Search

Motivated by the recent experimental developments, the Pom-CQM model of the $\gamma + N \to J/\psi + N$ reaction of Lee et al. [Eur. Phys. J. A. 58, 252 (2022)] and Sakinah et al. [Phys. Rev. C. 109, 065204 (2024)] has been applied to predict the exclusive $J/\psi$ photo-production on nuclei ($A$). Within the multiple scattering theory, the calculations have been performed by including the impulse amplitude $T^{\rm IMP}_{J/\psi A,\gamma A}$ and the $J/\psi$-nucleus final state interaction (FSI) amplitude $T^{\rm FSI}_{J/\psi A,\gamma A}$. For the deuteron target, $T^{\rm IMP}_{J/\psi d,\gamma d}$ is calculated exactly using the wave function generated from the realistic nucleon-nucleon potentials. It is found that, near the threshold region, the $J/\psi$ photo-production cross sections depend sensitively on the $d$-state of the deuteron wave function. The FSI amplitude $T^{\rm FSI}_{J/\psi A,\gamma A}$ is calculated using the first-order optical potential constructed from the $J/\psi$-$N$ scattering amplitude generated from the employed Pom-CQM model. It turns out that the FSI has significant effects in the large momentum-transfer region. By using the conventional fixed scatter approximation (FSA) and the nuclear form factors from the variational Monte-Carlo (VMC) calculations of Lonardoni et al. [Phys. Rev.C. 96, 024326 (2017)], the cross sections of the $J/\psi$ photo-production on ${^4\rm He}$, ${^{16}\rm O}$, and ${^{40}\rm Ca}$ are also predicted for future experimental investigations at JLab and EIC., Comment: 15 pages, 16 figures

Atom probe tomography (APT) enables near atomic scale three dimensional elemental mapping through the controlled field evaporation of surface atoms triggered by the combined application of a DC voltage and either voltage or laser pulses. As the selected laser wavelength for the atom probes transitioned from the near-infrared (1050 nm) to shorter wavelengths e.g., green (532 nm) and near ultraviolet, the quality of data improved and the range of materials amenable for analysis broadened. A new commercial laser atom probe with a wavelength of 257.5 nm, referred to as deep ultraviolet (DUV), has been recently launched. However, the effects of DUV lasers on different classes of materials have not yet been systematically investigated. In this study, a range of materials, including metals, semiconductor, and oxides, have been examined using commercial atom probes with different laser wavelengths but in principle comparable particle detection system. The quality of the NUV and DUV laser atom probe data is evaluated based on four key metrics: background, detection events, ion detection histogram, and mass-resolving power. Furthermore, the application of a thin coating to the finished APT specimens enhances the data quality for both laser wavelengths.

Thanks to unprecedented language understanding and generation capabilities of large language model (LLM), Retrieval-augmented Code Generation (RaCG) has recently been widely utilized among software developers. While this has increased productivity, there are still frequent instances of incorrect codes being provided. In particular, there are cases where plausible yet incorrect codes are generated for queries from users that cannot be answered with the given queries and API descriptions. This study proposes a task for evaluating answerability, which assesses whether valid answers can be generated based on users' queries and retrieved APIs in RaCG. Additionally, we build a benchmark dataset called Retrieval-augmented Code Generability Evaluation (RaCGEval) to evaluate the performance of models performing this task. Experimental results show that this task remains at a very challenging level, with baseline models exhibiting a low performance of 46.7%. Furthermore, this study discusses methods that could significantly improve performance.

Reconfigurable devices have garnered significant attention for alleviating the scaling requirements of conventional CMOS technology, as they require fewer components to construct circuits with similar function. Prior works required continuous voltage application for programming gate terminal(s) in addition to the primary gate terminal, which undermines the advantages of reconfigurable devices in realizing compact and power-efficient integrated circuits. Here, we realize reconfigurable devices based on a single-gate field-effect transistor (FET) architecture by integrating semiconducting channels consisting of a monolayer film of highly aligned SWCNTs with a ferroelectric AlScN gate dielectric, all compatible with CMOS back-end-of-line (BEOL) processing. We demonstrated these SWCNT ferroelectric FETs (FeFETs) in a centimeter-scale array (~1 cm^2) comprising ~735 devices, with high spatial uniformity in device characteristics across the array. The devices exhibited ambipolar transfer characteristics with high on-state currents and current on/off ratios exceeding 10^5, demonstrating an excellent balance between electron and hole conduction (~270 {\mu}A/{\mu}m at a drain voltage of 3 V. When functioning as a non-volatile memory, the SWCNT FeFETs demonstrated large memory windows of 0.26 V/nm and 0.08 V/nm in the hole and electron conduction regions, respectively, combined with excellent retention behavior for up to 10^4 s. Repeated reconfiguration between p-FET and n-FET modes was also enabled by switching the spontaneous polarization in AlScN and operating the transistor within a voltage range below the coercive voltage. We revealed through circuit simulations that reconfigurable SWCNT transistors can realize ternary content-addressable memory (TCAM) with far fewer devices compared to circuits based on silicon CMOS technology or based on resistive non-volatile devices., Comment: 37 pages, 16 figures (5 main and 11 supplementary figures)

