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Hot-wire directed energy deposition using a laser beam (DED-LB/w) is a method of metal additive manufacturing (AM) that has benefits of high material utilization and deposition rate, but parts manufactured by DED-LB/w suffer from a substantial heat input and undesired surface finish. Hence, monitoring and controlling the process parameters and signatures during the deposition is crucial to ensure the quality of final part properties and geometries. This paper explores the dynamic modeling of the DED-LB/w process and introduces a parameter-signature-property modeling and control approach to enhance the quality of modeling and control of part properties that cannot be measured in situ. The study investigates different process parameters that influence the melt pool width (signature) and bead width (property) in single and multi-layer beads. The proposed modeling approach utilizes a parameter-signature model as F_1 and a signature-property model as F_2. Linear and nonlinear modeling approaches are compared to describe a dynamic relationship between process parameters and a process signature, the melt pool width (F_1). A fully connected artificial neural network is employed to model and predict the final part property, i.e., bead width, based on melt pool signatures (F_2). Finally, the effectiveness and usefulness of the proposed parameter-signature-property modeling is tested and verified by integrating the parameter-signature (F_1) and signature-property (F_2) models in the closed-loop control of the width of the part. Compared with the control loop with only F_1, the proposed method shows clear advantages and bears potential to be applied to control other part properties that cannot be directly measured or monitored in situ., Comment: 28 pages, 14 figures, 4 tables

Binary mixtures of water with lower alcohols display non-linear phase behaviour upon mixing which are attributed to potential cluster formation at molecular level. Unravelling such elusive structures requires the investigation of hydrogen-bonding sub-nanosecond dynamics. We employ high-resolution neutron time-of-flight spectroscopy with polarization analysis in combination with selective deuteration to study the concentration-dependent structural dynamics, in the water rich part of the phase diagram of water-ethanol mixtures. This method enables the simultaneous access to atomic correlations in space and time, and allows us to separate spatially incoherent scattering probing self-diffusion of the ethanol fraction from the coherent scattering probing collective diffusion of the water network as a whole. Our observations indicate an enhanced rigidity of the hydrogen bond network at mesoscopic lengthscale compared to the intra-molecular scale as the ethanol fraction increases, which is consistent with the hypothesis of clusters.

We present an inelastic neutron scattering study of the crystal electric field levels in the intermetallic ferrimagnets RECo$_{5}$ (RE = Nd and Y). In NdCo$_{5}$, measurements at $5~$K reveal two levels at approximately 28.9 and 52.9 meV. Crystal field calculations including the exchange field $B_{\textrm{exc}}$ from the Co sites account for both of these, as well as the spectrum at temperatures above the spin-reorientation transition at $\sim 280$~K. In particular, it is found that both a large hexagonal crystal field parameter $A_{6}^6\langle r^6 \rangle$ and $B_{\textrm{exc}}$ are required to reproduce the data, with the latter having a much larger value than that deduced from previous computational and experimental studies. Our study sheds light on the delicate interplay of terms in the rare-earth Hamiltonian of RECo$_5$ systems, and is therefore expected to stimulate further experimental and computational work on the broader family of rare-earth permanent magnets.

Motivated by the classical spin-nematic state observed in the breathing pyrochlore spinel LiGa$_{0.95}$In$_{0.05}$Cr$_4$O$_8$, we theoretically discuss spin dynamics in models of spin-lattice coupling in these materials. Semiclassical dynamical simulations successfully recover the key features of inelastic neutron-scattering experiments on LiGa$_{0.95}$In$_{0.05}$Cr$_4$O$_8$: a broad finite-energy peak alongside a continuum of scattering near the (200) wave vector that extends from the elastic line to high energies. To interpret this result, we develop a small-fluctuation theory for the spin-ice-like nematic ground states, analogous to linear spin-wave theory for conventionally ordered magnets, which reproduces the numerical simulation results quantitatively. In particular, we find that the inelastic peak is well explained by collective modes confined to ferromagnetic loops of the underlying nematic order. In addition, we find a sharp, linearly dispersing mode in the dynamical structure factor, which originates in long-wavelength fluctuations of the nematic director: We believe identifying this mode will be an interesting target for future experiments on these materials. We also outline potential future applications of our methods to both pyrochlore spinels and other spin-nematic systems., Comment: 14 pages, 11 figures

