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A primary challenge in wireless power transfer (WPT) systems is to achieve efficient and stable power transmission without complex control strategies when load conditions change dynamically. Addressing this issue, we propose a third-order pseudo-Hermitian WPT system whose output characteristics exhibit a stable frequency and constant power. The frequency selection mechanism and energy efficiency of the nonlinear WPT system based on pseudo-Hermitian under the coupling mode theory approximation are analyzed. Theoretical analysis indicates that under certain coupling coefficients and load conditions, the proposed system can achieve frequency adaptation in a stable frequency mode without the need to change the circuit frequency. When the load changes dynamically, the stability of the power output is maintained using a proportional integral (PI) control strategy that only collects the voltage and current at the transmitting end, eliminating the need for wireless communication circuits with feedback from the receiving side. Experimental results demonstrate that the proposed design scheme can achieve constant power transmission when load conditions change, maintaining stable and relatively high transmission efficiency. The proposed scheme exhibits benefits in practical applications since no communication is required.

Directional wave speeds variations in anisotropic elastic solids enables material characterisation capabilities, such as determination of elastic constants and volumetric measurement of crystallographic texture. However, achieving such measurements is challenging especially on samples with complex geometries. Here we propose the use of Green's Function reconstruction from diffuse ultrasonic wave fields for accurate velocity measurements on components with arbitrary geometries. Strategies for accurate reconstruction, including averaging over an increased number of different source locations, using longer window lengths of diffuse fields, and accurately deconvolving a source-dependent factor, were implemented to achieve satisfactory convergence towards Green's Function. Additionally, low signal intensity challenges from laser interferometers were overcome to enable non-contact measurement of the wave speeds, by making use of simultaneous excitation of sources to increase signal-to-noise ratio and signal normalisation to account for energy dissipation of diffuse fields. With successful demonstration using both phased array and laser receivers, this advancement fundamentally broadens acoustic wave velocity measurement capabilities to a wider range of environments and holds promise for future material characterisation of complex-shaped components.

In recent years, the United States has witnessed a significant surge in the popularity of vaping or e-cigarette use, leading to a notable rise in cases of e-cigarette and vaping use-associated lung injury (EVALI) that caused hospitalizations and fatalities during the EVALI outbreak in 2019, highlighting the urgency to comprehend vaping behaviors and develop effective strategies for cessation. Due to the ubiquity of social media platforms, over 4.7 billion users worldwide use them for connectivity, communications, news, and entertainment with a significant portion of the discourse related to health, thereby establishing social media data as an invaluable organic data resource for public health research. In this study, we extracted a sample dataset from one vaping sub-community on Reddit to analyze users' quit-vaping intentions. Leveraging OpenAI's latest large language model GPT-4 for sentence-level quit vaping intention detection, this study compares the outcomes of this model against layman and clinical expert annotations. Using different prompting strategies such as zero-shot, one-shot, few-shot and chain-of-thought prompting, we developed 8 prompts with varying levels of detail to explain the task to GPT-4 and also evaluated the performance of the strategies against each other. These preliminary findings emphasize the potential of GPT-4 in social media data analysis, especially in identifying users' subtle intentions that may elude human detection., Comment: Accepted for the AI Applications in Public Health and Social Services workshop at the 22nd International Conference on Artificial Intelligence in Medicine (AIME 2024)

The Jinping neutrino experiment is designed to have multiple purposes in the China Jinping Underground Laboratory. Following the acrylic vessel design requirements proposal, a structural scheme has been developed and optimized. Subsequently, the stability of the acrylic shell structure was calculated using finite element analysis, as well as the load-bearing capacities under various working conditions. Further, the effects of temperature changes, rope failures, and Young's modulus of the ropes on the static behavior of the structure were analyzed. The results indicated that the stress level and structural displacement of the structure scheme satisfies the design requirements, as well as the stability of the vessel under compression. Moreover, the stress and displacement of the acrylic shell satisfies the given working conditions and temperatures. The structural scheme ensures basic safety if the rope fails., Comment: 27 pages, 11 figures,7 tables