The development of magnetic refrigerators that operate at room temperature without the use of environmentally harmful substances represents a significant advancement in eco-friendly technology. These refrigerators employ the magnetocaloric effect (MCE), which has traditionally been achieved using expensive rare-earth elements such as gadolinium. To facilitate cost-effective commercialization, it is essential to investigate alternative materials, such as transition metal alloys. In this study, an Fe47.5Ni37.5Mn15 alloy, which has a Curie temperature that is close to room temperature, is cast, and the alloy exhibits a noteworthy cooling power of 297.68 J/kg, which makes it good for cost-effective applications. To further enhance MCE performance through super-paramagnetism (e.g. size reduction), nanoparticles of the same composition are synthesized using a top-down approach via pulsed-laser ablation in ethanol. However, these nanoparticles do not exhibit a Curie temperature near room temperature, likely due to significant carbon incorporation during synthesis, which adversely affected their magnetocaloric properties. This study underscores the potential of transition metal alloys for magnetic refrigeration and highlights the need for optimized synthesis methods to achieve desired thermal properties in nanoparticulate form.

The quantum Josephson voltage standard is well established across the metrology community for many years. It relies on the synchronisation of the flux tunneling in the S/I/S Josepson junctions (JJ) with the microwave radiation (MW). The phenomenon is called the Shapiro steps. Together with the Quantum Hall resistance standard, the voltage standard forms the foundation of electrostatic metrology. The current is then defined as the ratio of the voltage and resistance. Realisation of the quantum current standard, would close the electrostatic metrological triangle of voltage-resistance-current. The current quantisation, the inverse Shapiro steps, was recently shown using the superconducting nanowires and small JJ. The effect is a synchronization of the MW with the Cooper pair tunnelling. This paves the way to combine the JJ voltage and current standards on the same chip and demonstrate feasibility of the multi-standard operation. We show the voltage and current quantization on the same chip up to frequency of 10 GHz, corresponding to the amplitudes 0.021 mV and 3.23 nA respectively. The accuracy of the voltage and current quantisation, however, is relatively low, 35 ppk and 100 ppk respectively. We discuss measures to optimise the JJs, circuit and environment to boost the amplitude and accuracy of the standards., Comment: 5 figures, 5 pages, published in APL

ThMn12-type (Sm,Zr)1(Fe,Co,Ti)12 compounds show great potential for permanent magnets. Magnetically hard anisotropic powders prepared via reduction-diffusion exhibit a significant increase in coercivity from 0.45 T to 1.26 T as the processing temperature is raised from 990{\deg}C to 1220{\deg}C. Structural and microchemical analyses at high-resolution reveal that high-temperature processing annihilates grain boundaries (GBs) and reduces the density of twin boundaries (TBs), which are defects acting as weak links limiting the coercivity in the 1:12 system. Ostwald ripening is proposed as the mechanism behind the reduction of GB and TB densities at higher temperature, driven by the reduction in interfacial energy and enhancing atomic structural uniformity.

Hydrogen, while a promising sustainable energy carrier, presents challenges such as the embrittlement of materials due to its ability to penetrate and weaken their crystal structures. Here we investigate Fe4N nitride layers, formed on iron through a cost-effective gas nitriding process, as an effective hydrogen permeation barrier. A combination of screening using advanced characterization, density functional theory calculations, and hydrogen permeation analysis reveals that a nitride layer reduces hydrogen diffusion by a factor of 20 at room temperature. This reduction is achieved by creating energetically unfavorable states due to stronger H-binding at the surface and high energy barriers for diffusion. The findings demonstrate the potential of Fe4N as a cost-efficient and easy-to-process solution to protecting metallic materials exposed to hydrogen, with great advantages for large-scale applications.

We explore how interactions inspired by drawing software can help edit text. Making an analogy between visual and text editing, we consider words as pixels, sentences as regions, and tones as colours. For instance, direct manipulations move, shorten, expand, and reorder text; tools change number, tense, and grammar; colours map to tones explored along three dimensions in a tone picker; and layers help organize and version text. This analogy also leads to new workflows, such as boolean operations on text fragments to construct more elaborated text. A study shows participants were more successful at editing text and preferred using the proposed interface over existing solutions. Broadly, our work highlights the potential of interaction analogies to rethink existing workflows, while capitalizing on familiar features.