Much HCI research on prompting prosocial behaviors focuses on methods for increasing empathy. However, increased empathy may have unintended negative consequences. Our work offers an alternative solution that encourages critical reflection for nurturing compassion, which involves motivation and action to help others. In a between-subject experiment, participants (N=60) viewed a climate change documentary while receiving no prompts (CON), reflective prompts to focus on their emotions (RE) or surprises (RS). State compassion, critical reflection, and motivation to act or learn were measured at the end of the session (post-video) and two weeks later (follow-up). Despite participants' condition not affecting compassion, critical reflection was positively correlated with post-video state compassion. RE and RS participants demonstrated deeper reflection and reported higher motivation to learn post-video, and more prosocial behavioral changes during follow-up. RS participants reported better follow-up recall than RE participants. We conclude by discussing implications on designing technology to support compassion and longer-term critical reflection., Comment: 20 pages, 5 figures, ACM CHI 2023

A recent line of work on VC set systems in minor-free (undirected) graphs, starting from Li and Parter, who constructed a new VC set system for planar graphs, has given surprising algorithmic results. In this work, we initialize a more systematic study of VC set systems for minor-free graphs and their applications in both undirected graphs and directed graphs (a.k.a digraphs). More precisely: - We propose a new variant of Li-Parter set system for undirected graphs. - We extend our set system to $K_h$-minor-free digraphs and show that its VC dimension is $O(h^2)$. - We show that the system of directed balls in minor-free digraphs has VC dimension at most $h-1$. - On the negative side, we show that VC set system constructed from shortest path trees of planar digraphs does not have a bounded VC dimension. The highlight of our work is the results for digraphs, as we are not aware of known algorithmic work on constructing and exploiting VC set systems for digraphs., Comment: Fix typos and several minor issues; abstract shorten due to Arxiv limits. Extended abstract appeared in SODA24

This paper investigates the self-cleansing performance of an airlift pump with a u-bend. For this purpose, an experimental test model is used to assess the effect of air supply on the pump's ability to lift water and remove particles under different submergence ratios and particle concentrations. In addition, a simple yet accurate fluid mechanical model is used to rationalize the experiments with individual particles, and to predict the critical water velocity required for removal from the pipe bend. Our experimental results show that the airlift pump is self-cleansing for particle concentrations corresponding to as much as 70% of the cross-sectional area in the u-bend. Furthermore, the self-cleansing ability is relatively independent of the submergence ratio and almost entirely determined by the shear stress. However, the submergence ratio strongly affects energy use, and we find that submergence ratios around 0.75 provide a good compromise between energy use and particle removal efficiency.

Given a simple $n$-vertex, $m$-edge graph $G$ undergoing edge insertions and deletions, we give two new fully dynamic algorithms for exactly maintaining the edge connectivity of $G$ in $\tilde{O}(n)$ worst-case update time and $\tilde{O}(m^{1-1/31})$ amortized update time, respectively. Prior to our work, all dynamic edge connectivity algorithms either assumed bounded edge connectivity, guaranteed approximate solutions, or were restricted to edge insertions only. Our results provide an affirmative answer to an open question posed by Thorup [Combinatorica'07]., Comment: corrected the runtime of the algorithm based on expander decompositions

The A-site ordered chromate spinels LiGa1-xInxCr4O8 host a network of size-alternating spin-3/2 Cr3+ tetrahedra known as a 'breathing' pyrochlore lattice. For the x=0.05 composition, the complex magneto-structural ordering observed in the parent x=0 material is replaced by a single transition at Tf=11 K, ascribed to the collinear nematic order caused by strong spin-lattice coupling. We present here an inelastic neutron scattering study of the spin dynamics in this composition. Above Tf , the dynamical scattering function S(Q,E) is ungapped and quasi-elastic, similar to undoped LiGaCr4O8. Below Tf , the spectral weight splits between a broad inelastic feature at 5.8 meV and toward the elastic line. The former feature can be ascribed to spin precessions within antiferromagnetic loops, lifted to finite energy by the effective biquadratic spin-lattice term in the spin Hamiltonian.

