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This research uses the implementation of a school suspension ban in Maryland to test whether a top-down state-initiated ban on suspensions in early primary grades can influence school behavior regarding school discipline. Beginning in the fall of 2017, the State of Maryland banned the use of out-of-school suspensions for grades PK-2, unless a student posed an "imminent threat" to staff or students. This research investigates (1) what was the effect of the ban on discipline outcomes for students in both treated grades and upper elementary grades not subject to the ban? (2) did schools bypass the ban by coding more events as threatening or increasing the use of in-school suspensions? and (3) were there differential effects for students in groups that are historically suspended more often? Using a comparative interrupted time series strategy, we find that the ban is associated with a substantial reduction in, but not a total elimination of, out-of-school suspensions for targeted grades without substitution of in-school suspensions. Disproportionalities by race and other characteristics remain after the ban. Grades not subject to the ban experienced few effects, suggesting the ban did not trigger a schoolwide response that reduced exclusionary discipline.

This study investigates the role of college major choices in labor market outcomes, with a focus on racial minorities and immigrants. Drawing upon research on school-to-work linkages, we examine two measures, linkage, the connection between college majors and specific occupations in the labor market, and match, the alignment of workers' occupations with their college majors. Analyzing data from the American Community Survey, 2013-2017, we show that linkage positively predicts earnings, particularly for workers in matched occupations, and negatively predicts unemployment. Notably, Black, Hispanic, and foreign-born workers in matched occupations benefit more from linkage strength than their White and U.S.-born counterparts. This advantage is more pronounced in states that are popular destinations for immigrants. Our findings suggest that earnings and unemployment disparities experienced among racial minorities and immigrants may diminish if they pursue majors closely tied to jobs in the labor market and secure jobs related to their college majors.

We present VLT/MUSE integral-field spectroscopy ($R\approx 1\,800$) of four giant gravitational arcs exhibiting strong C IV absorption at 8 intervening redshifts, $z_{abs}\approx 2.0$--$2.5$. We detect C IV absorption in a total of 222 adjacent and seeing-uncorrelated sightlines, whose spectra sample beams of ("de-lensed") linear size $\approx 1$ kpc. Our data show that (1) absorption velocities cluster at all probed transverse scales, $\Delta r_\perp\approx0$--$15$ kpc, depending on system; (2) the (transverse) velocity dispersion never exceeds the mean (line-of-sight) absorption spread; and (3) the (transverse) velocity autocorrelation function does not resolve kinematic patterns at the above spatial scales, but its velocity projection, $\xi^{arc}(\Delta v)$, exhibits a similar shape to the known two-point correlation function toward quasars, $\xi^{QSO}(\Delta v)$. An empirical kinematic model suggests that these results are a natural consequence of wide-beam observations of an unresolved clumpy medium. Our model recovers both the underlying velocity dispersion of the clumps ($70$--$170$ \kms) and the mean number of clumps per unit area ($2$--$13$ kpc$^{-2}$). The latter constrains the projected mean inter-clump distance to within $\approx0.3$--$0.8$ kpc, which we argue is a measure of clump size for near-unity covering fraction. The model is also able to predict $\xi^{arc}(\Delta v)$ from $\xi^{QSO}(\Delta v)$, suggesting that the strong systems that shape the former and the line-of-sight velocity components that define the latter trace the same kinematic population. Consequently, the clumps must possess an internal density structure that generates both weak and strong components. We discuss how our interpretation is consistent with previous observations using background galaxies and multiple quasars., Comment: Accepted for publication in A&A

Nanostructured high-index dielectrics have shown great promise as low-loss photonic platforms for wavefront control and enhancing optical nonlinearities. However, their potential as optomechanical resonators has remained unexplored. In this work, we investigate the generation and detection of coherent acoustic phonons in individual crystalline gallium phosphide nanodisks on silica in a pump-probe configuration. By pumping the dielectric above its bandgap energy and probing over its transparent region, we observe the radial breathing mode of the disk with an oscillation frequency around 10 GHz. We analyze the performance of nanoantennas of various sizes in the 300-600 nm diameter range at fixed 125 nm height and find that the detection efficiency is maximum near the fundamental anapole state, in agreement with numerical simulations. By comparing with reference gold nanodisk and nanorod plasmonic resonators, we find that the dielectric nanoantennas display a modulation amplitude up to ~5 times larger. We further demonstrate the launching of acoustic waves through the underlaying substrate and the mechanical coupling between two nanostructures placed 3 {\mu}m apart, laying the basis for photonic-phononic signal processing using dielectric nanoantennas.

There is increasing interest in ''decision-focused'' machine learning methods which train models to account for how their predictions are used in downstream optimization problems. Doing so can often improve performance on subsequent decision problems. However, current methods for uncertainty quantification do not incorporate any information at all about downstream decisions. We develop a framework based on conformal prediction to produce prediction sets that account for a downstream decision loss function, making them more appropriate to inform high-stakes decision-making. Our approach harnesses the strengths of conformal methods--modularity, model-agnosticism, and statistical coverage guarantees--while incorporating downstream decisions and user-specified utility functions. We prove that our methods retain standard coverage guarantees. Empirical evaluation across a range of datasets and utility metrics demonstrates that our methods achieve significantly lower decision loss compared to standard conformal methods. Additionally, we present a real-world use case in healthcare diagnosis, where our method effectively incorporates the hierarchical structure of dermatological diseases. It successfully generates sets with coherent diagnostic meaning, aiding the triage process during dermatology diagnosis and illustrating how our method can ground high-stakes decision-making on external domain knowledge.