Intra-cardiac Echocardiography (ICE) is a crucial imaging modality used in electrophysiology (EP) and structural heart disease (SHD) interventions, providing real-time, high-resolution views from within the heart. Despite its advantages, effective manipulation of the ICE catheter requires significant expertise, which can lead to inconsistent outcomes, particularly among less experienced operators. To address this challenge, we propose an AI-driven closed-loop view guidance system with human-in-the-loop feedback, designed to assist users in navigating ICE imaging without requiring specialized knowledge. Our method models the relative position and orientation vectors between arbitrary views and clinically defined ICE views in a spatial coordinate system, guiding users on how to manipulate the ICE catheter to transition from the current view to the desired view over time. Operating in a closed-loop configuration, the system continuously predicts and updates the necessary catheter manipulations, ensuring seamless integration into existing clinical workflows. The effectiveness of the proposed system is demonstrated through a simulation-based evaluation, achieving an 89% success rate with the 6532 test dataset, highlighting its potential to improve the accuracy and efficiency of ICE imaging procedures.

Recently, computer-aided design models and electromagnetic simulations have been used to augment synthetic aperture radar (SAR) data for deep learning. However, an automatic target recognition (ATR) model struggles with domain shift when using synthetic data because the model learns specific clutter patterns present in such data, which disturbs performance when applied to measured data with different clutter distributions. This study proposes a framework particularly designed for domain-generalized SAR-ATR called IRASNet, enabling effective feature-level clutter reduction and domain-invariant feature learning. First, we propose a clutter reduction module (CRM) that maximizes the signal-to-clutter ratio on feature maps. The module reduces the impact of clutter at the feature level while preserving target and shadow information, thereby improving ATR performance. Second, we integrate adversarial learning with CRM to extract clutter-reduced domain-invariant features. The integration bridges the gap between synthetic and measured datasets without requiring measured data during training. Third, we improve feature extraction from target and shadow regions by implementing a positional supervision task using mask ground truth encoding. The improvement enhances the ability of the model to discriminate between classes. Our proposed IRASNet presents new state-of-the-art public SAR datasets utilizing target and shadow information to achieve superior performance across various test conditions. IRASNet not only enhances generalization performance but also significantly improves feature-level clutter reduction, making it a valuable advancement in the field of radar image pattern recognition., Comment: 16 pages, 11 figures

d/Deaf and hearing song-signers become prevalent on video-sharing platforms, but translating songs into sign language remains cumbersome and inaccessible. Our formative study revealed the challenges song-signers face, including semantic, syntactic, expressive, and rhythmic considerations in translations. We present ELMI, an accessible song-signing tool that assists in translating lyrics into sign language. ELMI enables users to edit glosses line-by-line, with real-time synced lyric highlighting and music video snippets. Users can also chat with a large language model-driven AI to discuss meaning, glossing, emoting, and timing. Through an exploratory study with 13 song-signers, we examined how ELMI facilitates their workflows and how song-signers leverage and receive an LLM-driven chat for translation. Participants successfully adopted ELMI to song-signing, with active discussions on the fly. They also reported improved confidence and independence in their translations, finding ELMI encouraging, constructive, and informative. We discuss design implications for leveraging LLMs in culturally sensitive song-signing translations., Comment: 18 pages excluding reference and appendix

As minimally verbal autistic (MVA) children communicate with parents through few words and nonverbal cues, parents often struggle to encourage their children to express subtle emotions and needs and to grasp their nuanced signals. We present AACessTalk, a tablet-based, AI-mediated communication system that facilitates meaningful exchanges between an MVA child and a parent. AACessTalk provides real-time guides to the parent to engage the child in conversation and, in turn, recommends contextual vocabulary cards to the child. Through a two-week deployment study with 11 MVA child-parent dyads, we examine how AACessTalk fosters everyday conversation practice and mutual engagement. Our findings show high engagement from all dyads, leading to increased frequency of conversation and turn-taking. AACessTalk also encouraged parents to explore their own interaction strategies and empowered the children to have more agency in communication. We discuss the implications of designing technologies for balanced communication dynamics in parent-MVA child interaction., Comment: 19 pages excluding reference and appendix

Expressing stressful experiences in words is proven to improve mental and physical health, but individuals often disengage with writing interventions as they struggle to organize their thoughts and emotions. Reflective prompts have been used to provide direction, and large language models (LLMs) have demonstrated the potential to provide tailored guidance. Current systems often limit users' flexibility to direct their reflections. We thus present ExploreSelf, an LLM-driven application designed to empower users to control their reflective journey. ExploreSelf allows users to receive adaptive support through dynamically generated questions. Through an exploratory study with 19 participants, we examine how participants explore and reflect on personal challenges using ExploreSelf. Our findings demonstrate that participants valued the balance between guided support and freedom to control their reflective journey, leading to deeper engagement and insight. Building on our findings, we discuss implications for designing LLM-driven tools that promote user empowerment through effective reflective practices., Comment: 17 pages excluding reference and appendix

