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Soft metals like lithium and sodium play a critical role in battery technology owing to their high energy density. Texture formation by grain selection growth of soft metals during electrochemical processes is a crucial factor affecting power and safety. Developing a framework to understand and control grain growth is a multifaceted challenge. Here, a general thermodynamic theory and phase-field model are formulated to study grain selection growth of soft metals. Our study focuses on the interplay between surface energy and atomic mobility-related intrinsic strain energy in grain selection growth. Differences in grain selection growth arise from the anisotropy in surface energy and diffusion barrier of soft metal atoms. Our findings highlight the kinetic limitations of solid-state Li metal batteries, which originate from load stress-induced surface energy anisotropy. These insights lead to the development of an amorphous LixSi1-x (0.50

This study aimed to investigate the effects of genetic polymorphisms on tacrolimus blood levels and intra-individual variability in recipients of heart transplants during the early post-transplantation period. Demographic information, concomitant medications, daily tacrolimus dose, trough concentration, and physiological and biochemical information of 87 Chinese recipients of heart transplants were collected. Trough concentrations were determined using a chemiluminescent micro-particle immunoassay, and 17 selected single nucleic acid polymorphisms were genotyped by direct sequencing. We assessed intra-individual variability by calculating the coefficient of variation of tacrolimus trough concentration and analyzed factors associated with tacrolimus concentration and intra-individual variability. Our study found that low body weight and a high percentage of neutrophils significantly influenced the coefficient of variation of tacrolimus. CYP3A5*1D and CYP3A7 rs776744 haplotypes correlated significantly with an intra-individual coefficient of variation of tacrolimus trough concentration during the early postoperative period. Patients with the CYP3A5*1D rs15524 and CYP3A7 rs776744 TT haplotype had a higher coefficient of variation than carriers of the C allele. Genetic polymorphisms in recipients of heart transplants affect tacrolimus metabolism, significantly affecting tacrolimus blood concentration during the early postoperative period. Genotyping before drug administration can help optimize dosing regimens, reduce intra-individual variability, and improve prognosis., Comment: 26 pages,3figures

Using dispersion relations of the scattering amplitudes and semi-definite programming, we calculate causality bounds on the Wilson coefficients in scalar-tensor effective field theories that include parity-violating operators. Particular attention has been paid to the dynamical-Chern-Simons (dCS) and scalar-Gauss-Bonnet (sGB) couplings, along with higher order coefficients, and the interplay between them. For the leading terms, the bounds on the parity-conserving and -violating coefficients are simply projections of the complex coefficients. Some parity-violating coefficients are found to be upper bounded by the the parity-conserving counterparts, or the higher order parity-conserving coefficients. While the observational constraints on parity-violating coefficients are weaker than the parity-conserving counterparts, the causality bounds are of comparable strength and thus may play a more prominent role in constraining strong gravity effects in upcoming observations., Comment: 49 pages, 19 figures, 1 table

Conductor materials with good mechanical performance as well as high electrical- and thermal-conductivities are particularly important to break through the current bottle-neck limit ($\sim 100$ T) of pulsed magnets. Here we perform systematic studies on the elastic properties of the Cu-6wt%Ag alloy wires, a promising candidate material for the new-generation pulsed magnets, by employing two independent ultrasonic techniques - resonant ultrasound spectroscopy (RUS) and ultrasound pulse-echo experiments. Our RUS measurements manifest that the elastic properties of the Cu-6wt%Ag alloy wires can be improved by an electroplastic drawing procedure as compared with the conventional cold drawing. We also take this chance to test the availability of our newly-built ultrasound pulse-echo facility at Wuhan National High Magnetic Field Center (WHMFC, China), and the results suggest that the elastic performance of the electroplastically-drawn Cu-6wt%Ag alloy wire remains excellent without anomalous softening under extreme conditions, e.g., ultra-high magnetic field up to 50 T, nitrogen / helium cryogenic liquids., Comment: 6 pages, 4 figures, 1 table