Agents are a special kind of AI-based software in that they interact in complex environments and have increased potential for emergent behaviour. Explaining such emergent behaviour is key to deploying trustworthy AI, but the increasing complexity and opaque nature of many agent implementations makes this hard. In this work, we propose a Probabilistic Graphical Model along with a pipeline for designing such model -- by which the behaviour of an agent can be deliberated about -- and for computing a robust numerical value for the intentions the agent has at any moment. We contribute measurements that evaluate the interpretability and reliability of explanations provided, and enables explainability questions such as `what do you want to do now?' (e.g. deliver soup) `how do you plan to do it?' (e.g. returning a plan that considers its skills and the world), and `why would you take this action at this state?' (e.g. explaining how that furthers or hinders its own goals). This model can be constructed by taking partial observations of the agent's actions and world states, and we provide an iterative workflow for increasing the proposed measurements through better design and/or pointing out irrational agent behaviour., Comment: 57 pages, 8 figures, 5 tables

Koopman operator theory and Willems' fundamental lemma both can provide (approximated) data-driven linear representation for nonlinear systems. However, choosing lifting functions for the Koopman operator is challenging, and the quality of the data-driven model from Willems' fundamental lemma has no guarantee for general nonlinear systems. In this paper, we extend Willems' fundamental lemma for a class of nonlinear systems that admit a Koopman linear embedding. We first characterize the relationship between the trajectory space of a nonlinear system and that of its Koopman linear embedding. We then prove that the trajectory space of Koopman linear embedding can be formed by a linear combination of rich-enough trajectories from the nonlinear system. Combining these two results leads to a data-driven representation of the nonlinear system, which bypasses the need for the lifting functions and thus eliminates the associated bias errors. Our results illustrate that both the width (more trajectories) and depth (longer trajectories) of the trajectory library are important to ensure the accuracy of the data-driven model.

The SaaS paradigm has popularized the usage of pricings, allowing providers to offer customers a wide range of subscription possibilities. This creates a vast configuration space for users, enabling them to choose the features and support guarantees that best suit their needs. Regardless of the reasons why changes in these pricings are made, the frequency of changes within the elements of pricings continues to increase. Therefore, for those responsible for the development and operation of SaaS, it would be ideal to minimize the time required to transfer changes in SaaS pricing to the software and underlying infrastructure, without compromising the quality and reliability.% of the service; %i.e., this development and operation should be Pricing-Driven. This work explores the support offered by the industry for this need. By modeling over 150 pricings from 30 different SaaS over six years, we reveal that the configuration space grows exponentially with the number of add-ons and linearly with the number of plans. We also evaluate 21 different feature toggling solutions, finding that feature toggling, particularly permission toggles, is a promising technique for enabling rapid adaptation to pricing changes. Our results suggest that developing automated solutions with minimal human intervention could effectively reduce the time-to-market for SaaS updates driven by pricing changes, especially with the adoption of a standard for serializing pricings., Comment: 15 pages. Accepted in the 22nd International Conference on Service-Oriented Computing (ICSOC'24)

Generative Artificial Intelligence (AI) models may carry societal transformation to an extent demanding a delicate balance between opportunity and risk. This manuscript is the first of a series of White Papers informing the development of IEEE-SA's p3995: `Standard for the Implementation of Safeguards, Controls, and Preventive Techniques for Artificial Intelligence (AI) Models', Chair: Marina Cort\^{e}s (https://standards.ieee.org/ieee/3395/11378/). In this first horizon-scanning we identify key attention areas for standards activities in AI. We examine different principles for regulatory efforts, and review notions of accountability, privacy, data rights and mis-use. As a safeguards standard we devote significant attention to the stability of global infrastructures and consider a possible overdependence on cloud computing that may result from densely coupled AI components. We review the recent cascade-failure-like Crowdstrike event in July 2024, as an illustration of potential impacts on critical infrastructures from AI-induced incidents in the (near) future. It is the first of a set of articles intended as White Papers informing the audience on the standard development. Upcoming articles will focus on regulatory initiatives, technology evolution and the role of AI in specific domains., Comment: This is an interim version of our p3395 working group White Paper. We will update this version, until publication by the Institute of Electrical and Electronics Engineers, Standards Association (IEEE-SA), Sponsor Committee - Artificial Intelligence Standards Committee (C/AISC); https://standards.ieee.org/ieee/3395/11378/

It is a truth universally acknowledged, that space charge effects in ultrarelativistic electron storage rings are irrelevant due to the steep inverse dependence of their strength on the Lorentz factor. Yet, with the push towards the diffraction limit, the state-of-the-art light sources are approaching the point where their emittance becomes so small that the space charge force can no longer be ignored. In this paper, we demonstrate how space charge effects affect the injection dynamics, dynamical aperture, and collective beam stability on the example of 4th generation light sources PETRA IV and SOLEIL II.

Control barrier functions (CBFs) play a critical role in the design of safe optimization-based controllers for control-affine systems. Given a CBF associated with a desired ``safe'' set, the typical approach consists in embedding CBF-based constraints into the optimization problem defining the control law to enforce forward invariance of the safe set. While this approach effectively guarantees safety for a given CBF, the CBF-based control law can introduce undesirable equilibrium points (i.e., points that are not equilibria of the original system); open questions remain on how the choice of CBF influences the number and locations of undesirable equilibria and, in general, the dynamics of the closed-loop system. This paper investigates how the choice of CBF impacts the dynamics of the closed-loop system and shows that: (i) The CBF does not affect the number, location, and (local) stability properties of the equilibria in the interior of the safe set; (ii) undesirable equilibria only appear on the boundary of the safe set; and, (iii) the number and location of undesirable equilibria for the closed-loop system do not depend of the choice of the CBF. Additionally, for the well-established safety filters and controllers based on both CBF and control Lyapunov functions (CLFs), we show that the stability properties of equilibria of the closed-loop system are independent of the choice of the CBF and of the associated extended class-K function.