Synchronization of Bloch oscillations in small Josephson junctions (JJs) under microwave radiation, which leads to current quantization, has been proposed as an effect that is dual to the appearance of Shapiro steps. This current quantization was recently demonstrated in superconducting nanowires in a compact high-impedance environment. Direct observation of current quantization in JJs would cofirm the synchronization of Bloch oscillations with microwaves and help with the realisation of the metrological current standard. Here, we place JJs in a high-impedance environment and demonstrate dual Shapiro steps for frequencies up to 24 GHz (I=7.7 nA). Current quantization exists, however, only in a narrow range of JJ parameters. We carry out a systematic study to explain this by invoking the model of a JJ in the presence of thermal noise. The findings are important for fundamental physics and application in quantum metrology., Comment: 13 pages, 5 figures

The development of sustainable transportation and communication systems requires an increase in both energy density and capacity retention of Li-batteries. Using substrates forming a solid solution with body centered cubic Li enhances the cycle stability of anode-less batteries. However, it remains unclear how the substrate microstructure affects the lithiation behavior. Here, we deploy a correlative, near-atomic scale probing approach through combined ion- and electron-microscopy to examine the distribution of Li in Li-Ag diffusion couples as model system. We reveal that Li regions with over 93.8% at.% nucleate within Ag at random high angle grain boundaries, whereas grain interiors are not lithiated. We evidence the role of kinetics and mechanical constraint from the microstructure over equilibrium thermodynamics in dictating the lithiation process. The findings suggest that grain size and grain boundary character are critical to enhance the electrochemical performance of interlayers/electrodes, particularly for improving lithiation kinetics and hence reducing dendrite formation.

Some van der Waals (vdW) materials exhibit ferroelectricity, making them promising for novel non-volatile memories (NVMs) such as ferroelectric diodes (FeDs). CuInP2S6 (CIPS) is a well-known vdW ferroelectric that has been integrated with graphene for memory devices. Here we demonstrate FeDs with self-rectifying, hysteretic current-voltage characteristics based on vertical heterostructures of 10-nm-thick CIPS and graphene. By using vdW indium-cobalt top electrodes and graphene bottom electrodes, we achieve high electroresistance (on- and off-state resistance ratios) of ~10^6, on-state rectification ratios of ~2500 for read/write voltages of 2 V/0.5 V and maximum output current densities of 100 A/cm^2. These metrics compare favourably with state-of-the-art FeDs. Piezoresponse force microscopy measurements show that stabilization of intermediate net polarization states in CIPS leads to stable multi-bit data retention at room temperature. The combination of two-terminal design, multi-bit memory, and low-power operation in CIPS-based FeDs is potentially interesting for compute-in-memory and neuromorphic computing applications., Comment: 17 Pages

Averaged observations of physical phenomena have been utilized for comprehending specific occurrences in nature; however, these may overlook the crucial characteristics of individual events, thereby leading to diverse conclusions. For example, individual wave occurrences such as superposition and interference yield markedly divergent outcomes when viewed in detail. Similarly, this study enhances the comprehensive framework of spin-orbit torque (SOT) within the hysteresis loop shift measurement by employing the average of effective magnetic fields arising from two distinct magnetic reversals. This approach facilitates the presentation of a physically descriptive SOT model, previously characterized only by single chirality qualitatively. By integrating this model with established measurement methodologies and theoretical paradigms, we advance a theoretical framework based on the magnetic domain-wall chirality of individual polarizations and aim to elucidate the phenomena of SOT with clarity. The anticipated outcomes include the rectification of inaccuracies in widely employed measurement methodologies and the enhancement of our comprehension of the fundamental physics, which are expected to propel advancements in next-generation spintronics materials and devices., Comment: 24 pages, 5 figures

Ferroelectric field-effect-transistor (FEFET) has emerged as a scalable solution for 3D NAND and embedded flash (eFlash), with recent progress in achieving large memory window (MW) using metal-insulator-ferroelectric-insulator-semiconductor (MIFIS) gate stacks. Although the physical origin of the large MW in the MIFIS stack has already been discussed, its retention characteristics have not been explored yet. Here, we demonstrate MIFIS FEFET with a maximum MW of 9.7 V, and show that MIFIS FEFET has unstable retention characteristics, especially after erase. We discover the origin of the unstable retention characteristics and prove our hypothesis with absolute polarization measurement and different operation modes, showing that the unstable retention characteristics is a fundamental issue. Based on the understanding, we discuss a novel charge compensation model and promising engineering methodologies to achieve stable retention in MIFIS FEFET., Comment: We are submitting this to an IEEE journal but because of delays, we would like to share the information