In this work, we calculated the form factors of the weak decay process $\Lambda_b^0 \to \Lambda_c(2595)^+$, where the final charm baryon represents an excited state with spin-parity $\frac{1}{2}^-$. Utilizing the light-cone QCD sum rules approach, we incorporated the contributions of the lowest two charm baryon states: the ground state $\Lambda_c$ with $J^P=\frac{1}{2}^+$ and the excited state $\Lambda_c(2595)^+$ with $J^P=\frac{1}{2}^-$ in the hadronic representation of the $\Lambda_b$ to $\Lambda_c(2595)$ transition correlation function. This approach allowes us to extract the form factors of the $\Lambda_b^0 \to \Lambda_c(2595)^+$ from $\Lambda_b^0 \to \Lambda_c^+$ transition. During the light-cone QCD sum rules procedure, we employed the light-cone distribution amplitudes (LCDAs) of the $\Lambda_b$ baryon. Furthermore, by combining these form factors with the helicity amplitudes of the bottom baryon transition matrix elements, we calculated the differential decay widths for the processes $\Lambda_b^0 \to \Lambda_c(2595)^+\ell^-\bar{\nu}_\ell$. Additionally, within the lifetime of $\Lambda_b^0$, we obtained the absolute branching fractions for the semileptonic decays $\Lambda_b^0 \to \Lambda_c(2595)^+ \ell^- \bar{\nu}_\ell$. With the branching fractions of $\Lambda_b^0 \to \Lambda_c(2595)^+ \ell^- \bar{\nu}_\ell$ calculated in this work, we also determined the parameter $\mathcal{R}(\Lambda_c(2595)^+)$ which tests the lepton flavor universality. This parameter is defined as the ratio of branching fractions $\mathcal{B}r(\Lambda_b^0 \to \Lambda_c(2595)^+\tau^-\bar{\nu}_\tau)$ and $\mathcal{B}r(\Lambda_b^0 \to \Lambda_c(2595)^+\mu^-\bar{\nu}_\mu)$. Our results provide a valuable theoretical test for these decay channels and offer insights into the LCDAs of bottom baryons, paving the way for further in-depth investigations., Comment: 15 pages, 3 figures and 6 tables

Generative AI (GenAI) has spurred the expectation of being creative, due to its ability to generate content, yet so far, its creativity has somewhat disappointed, because it is trained using existing data following human intentions to generate outputs. The purpose of this paper is to explore what is required to evolve AI from generative to creative. Based on a reinforcement learning approach and building upon various research streams of computational creativity, we develop a triple prompt-response-reward engineering framework to develop the creative capability of GenAI. This framework consists of three components: 1) a prompt model for expected creativity by developing discriminative prompts that are objectively, individually, or socially novel, 2) a response model for observed creativity by generating surprising outputs that are incrementally, disruptively, or radically innovative, and 3) a reward model for improving creativity over time by incorporating feedback from the AI, the creator/manager, and/or the customers. This framework enables the application of GenAI for various levels of creativity strategically., Comment: 46 pages, 2 tables, 4 figures

The widespread adoption of social media platforms globally not only enhances users' connectivity and communication but also emerges as a vital channel for the dissemination of health-related information, thereby establishing social media data as an invaluable organic data resource for public health research. The surge in popularity of vaping or e-cigarette use in the United States and other countries has caused an outbreak of e-cigarette and vaping use-associated lung injury (EVALI), leading to hospitalizations and fatalities in 2019, highlighting the urgency to comprehend vaping behaviors and develop effective strategies for cession. In this study, we extracted a sample dataset from one vaping sub-community on Reddit to analyze users' quit vaping intentions. Leveraging large language models including both the latest GPT-4 and traditional BERT-based language models for sentence-level quit-vaping intention prediction tasks, this study compares the outcomes of these models against human annotations. Notably, when compared to human evaluators, GPT-4 model demonstrates superior consistency in adhering to annotation guidelines and processes, showcasing advanced capabilities to detect nuanced user quit-vaping intentions that human evaluators might overlook. These preliminary findings emphasize the potential of GPT-4 in enhancing the accuracy and reliability of social media data analysis, especially in identifying subtle users' intentions that may elude human detection.

Information Bottleneck (IB) is a widely used framework that enables the extraction of information related to a target random variable from a source random variable. In the objective function, IB controls the trade-off between data compression and predictiveness through the Lagrange multiplier $\beta$. Traditionally, to find the trade-off to be learned, IB requires a search for $\beta$ through multiple training cycles, which is computationally expensive. In this study, we introduce Flexible Variational Information Bottleneck (FVIB), an innovative framework for classification task that can obtain optimal models for all values of $\beta$ with single, computationally efficient training. We theoretically demonstrate that across all values of reasonable $\beta$, FVIB can simultaneously maximize an approximation of the objective function for Variational Information Bottleneck (VIB), the conventional IB method. Then we empirically show that FVIB can learn the VIB objective as effectively as VIB. Furthermore, in terms of calibration performance, FVIB outperforms other IB and calibration methods by enabling continuous optimization of $\beta$. Our codes are available at https://github.com/sotakudo/fvib.

We study the last fall degrees of {\em semi-local} polynomial systems, and the computational complexity of solving such systems for closed-point and rational-point solutions, where the systems are defined over a finite field. A semi-local polynomial system specifies an algebraic set which is the image of a global linear transformation of a direct product of local affine algebraic sets. As a special but interesting case, polynomial systems that arise from Weil restriction of algebraic sets in an affine space of low dimension are semi-local. Such systems have received considerable attention due to their application in cryptography. Our main results bound the last fall degree of a semi-local polynomial system in terms of the number of closed point solutions, and yield an efficient algorithm for finding all rational-point solutions when the prime characteristic of the finite field and the number of rational solutions are small. Our results on solving semi-local systems imply an improvement on a previously known polynomial-time attack on the HFE (Hidden Field Equations) cryptosystems. The attacks implied in our results extend to public key encryption functions which are based on semi-local systems where either the number of closed point solutions is small, or the characteristic of the field is small. It remains plausible to construct public key cryptosystems based on semi-local systems over a finite field of large prime characteristic with exponential number of closed point solutions. Such a method is presented in the paper, followed by further cryptanalysis involving the isomorphism of polynomials (IP) problem, as well as a concrete public key encryption scheme which is secure against all the attacks discussed in this paper.