It is generally believed that electronic correlation, geometric frustration, and topology, \textit{individually}, can facilitate the emergence of various intriguing properties that have attracted a broad audience for both fundamental research and potential applications. Here, we report a systematic investigation on a quasi-kagome Kondo Weyl semimetal candidate Ce$_3$TiSb$_5$. A series of unconventional Hall effects are observed. In the paramagnetic phase, signature of dynamic $c$-$f$ hybridization is revealed by a reduction of anomalous Hall effect and is connected to frustration-promoted incoherent Kondo scattering. A large topological Hall effect exceeding 0.2 $\mu\Omega$ cm is found at low temperatures, which should be ascribed to the noncolinear magnetic structures of the frustrated quasi-kagome lattice. In addition, a peculiar loop-shaped Hall effect with switching chirality is also seen, which is inferred to be associated with magnetic domain walls that pin history-dependent spin chirality and / or Fermi-arc surface states projected from the in-gap Weyl nodes. These exotic results place Ce$_3$TiSb$_5$ in a regime of highly-frustrated antiferromagnetic dense Kondo lattice with a nontrivial topology on an ``extended" global phase diagram, and highlight the interplay among electronic correlation, geometric frustration and topology., Comment: 13+3 pages, 6+3 figures, 2+1 tables

Recent studies emphasize the crucial role of data augmentation in enhancing the performance of object detection models. However,existing methodologies often struggle to effectively harmonize dataset diversity with semantic coordination.To bridge this gap, we introduce an innovative augmentation technique leveraging pre-trained conditional diffusion models to mediate this balance. Our approach encompasses the development of a Category Affinity Matrix, meticulously designed to enhance dataset diversity, and a Surrounding Region Alignment strategy, which ensures the preservation of semantic coordination in the augmented images. Extensive experimental evaluations confirm the efficacy of our method in enriching dataset diversity while seamlessly maintaining semantic coordination. Our method yields substantial average improvements of +1.4AP, +0.9AP, and +3.4AP over existing alternatives on three distinct object detection models, respectively., Comment: 15 pages, 7 figures, ICPR2024

The process how heavy-electron state is established in Kondo-lattice compounds remains an unsolved issue. Recent angle-resolved photoemission spectroscopy and ultrafast optical spectroscopy imply an intermediate regime with hybridization fluctuations prior to the establishment of Kondo coherence, which appears at odds with traditional transport measurements. Extensive experimental works are highly demanded to both reconcile this dichotomy and delineate the intrinsic features in this special regime. Here, on the example of quasi-one-dimensional Kondo lattice compound CeCo$_2$Ga$_8$, we investigated angular dependent magnetotransport properties by planar Hall effect and planar anisotropic magnetoresistance measurements. Upon cooling from $T_K^{on}$ (an onset of incoherent Kondo scattering ) to below $T^*$ (where coherent $c$-$f$ hybridization comes into play), the two-fold symmetrical pattern of planar Hall effect changes sign gradually (i.e. $180^\circ$ phase shift); most strikingly, as a crossover, additional oscillations appear and persist until the heavy-electron state is stabilized below $T^*$. These results provide new insights for the regime of hybridization dynamics which might be deemed as a precursor state of the heavy-electron state., Comment: 19 pages, 4 figures

Multi-channel electrophysiology systems for recording of neuronal activity face significant data throughput limitations, hampering real-time, data-informed experiments. These limitations impact both experimental neurobiology research and next-generation neuroprosthetics. We present a novel solution that leverages the high integration density of 22nm FDSOI CMOS technology to address these challenges. The proposed highly integrated programmable System-on-Chip comprises 68-channel 0.41 \textmu W/Ch recording frontends, spike detectors, 16-channel 0.87-4.39 \textmu W/Ch action potential and 8-channel 0.32 \textmu W/Ch local field potential codecs, as well as a MAC-assisted power-efficient processor operating at 25 MHz (5.19 \textmu W/MHz). The system supports on-chip training processes for compression, training and inference for neural spike sorting. The spike sorting achieves an average accuracy of 91.48% or 94.12% depending on the utilized features. The proposed PSoC is optimized for reduced area (9 mm2) and power. On-chip processing and compression capabilities free up the data bottlenecks in data transmission (up to 91% space saving ratio), and moreover enable a fully autonomous yet flexible processor-driven operation. Combined, these design considerations overcome data-bottlenecks by allowing on-chip feature extraction and subsequent compression., Comment: 26 pages, 14 figures, 1 table, Journal