In speaker verification systems, the utilization of short utterances presents a persistent challenge, leading to performance degradation primarily due to insufficient phonetic information to characterize the speakers. To overcome this obstacle, we propose a novel structure, MR-RawNet, designed to enhance the robustness of speaker verification systems against variable duration utterances using raw waveforms. The MR-RawNet extracts time-frequency representations from raw waveforms via a multi-resolution feature extractor that optimally adjusts both temporal and spectral resolutions simultaneously. Furthermore, we apply a multi-resolution attention block that focuses on diverse and extensive temporal contexts, ensuring robustness against changes in utterance length. The experimental results, conducted on VoxCeleb1 dataset, demonstrate that the MR-RawNet exhibits superior performance in handling utterances of variable duration compared to other raw waveform-based systems., Comment: 5 pages, accepted by Interspeech 2024

Sign languages are multi-channel languages that communicate information through not just the hands (manual signals) but also facial expressions and upper body movements (non-manual signals). However, since automatic sign language translation is usually performed by generating a single sequence of glosses, researchers eschew non-manual and co-occurring manual signals in favor of a simplified list of manual glosses. This can lead to significant information loss and ambiguity. In this paper, we introduce a new task named multi-channel sign language translation (MCSLT) and present a novel metric, SignBLEU, designed to capture multiple signal channels. We validated SignBLEU on a system-level task using three sign language corpora with varied linguistic structures and transcription methodologies and examined its correlation with human judgment through two segment-level tasks. We found that SignBLEU consistently correlates better with human judgment than competing metrics. To facilitate further MCSLT research, we report benchmark scores for the three sign language corpora and release the source code for SignBLEU at https://github.com/eq4all-projects/SignBLEU., Comment: Published in LREC-Coling 2024

Ferroelectric field-effect transistors (FeFET) with two-dimensional (2D) semiconductor channels are promising low-power, embedded non-volatile memory (NVM) candidates for next-generation in-memory computing. However, the performance of FeFETs can be limited by a charge imbalance between the ferroelectric layer and the channel, and for low-dimensional semiconductors, also by a high contact resistance between the metal electrodes and the channel. Here, we report a significant enhancement in performance of contact-engineered FeFETs with a 2D MoS2 channel and a ferroelectric Al0.68Sc0.32N (AlScN) gate dielectric. Replacing Ti with In contact electrodes results in a fivefold increase in on-state current (~120 uA/um at 1 V) and on-to-off ratio (~2*10^7) in the FeFETs. In addition, the high carrier concentration in the MoS2 channel during the on-state (> 10^14 cm^-2) facilitates the observation of a metal-to-insulator phase transition in monolayer MoS2 permitting observation of high field effect mobility (> 100 cm^2V^-1s^-1) at cryogenic temperatures. Our work and devices broaden the potential of FeFETs and provides a unique platform to implement high-carrier-density transport in a 2D channel., Comment: 42 pages, 5 main figures

Waveguide-integrated mid-infrared (MIR) photodetectors are pivotal components for developing molecular spectroscopy applications, leveraging mature photonic integrated circuit (PIC) technologies. Despite various strategies, critical challenges still remain in achieving broadband photoresponse, cooling-free operation, and large-scale complementary-metal-oxide-semiconductor (CMOS)-compatible manufacturability. To leap beyond these limitations, the bolometric effect - a thermal detection mechanism - is introduced into the waveguide platform. More importantly, we pursue a free-carrier absorption (FCA) process in germanium (Ge) to create an efficient light-absorbing medium, providing a pragmatic solution for full coverage of the MIR spectrum without incorporating exotic materials into CMOS. Here, we present an uncooled waveguide-integrated photodetector based on a Ge-on-insulator (Ge-OI) PIC architecture, exploiting the bolometric effect combined with FCA. Notably, our device exhibits a broadband responsivity of ~12 mA/W across 4030-4360 nm (and potentially beyond), challenging the state of the art, while achieving a noise-equivalent power of 3.4x10^-9 W/Hz^0.5 at 4180 nm. We further demonstrate label-free sensing of carbon dioxide using our integrated photodetector and sensing waveguide on a single chip. This approach to room-temperature waveguide-integrated MIR photodetection, harnessing bolometry with FCA in Ge, not only facilitates the realization of fully integrated lab-on-a-chip systems with wavelength flexibility but also provides a blueprint for MIR PICs with CMOS-foundry-compatibility., Comment: 6 figures for the main manuscript and 14 figures for the supplementary information

In this paper, we study interior estimates for solutions to linearized Monge-Amp\`ere equations in divergence form with drift terms and the right-hand side containing the divergence of a bounded vector field. Equations of this type appear in the study of semigeostrophic equations in meteorology and the solvability of singular Abreu equations in the calculus of variations with a convexity constraint. We prove an interior Harnack inequality and H\"older estimates for solutions to equations of this type in two dimensions, and under an integrability assumption on the Hessian matrix of the Monge-Amp\`ere potential in higher dimensions. Our results extend those of Le (Analysis of Monge-Amp\`ere equations, Graduate Studies in Mathematics, vol.240, American Mathematical Society, 2024) to equations with drift terms.