We have synthesized single-crystal samples of $\beta$-VOSO$_4$ and fully characterized their magnetic properties. Our magnetic susceptibility, high field magnetization and powder inelastic neutron scattering results are in excellent agreement with theoretical expressions for a one-dimensional spin-1/2 Heisenberg chain with an exchange parameter of $3.83(2)$ meV. Ab initio calculations identify the superexchange pathway, revealing that the spin-chain does not run along the expected crystallographic chain $a$ direction but instead between V$^{4+}$O$_{6}$ octahedra that are linked via SO$_{4}$ tetrahedra along the $b$ axis. We do not detect any phase transition to a long-range magnetic order within our experimental conditions, indicating $\beta$-VOSO$_4$ is very close to an ideal one-dimensional magnetic system.

Real-time acquisition of accurate machine parameters is of significance to achieving high performance in electric drives, particularly targeted for mission-critical applications. Unlike the saturation effects, the temperature variations are difficult to predict, thus it is essential to track temperature-dependent parameters online. In this paper, a unified framework is developed for online parameter identification of rotating electric machines, premised on the Recursive Prediction Error Method (RPEM). Secondly, the prediction gradient ($\mathbf{\Psi}^T$)-based RPEM is adopted for identification of the temperature-sensitive parameters, i.e., the permanent magnet flux linkage ($\Psi_m$) and stator-winding resistance ($R_s$) of the Interior Permanent Magnet Synchronous Machine (IPMSM). Three algorithms, namely, Stochastic Gradient (SGA), Gauss-Newton (GNA), and physically interpretative method (PhyInt) are investigated for the estimation gains computation. A speed-dependent gain-scheduling scheme is used to decouple the inter-dependency of $\Psi_m$ and $R_s$. With the aid of offline simulation methods, the main elements of RPEM such as $\mathbf{\Psi}^T$ are analyzed. The concept validation and the choice of the optimal algorithm is made with the use of System-on-Chip (SoC) based Embedded Real-Time Simulator (ERTS). Subsequently, the selected algorithms are validated with the aid of a 3-kW, IPMSM drive where the control and estimation routines are implemented in the SoC-based industrial embedded control system. The experimental results reveal that $\mathbf{\Psi}^T$-based RPEM, in general, can be a versatile technique in temperature-sensitive parameter adaptation both online and offline.

SmCo$_5$ and YCo$_5$ are isostructural compounds both showing large magnetocrystalline anisotropy, where the former originates mainly from the crystal-electric field and magnetic interactions. We investigate the contribution of both interactions by partially substituting Y by Sm in as-cast polycrystalline Y$_{1-x}$Sm$_{x}$Co$_5$ (with $x$=0, 0.1, 0.2, 0.3, and 0.4) and measuring their structural, magnetic, and electrical properties through X-ray diffraction, magnetization, and electrical transport measurements. Our results suggest an interplay between microstructure strain in as-cast samples and the electronic and magnetic interactions.