While control barrier functions are employed in addressing safety, control synthesis methods based on them generally rely on accurate system dynamics. This is a critical limitation, since the dynamics of complex systems are often not fully known. Supervised machine learning techniques hold great promise for alleviating this weakness by inferring models from data. We propose a novel control barrier function-based framework for safe control through event-triggered learning, which switches between prioritizing control performance and improving model accuracy based on the uncertainty of the learned model. By updating a Gaussian process model with training points gathered online, the approach guarantees the feasibility of control barrier function conditions with high probability, such that safety can be ensured in a data-efficient manner. Furthermore, we establish the absence of Zeno behavior in the triggering scheme, and extend the algorithm to sampled-data realizations by accounting for inter-sampling effects. The effectiveness of the proposed approach and theory is demonstrated in simulations., Comment: The first two authors contributed equally to the work

The increasing integration of renewable energy resources into power grids has led to time-varying system inertia and consequent degradation in frequency dynamics. A promising solution to alleviate performance degradation is using power electronics interfaced energy resources, such as renewable generators and battery energy storage for primary frequency control, by adjusting their power output set-points in response to frequency deviations. However, designing a frequency controller under time-varying inertia is challenging. Specifically, the stability or optimality of controllers designed for time-invariant systems can be compromised once applied to a time-varying system. We model the frequency dynamics under time-varying inertia as a nonlinear switching system, where the frequency dynamics under each mode are described by the nonlinear swing equations and different modes represent different inertia levels. We identify a key controller structure, named Neural Proportional-Integral (Neural-PI) controller, that guarantees exponential input-to-state stability for each mode. To further improve performance, we present an online event-triggered switching algorithm to select the most suitable controller from a set of Neural-PI controllers, each optimized for specific inertia levels. Simulations on the IEEE 39-bus system validate the effectiveness of the proposed online switching control method with stability guarantees and optimized performance for frequency control under time-varying inertia.

Diffusion-weighted MRI is increasingly used to study the normal and abnormal development of fetal brain in-utero. Recent studies have shown that dMRI can offer invaluable insights into the neurodevelopmental processes in the fetal stage. However, because of the low data quality and rapid brain development, reliable analysis of fetal dMRI data requires dedicated computational methods that are currently unavailable. The lack of automated methods for fast, accurate, and reproducible data analysis has seriously limited our ability to tap the potential of fetal brain dMRI for medical and scientific applications. In this work, we developed and validated a unified computational framework to (1) segment the brain tissue into white matter, cortical/subcortical gray matter, and cerebrospinal fluid, (2) segment 31 distinct white matter tracts, and (3) parcellate the brain's cortex and delineate the deep gray nuclei and white matter structures into 96 anatomically meaningful regions. We utilized a set of manual, semi-automatic, and automatic approaches to annotate 97 fetal brains. Using these labels, we developed and validated a multi-task deep learning method to perform the three computations. Our evaluations show that the new method can accurately carry out all three tasks, achieving a mean Dice similarity coefficient of 0.865 on tissue segmentation, 0.825 on white matter tract segmentation, and 0.819 on parcellation. The proposed method can greatly advance the field of fetal neuroimaging as it can lead to substantial improvements in fetal brain tractography, tract-specific analysis, and structural connectivity assessment.

This paper examines the integration of STEAM (Science, Technology, Engineering, Arts, and Mathematics) into education, emphasizing the inclusion of the Arts to foster creativity alongside traditional STEM skills. STEAM encourages multidisciplinary, student-centered approaches like project-based and inquiry-based learning, promoting real-world problem-solving. However, significant challenges arise in implementing STEAM, particularly for teachers who often lack interdisciplinary training and face rigid school structures. Assessing STEAM outcomes also remains complex. The paper highlights the need for reforms in teacher education to support interdisciplinary teaching, along with addressing "disciplinary egocentrism" in higher education. Despite these challenges, STEAM has shown promise in enhancing student engagement, creativity, and critical thinking. To unlock its full potential, systemic changes in curriculum design, educational practices, and teacher training are essential., Comment: 10 pages

The formation of the massive stars, and in particular, the role that the magnetic fields play in their early evolutionary phase is still far from being completely understood. Here, we present Atacama Large Millimeter/Submillimeter Array (ALMA) 1.2 mm full polarized continuum, and H$^{13}$CO$^+$(3$-$2), CS(5$-$4), and HN$^{13}$C(3$-$2) line observations with a high angular resolution ($\sim$0.4$''$ or 1100 au). In the 1.2 mm continuum emission, we reveal a dusty envelope surrounding the massive protostars, IRAS16547-E and IRAS16547-W, with dimensions of $\sim$10,000 au. This envelope has a bi-conical structure likely carved by the powerful thermal radio jet present in region. The magnetic fields vectors follow very-well the bi-conical envelope. The polarization fraction is $\sim$2.0\% in this region. Some of these vectors seem to converge to IRAS 16547-E, and IRAS 16547-W, the most massive protostars. Moreover, the velocity fields revealed from the spectral lines H$^{13}$CO$^+$(3$-$2), and HN$^{13}$C(3$-$2) show velocity gradients with a good correspondence with the magnetic fields, that maybe are tracing the cavities of molecular outflows or maybe in some parts infall. We derived a magnetic field strength in some filamentary regions that goes from 2 to 6.1\,mG. We also find that the CS(5$-$4) molecular line emission reveals multiple outflow cavities or bow-shocks with different orientations, some of which seem to follow the NW-SE radio thermal jet., Comment: Accepted by the Astrophysical Journal, 13 pages