With the advancement of Large-Language Models (LLMs) and Large Vision-Language Models (LVMs), agents have shown significant capabilities in various tasks, such as data analysis, gaming, or code generation. Recently, there has been a surge in research on web agents, capable of performing tasks within the web environment. However, the web poses unforeseeable scenarios, challenging the generalizability of these agents. This study investigates the disparities between human and web agents' performance in web tasks (e.g., information search) by concentrating on planning, action, and reflection aspects during task execution. We conducted a web task study with a think-aloud protocol, revealing distinct cognitive actions and operations on websites employed by humans. Comparative examination of existing agent structures and human behavior with thought processes highlighted differences in knowledge updating and ambiguity handling when performing the task. Humans demonstrated a propensity for exploring and modifying plans based on additional information and investigating reasons for failure. These findings offer insights into designing planning, reflection, and information discovery modules for web agents and designing the capturing method for implicit human knowledge in a web task.

We discuss that some light baryon resonances exhibit properties which cannot be described when attributing a three-valence quark structure to them. Besides pointing out the hadron resonances which clearly require description beyond the quark model, we focus on the third $s_{11},~ N^*$ state and its decay to final states consisting of the lightest hyperon resonances which have a partial width comparable to that for the decay to $\pi N$. Such properties of the mentioned nucleon resonance get manifested in the cross sections and other observables related to processes producing the lightest hyperon resonances. We show that all these findings arise from the strong association of the baryon resonances to the dynamics among the ground-state hadrons., Comment: Proceedings for the XLV Symposium on Nuclear Physics, held in Cocoyoc, Morelos, Mexico

Transesophageal echocardiography (TEE) plays a pivotal role in cardiology for diagnostic and interventional procedures. However, using it effectively requires extensive training due to the intricate nature of image acquisition and interpretation. To enhance the efficiency of novice sonographers and reduce variability in scan acquisitions, we propose a novel ultrasound (US) navigation assistance method based on contrastive learning as goal-conditioned reinforcement learning (GCRL). We augment the previous framework using a novel contrastive patient batching method (CPB) and a data-augmented contrastive loss, both of which we demonstrate are essential to ensure generalization to anatomical variations across patients. The proposed framework enables navigation to both standard diagnostic as well as intricate interventional views with a single model. Our method was developed with a large dataset of 789 patients and obtained an average error of 6.56 mm in position and 9.36 degrees in angle on a testing dataset of 140 patients, which is competitive or superior to models trained on individual views. Furthermore, we quantitatively validate our method's ability to navigate to interventional views such as the Left Atrial Appendage (LAA) view used in LAA closure. Our approach holds promise in providing valuable guidance during transesophageal ultrasound examinations, contributing to the advancement of skill acquisition for cardiac ultrasound practitioners., Comment: Accepted in MICCAI 2024; 11 pages, 3 figures

The understanding of protein structure, folding, and interaction with other proteins remains one of the grand challenges of modern biology. Tremendous progress has been made thanks to X-ray- or electron-based techniques that have provided atomic configurations of proteins, and their solvation shell. These techniques though require a large number of similar molecules to provide an average view, and lack detailed compositional information that might play a major role in the biochemical activity of these macromolecules. Based on its intrinsic performance and recent impact in materials science, atom probe tomography (APT) has been touted as a potential novel tool to analyse biological materials, including proteins. However, analysis of biomolecules in their native, hydrated state by APT have not yet been routinely achieved, and the technique's true capabilities remain to be demonstrated. Here, we present and discuss systematic analyses of individual amino-acids in frozen aqueous solutions on two different nanoporous metal supports across a wide range of analysis conditions. Using a ratio of the molecular ions of water as a descriptor for the conditions of electrostatic field, we study the fragmentation and behavior of those amino acids. We discuss the importance sample support, specimen preparation route, acquisition conditions and data analysis, to pave the way towards establishing guidelines for cryo-APT analysis of biomolecules.