With some explicitly $Z_3$ breaking terms in the NMSSM effective superpotential and scalar potential, domain walls (DWs) from spontaneously breaking of the discrete symmetry in approximate $Z_3$-invariant NMSSM can collapse and lead to observable stochastic gravitational wave (GW) background signals. In the presence of a hidden sector, such terms may originate from the geometric superconformal breaking with holomorphic quadratic correction to frame function when the global scale-invariant superpotential is naturally embedded into the canonical superconformal supergravity models. The smallness of such mass parameters in the NMSSM may be traced back to the original superconformal invariance. Naive estimations indicate that a SUSY explanation to muon $g-2$ anomaly can have tension with the constraints on SUSY by PTA data, because large SUSY contributions to $\Delta a_\mu$ in general needs relatively light superpartners while present $\Omega_{gw}^0$ can set the lower bounds for $m_{soft}$. We calculate numerically the signatures of GW produced from the collapse of DWs and find that the observed nHZ stochastic GW background by NANOGrav, etc., can indeed be explained with proper tiny values of $\chi m_{3/2}\sim 10^{-14}{\rm eV}$ for $\chi S^2$ case (and $\chi m_{3/2}\sim 10^{-10}{\rm eV}$ for $\chi H_u H_d$ case), respectively. Besides, there are still some parameter points, whose GW spectra intersect with the NANOGrav signal region, that can explain the muon $g-2$ anomaly to $1\sigma$ range., Comment: 33 pages, 6 figures, typos corrected, version published in PRD

The range and speed of a moving object can be ascertained using the sensing technique known as light detection and ranging (LiDAR). It has recently been suggested that quantum LiDAR, which uses entangled states of light, can enhance the capabilities of LiDAR. Entangled pulsed light is used in prior quantum LiDAR approaches to assess both range and velocity at the same time using the pulses' time of flight and Doppler shift. The entangled pulsed light generation and detection, which are crucial for pulsed quantum LiDAR, are often inefficient. Here, we study a quantum LiDAR that operates on a frequency-modulated continuous wave (FMCW), as opposed to pulses. We first outline the design of the quantum FMCW LiDAR using entangled frequency-modulated photons in a Mach-Zehnder interferometer, and we demonstrate how it can increase accuracy and resolution for range and velocity measurements by $\sqrt{n}$ and $n$, respectively, with $n$ entangled photons. We also demonstrate that quantum FMCW LiDAR may perform simultaneous measurements of the range and velocity without the need for quantum pulsed compression, which is necessary in pulsed quantum LiDAR. Since the generation of entangled photons is the only inefficient nonlinear optical process needed, the quantum FMCW LiDAR is better suited for practical implementations. Additionally, most measurements in the quantum FMCW LiDAR can be carried out electronically by down-converting optical signal to microwave region.

This paper presents theoretical and numerical models for the backscattering of 2D Rayleigh waves in single-phase, untextured polycrystalline materials with statistically equiaxed grains. The theoretical model, based on our prior inclusion-induced Rayleigh wave scattering model and the independent scattering approximation, considers single scattering of Rayleigh-to-Rayleigh (R-R) waves. The numerical finite element model is established to accurately simulate the scattering problem and evaluate the theoretical model. Good quantitative agreement is observed between the theoretical model and the finite element results, especially for weakly scattering materials. The agreement decreases with the increase of the anisotropy index, owing to the reduced applicability of the Born approximation. However, the agreement remains generally good when weak multiple scattering is involved. In addition, the R-R backscattering behaviour of 2D Rayleigh waves is similar to the longitudinal-to-longitudinal and transverse-to-transverse backscattering of bulk waves, with the former exhibiting stronger scattering. These findings establish a foundation for using Rayleigh waves in quantitative characterisation of polycrystalline materials., Comment: 18 pages, 10 figures

Discrete R symmetries always play an important role in low energy SUSY. The spontaneously broken of such discrete R symmetries, for example, by gaugino condensation, can lead to domain walls, which need to be either inflated away or collapse to avoid cosmic difficulties. We propose that explicitly R symmetry violation needed for collapse of domain walls can be the consequence of multiple sector SUSY breaking. The consistency constraints for the generation of non-problematic domain walls from gaugino condensation are discussed. We also study the emitted gravitational waves related to the collapse of domain walls. We find that, for SUSY breaking scale of order ${\cal O}(1)$ ${\rm GeV}$ in one of the sequestered sector (and also a low reheating temperature of order ${\rm MeV}$ if the reheating is not completed when the domain walls collapse), the peak frequency of gravitational waves emitted can lie at nHz. Such a low SUSY breaking scale can be consistency and natural in multiple sector SUSY breaking scenario. The GWs signal by NANOGrav could be a signal of such multiple sector SUSY breaking scenario and it may also indicate the existences of light goldstini at ${\rm eV}$ mass scale., Comment: 14 pages; typos corrected, references added