We theoretically propose a multiparameter cascaded quantum interferometer in which a two-input and two-output setup is obtained by concatenating 50:50 beam splitters with $n$ independent and adjustable time delays. A general method for deriving the coincidence probability of such an interferometer is given based on the linear transformation of the matrix of beam splitters. As examples, we analyze the interference characteristics of one-, two- and three-parameter cascaded quantum interferometers with different frequency correlations and input states. Some typical interferograms of such interferometers are provided to reveal richer and more complicated two-photon interference phenomena. This work offers a general theoretical framework for designing versatile quantum interferometers and provides a convenient method for deriving the coincidence probabilities involved. In principle, arbitrary two-input and two-output experimental setups can be designed with the framework. Potential applications can be found in the complete spectral characterization of two-photon states, multiparameter estimation, and quantum metrology., Comment: 16 pages, 10 figures. arXiv admin note: text overlap with arXiv:2305.13734

The Wilson coefficients of the Standard Model Effective Field Theory are subject to a series of positivity bounds. It has been shown that, while the positivity part of the UV partial wave unitarity leads to the Wilson coefficients living in a convex cone, further including the non-positivity part caps the cone from above. For the Higgs scattering, a capped positivity cone have been obtained using a simplified, linear unitarity conditions and without utilizing the full internal symmetries of the Higgs scattering. Here we further implement the stronger nonlinear unitarity conditions from the UV, which generically gives rise to better bounds. We show that, for the Higgs case in particular, while the nonlinear unitarity conditions per se do not enhance the bounds, the fuller use of the internal symmetries do shrink the capped positivity cone significantly., Comment: 20 pages, 4 figures, invited contribution to JUSTC

Motivated by the recent observations of electronic correlation effect [M. Corasaniti \textit{et al}., Phys. Rev. B \textbf{104}, L121112 (2021)] and topology-stabilized magnetic fluctuations [N. Drucker \textit{et al}., Nat. Commun. \textbf{14}, 5182 (2023)] in the noncentrosymmetric magnetic Weyl semimetal candidate CeAlGe, we performed systematic studies on the local static and dynamic spin susceptibilities by $^{27}$Al nuclear magnetic resonance. Due to the large spin susceptibility from Ce-$4f$ electrons, the theoretically predicted responses from Weyl fermions are overwhelmed. A Knight-shift anomaly is observed below $T^*\sim50$ K, a signature of the onset of coherent Kondo coupling. In addition, an anomalous peak is found in $1/T_1T$ near 15 K, well above the magnetic ordering temperature $T_N \approx 5$ K, which probably is a consequence of topology-stabilized magnetic fluctuations. These results highlight the interplay among electronic correlation, magnetism and band topology in this family of Kondo Weyl semimetals., Comment: 6+3 pages, 5+3 figures

Situated visualization blends data into the real world to fulfill individuals' contextual information needs. However, interacting with situated visualization in public environments faces challenges posed by user acceptance and contextual constraints. To explore appropriate interaction design, we first conduct a formative study to identify user needs for data and interaction. Informed by the findings, we summarize appropriate interaction modalities with eye-based, hand-based and spatially-aware object interaction for situated visualization in public environments. Then, through an iterative design process with six users, we explore and implement interactive techniques for activating and analyzing with situated visualization. To assess the effectiveness and acceptance of these interactions, we integrate them into an AR prototype and conduct a within-subjects study in public scenarios using conventional hand-only interactions as the baseline. The results show that participants preferred our prototype over the baseline, attributing their preference to the interactions being more acceptable, flexible, and practical in public., Comment: CHI 2024 full paper