Haldane's seminal work established two fundamentally different types of excitation spectra for antiferromagnetic Heisenberg quantum spin chains: gapped excitations in integer-spin chains and gapless excitations in half-integer-spin chains. In finite-length half-integer spin chains, quantization, however, induces a gap in the excitation spectrum, with the upper bound given by the Lieb-Schulz-Mattis (LSM) theorem. Here, we investigate the length-dependent excitations in spin-1/2 Heisenberg chains obtained by covalently linking olympicenes--Olympic rings shaped nanographenes carrying spin-1/2--into one-dimensional chains. The large exchange interaction (J~38 mV) between olympicenes and the negligible magnetic anisotropy in these nanographenes make them an ideal platform for studying quantum spin excitations, which we directly measure using inelastic electron tunneling spectroscopy. We observe a power-law decay of the lowest excitation energy with increasing chain length L, remaining below the LSM boundary. In a long chain with L = 50, a nearly V-shaped excitation continuum is observed, reinforcing the system's gapless nature in the thermodynamic limit. Finally, we visualize the standing wave of a single spinon confined in odd-numbered chains using low-bias current maps. Our results provide compelling evidence for the realization of a one-dimensional analog of a gapless spin liquid., Comment: 5 figures. arXiv admin note: text overlap with arXiv:2402.13590

This paper proposes a control design approach for stabilizing nonlinear control systems. Our key observation is that the set of points where the decrease condition of a control Lyapunov function (CLF) is feasible can be regarded as a safe set. By leveraging a nonsmooth version of control barrier functions (CBFs) and a weaker notion of CLF, we develop a control design that forces the system to converge to and remain in the region where the CLF decrease condition is feasible. We characterize the conditions under which our controller asymptotically stabilizes the origin or a small neighborhood around it, even in the cases where it is discontinuous. We illustrate our design in various examples.

The PETRA IV project for upgrading the 2.3 km 6 GeV PETRA III storage ring to a diffraction-limited synchrotron radiation source is nearing the end of its detailed technical design phase. We present the ring lattice based on the hybrid six-bend achromat (H6BA) cell and a detailed evaluation of its beam dynamics performance. Design challenges as well as unique opportunities associated with a low emittance ring of a large size are discussed.

In the non-metric gravity proposed by K. Krasnov, this is a theory in which the scalar constraint of the Ashtekar's formalism is modified in such way that the cosmological constant is replaced by a cosmological function that depends of the canonical variables $A_{a}{}^{i}$ and $E_{i}{}^{a}$, the General Relativity (GR) is the particular case when the cosmological function is a constant. Some years ago inspired by this theory Rosas-Rodr\'iguez proposed two cosmological functions, one for the Ashtekar's formalism and the other for the ADM formalism. In this paper we show that this cosmological functions are related thought the three-dimensional Ricci scalar.

Additive manufacturing holds more potential to enable the development of ceramic-based components. Ceramics offer high resistance to heat, high fracture toughness, and are extremely corrosion resistant. Thus, ceramics are widely used in sectors such as the aerospace industry, automotive, microelectronics, and biomedicine. Using various additive manufacturing platforms, ceramics with complex and uniquely designed geometry can be developed to suit specific applications. This project aims at innovating high-temperature thermocouples by embedding conductive metal pastes into a ceramic structure. The paste used includes tungsten, molybdenum, and antimony. The metal pastes are precisely extruded into a T-shaped trench inside the ceramic matrix. Following specific temperature ranges, the ceramic matrix is sintered to improve the properties of the material. The sensors produced can function at extremely high temperatures and are thereby suitable for high-temperature environments. Comparative testing of the 3D sintered sensors with conventional temperature sensors shows high correlation between the two classes of sensors. The resulting R-squared value of 0.9885 is satisfactory which implies the reliability and accuracy of 3D sintering sensors are satisfactory in temperature sensing applications., Comment: 12 pages, 5 figures

Koopman operator theory offers a rigorous treatment of dynamics and has been emerging as a powerful modeling and learning-based control method enabling significant advancements across various domains of robotics. Due to its ability to represent nonlinear dynamics as a linear operator, Koopman theory offers a fresh lens through which to understand and tackle the modeling and control of complex robotic systems. Moreover, it enables incremental updates and is computationally inexpensive making it particularly appealing for real-time applications and online active learning. This review comprehensively presents recent research results on advancing Koopman operator theory across diverse domains of robotics, encompassing aerial, legged, wheeled, underwater, soft, and manipulator robotics. Furthermore, it offers practical tutorials to help new users get started as well as a treatise of more advanced topics leading to an outlook on future directions and open research questions. Taken together, these provide insights into the potential evolution of Koopman theory as applied to the field of robotics.

Many ligands commonly used to prepare nanoparticle catalysts with precise nanoscale features contain nitrogen (e.g., oleylamine); here, we found that the use of nitrogen-containing ligands during the synthesis of metal oxide nanoparticle catalysts substantially impacted product analysis during photocatalytic studies. We confirmed these experimental results via hybrid Density Functional Theory computations of the materials' electronic properties to evaluate their viability as photocatalysts for nitrogen reduction. This nitrogen ligand contamination, and subsequent interference in photocatalytic studies, is avoidable through the careful design of synthetic pathways that exclude nitrogen-containing constituents. This result highlights the urgent need for careful evaluation of catalyst synthesis protocols, as contamination by nitrogen-containing ligands may go unnoticed since the presence of nitrogen is often not detected or probed., Comment: 13 pages, 3 figures

This paper studies the dynamical properties of closed-loop systems obtained from control barrier function-based safety filters. We provide a sufficient and necessary condition for the existence of undesirable equilibria and show that the Jacobian matrix of the closed-loop system evaluated at an undesirable equilibrium always has a nonpositive eigenvalue. In the special case of linear planar systems and ellipsoidal obstacles, we give a complete characterization of the dynamical properties of the corresponding closed-loop system. We show that for underactuated systems, the safety filter always introduces a single undesirable equilibrium, which is a saddle-point. We prove that all trajectories outside the global stable manifold of such equilibrium converge to the origin. In the fully actuated case, we discuss how the choice of nominal controller affects the stability properties of the closed-loop system. Various simulations illustrate our results.