As large language models (LLMs) advance to produce human-like arguments in some contexts, the number of settings applicable for human-AI collaboration broadens. Specifically, we focus on subjective decision-making, where a decision is contextual, open to interpretation, and based on one's beliefs and values. In such cases, having multiple arguments and perspectives might be particularly useful for the decision-maker. Using subtle sexism online as an understudied application of subjective decision-making, we suggest that LLM output could effectively provide diverse argumentation to enrich subjective human decision-making. To evaluate the applicability of this case, we conducted an interview study (N=20) where participants evaluated the perceived authorship, relevance, convincingness, and trustworthiness of human and AI-generated explanation-text, generated in response to instances of subtle sexism from the internet. In this workshop paper, we focus on one troubling trend in our results related to opinions and experiences displayed in LLM argumentation. We found that participants rated explanations that contained these characteristics as more convincing and trustworthy, particularly so when those opinions and experiences aligned with their own opinions and experiences. We describe our findings, discuss the troubling role that confirmation bias plays, and bring attention to the ethical challenges surrounding the AI generation of human-like experiences., Comment: Presented at the Trust and Reliance in Evolving Human-AI Workflows (TREW) Workshop at CHI 2024

The intensive computational burden of Stable Diffusion (SD) for text-to-image generation poses a significant hurdle for its practical application. To tackle this challenge, recent research focuses on methods to reduce sampling steps, such as Latent Consistency Model (LCM), and on employing architectural optimizations, including pruning and knowledge distillation. Diverging from existing approaches, we uniquely start with a compact SD variant, BK-SDM. We observe that directly applying LCM to BK-SDM with commonly used crawled datasets yields unsatisfactory results. It leads us to develop two strategies: (1) leveraging high-quality image-text pairs from leading generative models and (2) designing an advanced distillation process tailored for LCM. Through our thorough exploration of quantization, profiling, and on-device deployment, we achieve rapid generation of photo-realistic, text-aligned images in just two steps, with latency under one second on resource-limited edge devices., Comment: 4 pages, accepted to CVPR24 First Workshop on Efficient and On-Device Generation (EDGE)

In his ground-breaking work, K. Kato constructed the Euler system of Beilinson--Kato's zeta elements and proved spectacular results on the Iwasawa main conjecture for elliptic curves and the classical and $p$-adic Birch and Swinnerton-Dyer conjectures by using these elements. The goal of this expository lecture note is to explain how Kato's Euler systems fit into the framework of the arithmetic of elliptic curves and their Iwasawa theory, and we hope that this approach eventually helps the reader to read Kato's original paper more easily and with less pain., Comment: This is the refereed version. It is written for the proceedings of the ICTS program "Elliptic curves and the special values of $L$-functions". Several typos are corrected and the exposition is improved. Comments very welcome

This study demonstrates the developments of self-assembled optical metasurfaces to overcome inherent limitations in polarization density (P) within natural materials, which hinder achieving high refractive indices (n) at optical frequencies. The Maxwellian macroscopic description establishes a link between P and n, revealing a static limit in natural materials, restricting n to approximately 4.0 at optical frequencies. Optical metasurfaces, utilizing metallic colloids on a deep-subwavelength scale, offer a solution by unnaturally enhancing n through electric dipolar (ED) resonances. Self-assembly enables the creation of nanometer-scale metallic gaps between metallic nanoparticles (NPs), paving the way for achieving exceptionally high n at optical frequencies. This study focuses on assembling polyhedral gold (Au) NPs into a closely packed monolayer by rationally designing the polymeric ligand to balance attractive and repulsive forces, in that polymeric brush-mediated self-assembly of the close-packed Au NP monolayer is robustly achieved over a large-area. The resulting monolayer of Au nanospheres (NSs), nanooctahedras (NOs), and nanocubes (NCs) exhibits high macroscopic integrity and crystallinity, sufficiently enough for pushing n to record-high regimes. The study underlies the significance of capacitive coupling in achieving an unnaturally high n and explores fine-tuning Au NC size to optimize this coupling. The achieved n of 10.12 at optical frequencies stands as a benchmark, highlighting the potential of polyhedral Au NPs in advancing optical metasurfaces.

The growth in data generation necessitates efficient data processing technologies to address the von Neumann bottleneck in conventional computer architecture. Memory-driven computing, which integrates non-volatile memory (NVM) devices in a 3D stack, is gaining attention, with CMOS back-end-of-line (BEOL) compatible ferroelectric (FE) diodes being ideal due to their two-terminal design and inherently selector-free nature, facilitating high-density crossbar arrays. Here, we demonstrate BEOL-compatible, high-performance FE-diodes scaled to 5, 10, and 20 nm FE Al0.72Sc0.28N/Al0.64Sc0.36N films. Through interlayer (IL) engineering, we show substantial improvements in the ON/OFF ratios (>166 times) and rectification ratios (>176 times) in these scaled devices. The superlative characteristics also enables 5-bit multi-state operation with a stable retention. We also experimentally and theoretically demonstrate the counterintuitive result that the inclusion of an IL can lead to a decrease in the ferroelectric switching voltage of the device. An in-depth analysis into the device transport mechanisms is performed, and our compact model aligns seamlessly with the experimental results. Our results suggest the possibility of using scaled AlxSc1-xN FE-diodes for high performance, low-power, embedded NVM.