We present a comprehensive experimental and ab-initio study of the $S=1/2$ Mo$^{5+}$ system, KMoOP$_2$O$_7$, and show that it realizes the $S = 1/2$ Heisenberg chain antiferromagnet model. Powder neutron diffraction reveals that KMoOP$_2$O$_7$ forms a magnetic network comprised of pairs of Mo$^{5+}$ chains within its monoclinic $P2_1/n$ structure. Antiferromagnetic interactions within the Mo$^{5+}$ chains are identified through magnetometry measurements and confirmed by analysis of the magnetic specific heat. The latter reveals a broad feature centred on $T_\textrm{N} = 0.54$ K, which we ascribe to the onset of long-range antiferromagnetic order. No magnetic Bragg scattering is observed in powder neutron diffraction data collected at 0.05 K, however, which is consistent with a strongly suppressed ordered moment with an upper limit $\mu_\textrm{ord} < 0.15 \mu_\textrm{B}$. The one-dimensional character of the magnetic correlations in KMoOP$_2$O$_7$ is verified through analysis of inelastic neutron scattering data, resulting in a model with $J_\textrm{1} \approx 34$ K and $J_\textrm{2} \approx -2$ K for the intrachain and interchain exchange interactions, respectively. The origin of these experimental findings are addressed through density-functional theory calculations., Comment: 10 pages, 7 figures

This paper investigates runtime monitoring of perception systems. Perception is a critical component of high-integrity applications of robotics and autonomous systems, such as self-driving cars. In these applications, failure of perception systems may put human life at risk, and a broad adoption of these technologies requires the development of methodologies to guarantee and monitor safe operation. Despite the paramount importance of perception, currently there is no formal approach for system-level perception monitoring. In this paper, we formalize the problem of runtime fault detection and identification in perception systems and present a framework to model diagnostic information using a diagnostic graph. We then provide a set of deterministic, probabilistic, and learning-based algorithms that use diagnostic graphs to perform fault detection and identification. Moreover, we investigate fundamental limits and provide deterministic and probabilistic guarantees on the fault detection and identification results. We conclude the paper with an extensive experimental evaluation, which recreates several realistic failure modes in the LGSVL open-source autonomous driving simulator, and applies the proposed system monitors to a state-of-the-art autonomous driving software stack (Baidu's Apollo Auto). The results show that the proposed system monitors outperform baselines, have the potential of preventing accidents in realistic autonomous driving scenarios, and incur a negligible computational overhead.

The neutron diffraction and nuclear magnetic resonance (NMR) measurements have been used to microscopically analyze the magnetic structure in the $S = 1/2$ kagome antiferromagnet CdCu$_{3}$(OH)$_{6}$(NO$_{3}$)$_{2}\cdot $H$_{2}$O. Below the magnetic ordering temperature $T_N\simeq 4$ K, magnetic Bragg reflections at (110) and (100) were found in the neutron diffraction pattern, which suggests a $q=0$ magnetic structure. Furthermore, the vector spin chirality for the $q=0$ structure was successfully identified from the internal field direction obtained by the $^{14}$N-NMR measurement. Our findings point to a chirality-ordered magnetic structure with negative vector chirality and $\langle 100 \rangle$ anisotropy., Comment: 6 pages, 5 figures

The principal Hugoniot of carbon, initially diamond, was measured from 3 to 80 TPa (30 to 800 million atmospheres), the highest pressure ever achieved, using radiography of spherically-converging shocks. The shocks were generated by ablation of a plastic coating by soft x-rays in a laser-heated hohlraum at the National Ignition Facility (NIF). Experiments were performed with low and high drive powers, spanning different but overlapping pressure ranges. The radius-time history of the shock, and the profile of mass density behind, were determined by profile-matching from a time-resolved x-ray radiograph across the diameter of the sphere. Above ~50 TPa, the heating induced by the shock was great enough to ionize a significant fraction of K-shell electrons, reducing the opacity to the 10.2 keV probe x-rays. The opacity and mass density were deduced simultaneously using the constraint that the total mass of the sample was constant. The Hugoniot and opacity were consistent with density functional theory calculations of the electronic states and equation of state (EOS), and varied significantly from theoretical Hugoniots based on Thomas-Fermi theory. Theoretical models used to predict the compressibility of diamond ablator experiments at the NIF, producing the highest neutron yields so far from inertial confinement fusion experiments, are qualitatively consistent with our EOS measurements but appear to overpredict the compressibility slightly. These measurements help to evaluate theoretical techniques and constrain wide-range EOS models applicable to white dwarf stars, which are the ultimate evolutionary form of at least 97% of stars in the galaxy., Comment: arXiv admin note: text overlap with arXiv:2203.08891