The $^{246}$Cm(n,$\gamma$) and $^{248}$Cm(n,$\gamma$) cross-sections have been measured at the Experimental Area 2 (EAR2) of the n_TOF facility at CERN with three C$_6$D$_6$ detectors. This measurement is part of a collective effort to improve the capture cross-section data for Minor Actinides (MAs), which are required to estimate the production and transmutation rates of these isotopes in light water reactors and innovative reactor systems. In particular, the neutron capture in $^{246}$Cm and $^{248}$Cm open the path for the formation of other Cm isotopes and heavier elements such as Bk and Cf and the knowledge of (n,$\gamma$) cross-sections of these Cm isotopes plays an important role in the transport, transmutation and storage of the spent nuclear fuel. The reactions $^{246}$Cm(n,$\gamma$) and $^{248}$Cm(n,$\gamma$) have been the two first capture measurements analyzed at n_TOF EAR2. Until this experiment and two recent measurements performed at J-PARC, there was only one set of data of the capture cross-sections of $^{246}$Cm and $^{248}$Cm, that was obtained in 1969 in an underground nuclear explosion experiment. In the measurement at n_TOF a total of 13 resonances of $^{246}$Cm between 4 and 400 eV and 5 of $^{248}$Cm between 7 and 100 eV have been identified and fitted. The radiative kernels obtained for $^{246}$Cm are compatible with JENDL-5, but some of them are not with JENDL-4, which has been adopted by JEFF-3.3 and ENDF/B-VIII.0. The radiative kernels obtained for the first three $^{248}$Cm resonances are compatible with JENDL-5, however, the other two are not compatible with any other evaluation and are 20% and 60% larger than JENDL-5.

The ESO public survey VISTA Variables in the V\'ia L\'actea (VVV) surveyed the inner Galactic bulge and the adjacent southern Galactic disk from $2009-2015$. Upon its conclusion, the complementary VVV eXtended (VVVX) survey has expanded both the temporal as well as spatial coverage of the original VVV area, widening it from $562$ to $1700$ sq. deg., as well as providing additional epochs in $JHK_{\rm s}$ filters from $2016-2023$. With the completion of VVVX observations during the first semester of 2023, we present here the observing strategy, a description of data quality and access, and the legacy of VVVX. VVVX took $\sim 2000$ hours, covering about 4% of the sky in the bulge and southern disk. VVVX covered most of the gaps left between the VVV and the VISTA Hemisphere Survey (VHS) areas and extended the VVV time baseline in the obscured regions affected by high extinction and hence hidden from optical observations. VVVX provides a deep $JHK_{\rm s}$ catalogue of $\gtrsim 1.5\times10^9$ point sources, as well as a $K_{\rm s}$ band catalogue of $\sim 10^7$ variable sources. Within the existing VVV area, we produced a $5D$ map of the surveyed region by combining positions, distances, and proper motions of well-understood distance indicators such as red clump stars, RR Lyrae, and Cepheid variables. In March 2023 we successfully finished the VVVX survey observations that started in 2016, an accomplishment for ESO Paranal Observatory upon 4200 hours of observations for VVV+VVVX. The VVV+VVVX catalogues complement those from the Gaia mission at low Galactic latitudes and provide spectroscopic targets for the forthcoming ESO high-multiplex spectrographs MOONS and 4MOST., Comment: 17 pages, 11 figures (+ appendix). Accepted for publication in Astronomy and Astrophysics in section 14: Catalogs and data

Newcomer programs support recent immigrant, English learner students beyond what is typically offered in the traditional English learner classroom by providing students with innovative teaching methods and nonacademic support. In Houston ISD, Liberty High School is a separate-site program that serves high school-aged and older newcomer and immigrant students. To accommodate older students' job schedules, Liberty offers both day and night programs in which students can earn their high school diploma. Given the growing number of adolescent newcomer students in Houston ISD, it is important to understand how recent immigrant, English learner students choose newcomer programs and schools. Using 12 years of administrative data, this research brief describes which student characteristics predict enrollment at Liberty High School. Results show that economically disadvantaged students, students from Central America and Mexico, students who lived closer to the school, and students who lived in neighborhoods with higher concentrations of immigrants were more likely to enroll.

Newcomer programs aim to serve newly arrived immigrant students by providing specialized instruction and nonacademic support beyond what is offered in traditional English learner classrooms. In Houston ISD, Las Americas is a standalone program that serves newcomer students in grades 4-8. Given the growth of newly arrived immigrant students in the district, it is important to understand what characteristics predict whether students and families choose to enroll in a newcomer program. An analysis of 12 years of administrative data showed that economically disadvantaged students, students from sub-Saharan Africa and Central America, students with lower levels of oral English proficiency, and students who lived close to the school were most likely to enroll at Las Americas. Additionally, results suggest that the school's outreach and recruitment strategies were associated with enrollment. Finally, the implementation of the school's grade level expansion and school busing policy both had positive impacts on enrollment.

Given a module $X$ and a regular cardinal $\kappa$ we study various notions of $(\kappa,\mathrm{Add}(X))$-freeness and $(\kappa,\mathrm{Add}(X))$-separability. Bearing on appropriate set-theoretic assumptions, we construct a non-trivial $\kappa^+$-generated, $(\kappa^+,\mathrm{Add}(X))$-free and $(\kappa^+,\mathrm{Add}(X))$-separable module. Our construction allows $\kappa$ to be singular thus extending \cite[Theorem~4.7]{CortesGuilTorrecillas}. Bearing on similar set-theoretic assumptions, we characterize when every module $X$ has a perfect decomposition. As a subproduct we show that Enoch's conjecture for classes $\mathrm{Add}(X)$ is consistent with ZFC -- a fact first proved by \v{S}aroch \cite{Saroch}.