Inspired by recent experimental synthesis of the two-dimensional Janus material MoSH, we have performed extensive first-principles calculations to investigate the characteristics of all possible Janus two-dimensional transition metal hydrosulfides (JTMSHs), in both the 2H and 1T phases. Our investigations revealed that the JTMSHs can form a unique family of two-dimensional materials with intriguing physical and chemical properties. In details, we have found that JTMSHs can exist in various states, exhibiting metallic, semiconducting, and magnetic character. One particularly intriguing finding considered identification of electride states with distinct bonding characteristics in the 2H-JTMSHs for TM=V, Nb, Ta, Mo, W and Tc. Additionally, we have observed evidence of charge density wave scenario in 1T-JTMSH with TM=Tc, Re, and W and 2H-JTMSH with TM = Tc. Importantly, by applying compressive strain to these materials, the charge density wave can be completely suppressed, eventually leading to the superconducting phase. In particular, we have shown that when subjected to a compressive strain within 10%, the superconducting transition temperature (TC) of 1T-WSH, 1T-TcSH and 2H-TcSH can reach values of 13.8, 16.2 and 24.2 K respectively. Moreover, our investigation also unveiled two intrinsic phonon-mediated superconductors, namely 2H-WSH and 1T-RuSH with TC of 17.0 and 8 K, respectively., Comment: 19pages,6figures

The validation of global climate models is crucial to ensure the accuracy and efficacy of model output. We introduce the spherical convolutional Wasserstein distance to more comprehensively measure differences between climate models and reanalysis data. This new similarity measure accounts for spatial variability using convolutional projections and quantifies local differences in the distribution of climate variables. We apply this method to evaluate the historical model outputs of the Coupled Model Intercomparison Project (CMIP) members by comparing them to observational and reanalysis data products. Additionally, we investigate the progression from CMIP phase 5 to phase 6 and find modest improvements in the phase 6 models regarding their ability to produce realistic climatologies.

Non-fungible tokens (NFTs) drive the prosperity of the Web3 ecosystem. By November 2023, the total market value of NFT projects reached approximately 16 billion USD. Accompanying the success of NFTs are various security issues, i.e., attacks and scams are prevalent in the ecosystem. While NFTs have attracted significant attentions from both industry and academia, there is a lack of understanding of kinds of NFT security issues. The discovery, in-depth analysis, and systematic categorization of these security issues are of significant importance for the prosperous development of the NFT ecosystem. To fill the gap, we performed a systematic literature review related to NFT security, and we have identified 142 incidents from 213 security reports and 18 academic papers until October 1st, 2023. Through manual analysis of the compiled security incidents, we have classified them into 12 major categories. Then we explored potential solutions and mitigation strategies. Drawing from these analyses, we established the first NFT security reference frame. Except, we extracted the characteristics of NFT security issues, i.e., the prevalence, severity, and intractability. We have indicated the gap between industry and academy for NFT security, and provide further research directions for the community. This paper, as the first SoK of NFT security, has systematically explored the security issues within the NFT ecosystem, shedding light on their root causes, real-world attacks, and potential ways to address them. Our findings will contribute to the future research of NFT security.

Rule-based models, e.g., decision trees, are widely used in scenarios demanding high model interpretability for their transparent inner structures and good model expressivity. However, rule-based models are hard to optimize, especially on large data sets, due to their discrete parameters and structures. Ensemble methods and fuzzy/soft rules are commonly used to improve performance, but they sacrifice the model interpretability. To obtain both good scalability and interpretability, we propose a new classifier, named Rule-based Representation Learner (RRL), that automatically learns interpretable non-fuzzy rules for data representation and classification. To train the non-differentiable RRL effectively, we project it to a continuous space and propose a novel training method, called Gradient Grafting, that can directly optimize the discrete model using gradient descent. A novel design of logical activation functions is also devised to increase the scalability of RRL and enable it to discretize the continuous features end-to-end. Exhaustive experiments on ten small and four large data sets show that RRL outperforms the competitive interpretable approaches and can be easily adjusted to obtain a trade-off between classification accuracy and model complexity for different scenarios. Our code is available at: https://github.com/12wang3/rrl., Comment: Accepted by IEEE TPAMI in October 2023; Interpretable ML; Neuro-Symbolic AI; Preliminary conference version (NeurIPS 2021) available at arXiv:2109.15103