We previously reported an experimental platform to induce a spherically-convergent shock in a sample using laser-driven ablation, probed with time-resolved x-ray radiography, and an analysis method to deduce states along the principal shock Hugoniot simultaneously with the x-ray opacity. We have now developed a modified method of analysis that is numerically better-conditioned and faster, and usually provides a better representation of the radiograph with correspondingly lower uncertainties. The previous approach was based on optimizing parameters in a model of the density distribution as a function of radius and time, warped to follow loci such as the shock and the outside of the sample. The converging shock configuration can be described more efficiently in terms of the shocked density and sound speed, expressed as functions of the shock speed Studies of the Hugoniot from various theoretical equations of state (EOS) indicate that, in the typical range of states explored by these experiments, these functions can be described by low-order polynomials. Similarly, few-parameter functions were found suitable for representing the variation of x-ray opacity with shock pressure. This approach was found to perform better in most cases than an alternative method based on parameterization of the EOS.

The quantum approximate optimization algorithm/quantum alternating operator ansatz (QAOA) is a heuristic to find approximate solutions of combinatorial optimization problems. Most literature is limited to quadratic problems without constraints. However, many practically relevant optimization problems do have (hard) constraints that need to be fulfilled. In this article, we present a framework for constructing mixing operators that restrict the evolution to a subspace of the full Hilbert space given by these constraints; We generalize the "XY"-mixer designed to preserve the subspace of "one-hot" states to the general case of subspaces given by a number of computational basis states. We expose the underlying mathematical structure which reveals more of how mixers work and how one can minimize their cost in terms of number of CX gates, particularly when Trotterization is taken into account. Our analysis also leads to valid Trotterizations for "XY"-mixer with fewer CX gates than is known to date. In view of practical implementations, we also describe algorithms for efficient decomposition into basis gates. Several examples of more general cases are presented and analyzed.

We present a randomized algorithm that computes single-source shortest paths (SSSP) in $O(m\log^8(n)\log W)$ time when edge weights are integral and can be negative. This essentially resolves the classic negative-weight SSSP problem. The previous bounds are $\tilde O((m+n^{1.5})\log W)$ [BLNPSSSW FOCS'20] and $m^{4/3+o(1)}\log W$ [AMV FOCS'20]. Near-linear time algorithms were known previously only for the special case of planar directed graphs [Fakcharoenphol and Rao FOCS'01]. In contrast to all recent developments that rely on sophisticated continuous optimization methods and dynamic algorithms, our algorithm is simple: it requires only a simple graph decomposition and elementary combinatorial tools. In fact, ours is the first combinatorial algorithm for negative-weight SSSP to break through the classic $\tilde O(m\sqrt{n}\log W)$ bound from over three decades ago [Gabow and Tarjan SICOMP'89]., Comment: Simplified algorithms and minor corrections throughout the paper

Over the course of six years, a diverse group of school districts and charter management organizations in California ran a substantial experiment in implementing the Next Generation Science Standards (NGSS) in elementary and middle grades. WestEd led an extensive evaluation of that effort, the California K-8 NGSS Early Implementers Initiative, resulting in more than a dozen evaluation reports highlighting important themes and learnings. All reports are intended to be helpful to administrators at the school and district levels, education policymakers, and people charged with designing and/or delivering science professional learning. This report on highlights from the Early Implementers Initiative is the final report of the series. It offers high-level, major lessons learned, challenges, and strategies gleaned from the evaluation series. It also offers recommendations for policymakers and administrators for implementing the Next Generation Science Standards in their own districts.