Singular fourth-order Abreu equations have been used to approximate minimizers of convex functionals subject to a convexity constraint in dimensions higher than or equal to two. For Abreu type equations, they often exhibit different solvability phenomena in dimension one and dimensions at least two. We prove the analogues of these results for the variational problem and singular Abreu equations in dimension one, and use the approximation scheme to obtain a characterization of limiting minimizers to the one-dimensional variational problem., Comment: final version to appear in Applied Mathematics and Optimization

We present a comprehensive theoretical and computational model that explores the behavior of a thin hydrated film bonded to a non-hydrated / impermeable soft substrate in the context of surface and bulk elasticity coupled with surface diffusion kinetics. This type of coupling can manifests as an integral aspect in diverse engineering processes encountered in optical interference coatings, tissue engineering, soft electronics, and can prove important in design process for the next generation of sensors and actuators, especially as the focus is shifted to systems in smaller lengthscales. The intricate interplay between solvent diffusion and deformation of the film is governed by surface poroelasticity, and the viscoelastic deformation of the substrate. While existing methodologies offer tools for studying coupled poroelasticity involving solvent diffusion and network deformation, there exists a gap in understanding how coupled poroelastic processes occurring in a film attached to the boundary of a highly deformable solid can influence its response. In this study, we introduce a non-equilibrium thermodynamics formulation encompassing the multiphysical processes of surface poroelasticity and bulk viscoelasticity, complemented by a corresponding finite element implementation. Our approach captures the complex dynamics between the finite deformation of the substrate and solvent diffusion on the surface. This work contributes valuable insights, particularly in scenarios where the coupling of surface diffusion kinetics and substrate elasticity is an important design factor., Comment: 20 pages, 8 figues. arXiv admin note: text overlap with arXiv:2305.08805

The evolution of video generation from text, starting with animating MNIST numbers to simulating the physical world with Sora, has progressed at a breakneck speed over the past seven years. While often seen as a superficial expansion of the predecessor text-to-image generation model, text-to-video generation models are developed upon carefully engineered constituents. Here, we systematically discuss these elements consisting of but not limited to core building blocks (vision, language, and temporal) and supporting features from the perspective of their contributions to achieving a world model. We employ the PRISMA framework to curate 97 impactful research articles from renowned scientific databases primarily studying video synthesis using text conditions. Upon minute exploration of these manuscripts, we observe that text-to-video generation involves more intricate technologies beyond the plain extension of text-to-image generation. Our additional review into the shortcomings of Sora-generated videos pinpoints the call for more in-depth studies in various enabling aspects of video generation such as dataset, evaluation metric, efficient architecture, and human-controlled generation. Finally, we conclude that the study of the text-to-video generation may still be in its infancy, requiring contribution from the cross-discipline research community towards its advancement as the first step to realize artificial general intelligence (AGI)., Comment: First complete survey on Text-to-Video Generation, 44 pages, 20 figures

The numerous stories around LK-99 as a possible room-temperature superconductor over the summer of 2023 epitomise that materials are more than a bulk crystallographic structure or an expected composition. Like all materials, those at the core of technologies for the energy generation transition, including batteries, catalysts or quantum materials draw their properties from a hierarchy of microstructural features where impurities can dramatically influence the outcomes. As we move towards a circular economy, the recycling of materials will inevitably create fluxes of increasingly impure materials, generating new challenges for fabricating materials with controlled properties. Here, we provide our perspective on how high-end microscopy and microanalysis have helped us to understand relationships between synthesis, processing and microstructure, avoiding imprecise or even erroneous interpretations on the origins of the properties from a range of materials. We highlight examples of how unexpected impurities and their spatial distribution on the nanoscale can be turned into an advantage to define pathways for synthesis of materials with new and novel sets of physical properties.

We explicitly construct the rank one primitive Stark (equivalently, Kolyvagin) system extending a constant multiple of Flach's zeta elements for semi-stable elliptic curves. As its arithmetic applications, we obtain the equivalence between a specific behavior of the Stark system and the minimal modularity lifting theorem, and we also discuss the cyclicity of the adjoint Selmer groups. This Stark system construction yields a more refined interpretation of the collection of Flach's zeta elements than the "geometric Euler system" approach due to Flach, Wiles, Mazur, and Weston., Comment: The comparison with other recent work is given, as per the request. Comments are very welcome

In this short note, we study the anticyclotomic analogue of the "weak" main conjecture of Mazur-Tate on Fitting ideals of Selmer groups for elliptic curves with supersingular reduction., Comment: submitted