contact ion pairs has been controlled to be low so as to avoid precipitation of the system at concentrations close to the experimental solubility limit. A comprehensive comparison of the performance for aqueous solutions of alkaline halides of force fields of electrolytes using scaled and integer charges is now possible. This comparison will help in the future to learn about the benefits and limitations of the use of scaled charges to describe electrolyte solutions.

This work introduces a framework to address the computational complexity inherent in Mixed-Integer Programming (MIP) models by harnessing the potential of deep learning. By employing deep learning, we construct problem-specific heuristics that identify and exploit common structures across MIP instances. We train deep learning models to estimate complicating binary variables for target MIP problem instances. The resulting reduced MIP models are solved using standard off-the-shelf solvers. We present an algorithm for generating synthetic data enhancing the robustness and generalizability of our models across diverse MIP instances. We compare the effectiveness of (a) feed-forward neural networks (ANN) and (b) convolutional neural networks (CNN). To enhance the framework's performance, we employ Bayesian optimization for hyperparameter tuning, aiming to maximize the occurrence of global optimum solutions. We apply this framework to a flow-based facility location allocation MIP formulation that describes long-term investment planning and medium-term tactical scheduling in a personalized medicine supply chain.