- Aims: We intended to quantify the impact of stellar multiplicity on the presence and properties of exoplanets. - Methods: We investigated all exoplanet host stars at less than 100 pc using the latest astrometric data from Gaia DR3 and advanced statistical methodologies. We complemented our search for common proper motion and parallax companions with data from the Washington Double Star catalogue and the literature. After excluding a number of systems based on radial velocity data, and membership in clusters and open associations, or with resolved ultracool companions, we kept 215 exoplanet host stars in 212 multiple-star systems. - Results: We found 17 new companions in the systems of 15 known exoplanet host stars, measured precise angular and projected physical separations and position angles for 236 pairs of stars, compiled key parameters for 276 planets in multiple systems, and established a comparison sample comprising 687 single stars with exoplanets. With all of this, we statistically analysed a series of hypothesis regarding planets in multiple stellar systems. Although they are only statistically significant at a 2{\sigma} level, our analysis pointed to several interesting results on the comparison in the mean number of planets in multiple versus single stellar systems and the tendency of high mass planets to be located in closer orbits in multiple systems. We confirm that planets in multiple systems tend to have orbits with larger eccentricities than those in single systems. In particular, we found a significant (> 4{\sigma}) preference for planets to exhibit high orbital eccentricities at small ratios between star-star projected physical separations and star-planet semi-major axes., Comment: Accepted in A&A. 47 Pages, 14 figures and 9 tables (4 tables online)

We present the abundances of magnesium (Mg) and silicon (Si) for 314 dwarf stars with spectral types in the interval K7.0-M5.5 (Teff range ~4200-3050 K) observed with the CARMENES high-resolution spectrograph at the 3.5 m telescope at the Calar Alto Observatory. Our analysis employs the BT-Settl model atmospheres, the radiative transfer code Turbospectrum, and a state-of-the-art selection of atomic and molecular data. These Mg and Si abundances are critical for understanding both the chemical evolution and assembly of the Milky Way and the formation and composition of rocky planets. Our chemical abundances show a line-to-line scatter at the level of 0.1 dex for all studied spectral types. The typical error bar of our chemical abundance measurements is +- 0.11 dex (Mg) and +- 0.16 dex (Si) for all spectral types based on the comparison of the results obtained for stellar components of multiple systems. The derived abundances are consistent with the galactic evolution trends and observed chemical abundance distribution of earlier FGK-type stars in the solar neighbourhood. Besides, our analysis provides compatible abundances for stars in multiple systems. In addition, we studied the abundances of different galactic stellar populations. In this paper, we also explore the relation of the Mg and Si abundances of stars with and without known planets., Comment: 11 Pages, 5 figures. Accepted for publication in A&A

We present a study connecting the physical properties of protostellar envelopes to the morphology of the envelope-scale magnetic field. We use the ALMA polarization observations of 55 young prtostars at 0.87 mm on $\sim400-3000$ au scales from the {\em B}-field Orion Protostellar Survey (BOPS) to infer the envelope-scale magnetic field and both dust and gas emission on comparable scales to measure the envelope properties. We find that the protostellar envelopes with compact polarized dust emission tend to have lower envelope masses, than the sources with more extended envelopes. We also find that protostars showing hourglass-field morphologies tend to have lower velocity dispersions in their envelopes, whereas systems with spiral-field morphologies have higher velocity dispersion. Combining with the disk properties taken from the Orion VLA/ALMA Nascent Disk and Multiplicity (VANDAM) survey, we connect envelope properties to fragmentation. Our results suggest that envelope mass may not correlate with fragmentation, whereas turbulence appears to promote fragmentation. On the other hand, we find that fragmentation is suppressed in systems with pinched magnetic fields, suggesting that the magnetic field play a role on providing additional support against gravitational collapse, and the formation of an hourglass-like field may coincide with enhanced magnetic braking that removes angular momentum and hinders the formation of embedded disks. Nevertheless, significant misalignment between magnetic field and outflow axes tends to reduce magnetic braking, leading to the formation of larger disks., Comment: 18 pages, 6 figures, submitted to ApJ

Non-reciprocal interactions are ubiquitous in nature, and in Physics this realization has started to push boundaries by making non-hermiticity a fundamental rather than exceptional property. Despite the prevalence of evanescent coupling in physics, little attention has been paid to wavefunction profiles, with reciprocity often assumed for practical reasons. Our work challenges this assumption by demonstrating the origin of non-reciprocity in a photonic platform. We experimentally validate non-reciprocal dynamics on directional couplers fabricated via femtosecond laser writing, and corroborate our findings through continuous simulations. Extending these insights, we observe the topological Non-Hermitian Skin Effect in a Rice-Mele lattice model. Our findings open new avenues of research using simple and scalable configurations, and potentially guiding future developments in Physics and beyond., Comment: 17 pages, 3 figures

The contribution of the magnetic field to the formation of high-mass stars is poorly understood. We report the high-angular resolution ($\sim0.3^{\prime\prime}$, 870 au) map of the magnetic field projected on the plane of the sky (B$_\mathrm{POS}$) towards the high-mass star forming region G333.46$-$0.16 (G333), obtained with the Atacama Large Millimeter/submillimeter Array (ALMA) at 1.2 mm as part of the Magnetic Fields in Massive Star-forming Regions (MagMaR) survey. The B$_\mathrm{POS}$ morphology found in this region is consistent with a canonical ``hourglass'' which suggest a dynamically important field. This region is fragmented into two protostars separated by $\sim1740$ au. Interestingly, by analysing H$^{13}$CO$^{+}$ ($J=3-2$) line emission, we find no velocity gradient over the extend of the continuum which is consistent with a strong field. We model the B$_\mathrm{POS}$, obtaining a marginally supercritical mass-to-flux ratio of 1.43, suggesting an initially strongly magnetized environment. Based on the Davis-Chandrasekhar-Fermi method, the magnetic field strength towards G333 is estimated to be 5.7 mG. The absence of strong rotation and outflows towards the central region of G333 suggests strong magnetic braking, consistent with a highly magnetized environment. Our study shows that despite being a strong regulator, the magnetic energy fails to prevent the process of fragmentation, as revealed by the formation of the two protostars in the central region.

Water is a fundamental component of life, playing a critical role in regulating metabolic processes and facilitating the dissolution and transport of essential molecules. However, the presence of emerging contaminants, such as pharmaceuticals, poses significant challenges to water quality and safety. Nanomaterials-based technologies arise as a promising tool to remove those contaminants from water. Nevertheless, interfacial water plays a major role in the adsorption of chemical compounds in the nanomaterials - as it plays in biological processes such as protein folding, enzyme activity, and drug delivery. To understand this role, in this study we employ Molecular Dynamics (MD) simulations to explore the adsorption dynamics of potassium diclofenac (K-DCF) on single-walled (SWCNT) and double-walled (DWCNT) carbon nanotubes, considering both dry and wet conditions. Our findings reveal that the structuring of water molecules around CNTs creates hydration layers that significantly influence the accessibility of active sites and the interaction strength between contaminants and adsorbents. Our analysis indicates higher energy barriers for adsorption in DWCNTs compared to SWCNTs, which is attributed to stronger water-surface interactions. This research highlights the importance of understanding nanoscale water behavior for optimizing the design and functionality of nanomaterials for water purification. These findings can guide the development of more efficient and selective nanomaterials, enhancing contaminant removal and ensuring safer water resources, while also contributing to a deeper understanding of fundamental biological interactions.

We continue the systematic study of left-invariant generalised Einstein metrics on Lie groups initiated in arXiv:2206.01157. Our approach is based on a new reformulation of the corresponding algebraic system. For a fixed Lie algebra $\mathfrak{g}$, the unknowns of the system consist of a scalar product $g$ and a $3$-form $H$ on $\mathfrak{g}$ as well as a linear form $\delta$ on $\mathfrak{g}\oplus\mathfrak{g}^*$. As in arXiv:2206.01157, the Lie bracket of $\mathfrak{g}$ is considered part of the unknowns. In the Riemannian case, we show that the generalised Einstein condition always reduces to the commutator ideal and we provide a full classification of solvable generalised Einstein Lie groups. In the Lorentzian case, under the additional assumption $\delta=0$, we classify -- up to one case -- all almost Abelian generalised Einstein Lie groups. We then particularize to four dimensions and provide a full classification of generalised Einstein Riemannian Lie groups as well as generalised Einstein Lorentzian Lie groups with $\delta =0$ and non-degenerate commutator ideal., Comment: 58 pages

We introduce Annealed Multiple Choice Learning (aMCL) which combines simulated annealing with MCL. MCL is a learning framework handling ambiguous tasks by predicting a small set of plausible hypotheses. These hypotheses are trained using the Winner-takes-all (WTA) scheme, which promotes the diversity of the predictions. However, this scheme may converge toward an arbitrarily suboptimal local minimum, due to the greedy nature of WTA. We overcome this limitation using annealing, which enhances the exploration of the hypothesis space during training. We leverage insights from statistical physics and information theory to provide a detailed description of the model training trajectory. Additionally, we validate our algorithm by extensive experiments on synthetic datasets, on the standard UCI benchmark, and on speech separation.

Heat management in devices is a key to their efficiency and longevity. Here, thermal switches (TS) are of great importance because of their ability to transition between different thermal conductivity $\kappa$ states. While traditional TS are bulky and slow, recent experiments have suggested "smart" responsive (bio--inspired) polymers as their fast alternatives. One example is poly(N--isopropylacrylamide) (PNIPAM) in water, where $\kappa$ drops suddenly around a temperature $T_{\ell} \simeq 305$ K when a PNIPAM undergoes a coil--to--globule transition. At a first glance, this may suggest that the change in polymer conformation has a direct influence on TS. However, it may be presumptuous to trivially "only" link conformations with TS, especially because many complex microscopic details control macroscopic conformational transition. Motivated by this, we study TS in "smart" polymers using generic simulations. As the test cases, we investigate two different modes of polymer collapse using external stimuli, i.e., changing $T$ and cosolvent mole fraction $x_{\rm c}$. Collapse upon increasing $T$ shows a direct correlation between the conformation and $\kappa$ switching, while no correlation is observed in the latter case. These results suggest that the (co--)solvent--monomer interactions play a greater important role than the exact conformation in dictating TS. While some results are compared with the available experiments, possible future directions are also highlighted.

The growth of quantum technologies is attracting the interest of many students eager to learn concepts such as quantum entanglement or quantum superposition. However, the non-intuitive nature of these concepts poses a challenge to understanding them. Here, we present an entangled photon system which can perform a Bell test, i.e. the CHSH inequality, and can obtain the complete tomography of the two-photon state. The proposed setup is versatile, cost-effective and allows for multiple classroom operating modes. We present two variants, both facilitating the measurement of Bell inequalities and quantum state tomography. Experimental results showcase successful manipulation of the quantum state of the photons, achieving high-fidelity entangled states and significant violations of Bell's inequalities. Our setup's simplicity and affordability enhances accessibility for less specialized laboratories, allowing students to familiarize themselves with quantum physics concepts.

We show that Hawking black-hole evaporation saturates the Landauer Principle of information thermodynamics. Our result implies that information loss experienced by a black hole during Hawking evaporation takes place as efficiently as possible. We also extend the analysis to the case of Barrow entropy as a phenomenological realization of a fractal event horizon, where the Landauer Principle informs amongst different options for the black hole temperature. To our knowledge, this work is the first identification of the two results as expressions of the same process., Comment: 4 pages. Title modified, additional discussion and references

We employ the recent performance-barrier event-triggered control (P-ETC) for achieving global exponential convergence of a class of reaction-diffusion PDEs via PDE backstepping control. Rather than insisting on a strictly monotonic decrease of the Lyapunov function for the closed-loop system, P-ETC allows the Lyapunov function to increase as long as it remains below an acceptable performance-barrier. This approach integrates a performance residual, the difference between the value of the performance-barrier and the Lyapunov function, into the triggering mechanism. The integration adds flexibility and results in fewer control updates than with regular ETC (R-ETC) that demands a monotonic decrease of the Lyapunov function. Our P-ETC PDE backstepping design ensures global exponential convergence of the closed-loop system in the spatial L^2 norm, without encountering Zeno phenomenon. To avoid continuous monitoring of the triggering function that generates events, we develop periodic event-triggered and self-triggered variants (P-PETC and P-STC, respectively) of the P-ETC. The P-PETC only requires periodic evaluation of the triggering function whereas the P-STC preemptively computes the time of the next event at the current event time using the system model and continuously available system states. The P-PETC and P-STC also ensure a Zeno-free behavior and deliver performance equivalent to that of the continuous-time P-ETC which requires continuous evaluation of the triggering function, in addition to the continuous sensing of the state. We provide numerical simulations to illustrate the proposed technique and to compare it with R-ETC associated with strictly decreasing Lyapunov functions.

We present a detailed study of cardinality-aware top-$k$ classification, a novel approach that aims to learn an accurate top-$k$ set predictor while maintaining a low cardinality. We introduce a new target loss function tailored to this setting that accounts for both the classification error and the cardinality of the set predicted. To optimize this loss function, we propose two families of surrogate losses: cost-sensitive comp-sum losses and cost-sensitive constrained losses. Minimizing these loss functions leads to new cardinality-aware algorithms that we describe in detail in the case of both top-$k$ and threshold-based classifiers. We establish $H$-consistency bounds for our cardinality-aware surrogate loss functions, thereby providing a strong theoretical foundation for our algorithms. We report the results of extensive experiments on CIFAR-10, CIFAR-100, ImageNet, and SVHN datasets demonstrating the effectiveness and benefits of our cardinality-aware algorithms., Comment: arXiv admin note: substantial text overlap with arXiv:2403.19625

Nowadays, the new network architectures with respect to the traditional network topologies must manage more data, which entails having increasingly robust and scalable network structures. As there is a process of growth, adaptability, and change in traditional data networks, faced with the management of large volumes of information, it is necessary to incorporate the virtualization of network functions in the context of information content networks, in such a way that there is a balance between the user and the provider at cost level and profit, the functions on the network. In turn, NFVs (Network Functions Virtualization) are considered network structures designed based on IT virtualization technologies, which allow virtualizing of the functions that can be found in the network nodes, which are connected through routing tables, which allows offering communication services for various types of customers. Therefore, information-centric networks (IC, unlike traditional data networks which proceed to exchange information between hosts using data packets and TCP/IP communication protocols, use the content of the data for this purpose where the data travels through the network is stored in a routing table located in the CR (Content Router) of the router temporality to be reused later, which allows for reducing operation costs and capital costs . The purpose of this work is to analyze how the virtualization of network functions is integrated into the field of information-centric networks. Also, the advantages and disadvantages of both architectures are considered and presented as a critical analysis when considering the current difficulties and future trends of both network topologies., Comment: 7 pages,7 figures, conference paper, index in Scopus

We studied the frequency and quality factor of mechanical plasmonic nanoresonators as a function of temperature, ranging from ambient to 4 K. Our investigation focused on individual gold nanorods and nanodisks of various sizes. We observed that oscillation frequencies increase linearly as temperature decreases until saturation is reached at cryogenic temperatures. This behavior is explained by the temperature dependence of the elastic modulus, with a Debye temperature compatible with reported bulk values for gold. To describe the behavior of the quality factor, we developed a model considering the nanostructures as anelastic solids, identifying a dissipation peak around 150 K due to a thermally activated process, likely of the Niblett-Wilks mechanism type. Importantly, our findings suggest that external dissipation factors are more critical to improving quality factors than internal friction, which can be increased by modifying the nanoresonator's environment. Our results enable the design of structures with high vibration frequencies and quality factors by effectively controlling external losses., Comment: Main text and supporting information, 18 pages, 6 figures

The calcium isotopes are an ideal system to investigate the evolution of shell structure and magic numbers. Although the properties of surface nucleons in calcium have been well studied, probing the structure of deeply bound nucleons remains a challenge. Here, we report on the first measurement of unbound states in $^{53}$Ca and $^{55}$Ca, populated from \ts{54,56}Ca($p,pn$) reactions at a beam energy of around 216 MeV/nucleon at the RIKEN Radioactive Isotopes Beam Factory. The resonance properties, partial cross sections, and momentum distributions of these unbound states were analyzed. Orbital angular momentum $l$ assignments were extracted from momentum distributions based on calculations using the distorted wave impulse approximation (DWIA) reaction model. The resonances at excitation energies of 5516(41)\,keV in $^{53}$Ca and 6000(250)\,keV in $^{55}$Ca indicate a significant $l$\, =\,3 component, providing the first experimental evidence for the $\nu 0f_{7/2}$ single-particle strength of unbound hole states in the neutron-rich Ca isotopes. The observed excitation energies and cross-sections point towards extremely localized and well separated strength distributions, with some fragmentation for the $\nu 0f_{7/2}$ orbital in $^{55}$Ca. These results are in good agreement with predictions from shell-model calculations using the effective GXPF1Bs interaction and \textit{ab initio} calculations and diverge markedly from the experimental distributions in the nickel isotones at $Z=28$., Comment: 13 pages, 7 figures