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A transport PDE with a spatial integral and recirculation with constant delay has been a benchmark for neural operator approximations of PDE backstepping controllers. Introducing a spatially-varying delay into the model gives rise to a gain operator defined through integral equations which the operator's input -- the varying delay function -- enters in previously unencountered manners, including in the limits of integration and as the inverse of the `delayED time' function. This, in turn, introduces novel mathematical challenges in estimating the operator's Lipschitz constant. The backstepping kernel function having two branches endows the feedback law with a two-branch structure, where only one of the two feedback branches depends on both of the kernel branches. For this rich feedback structure, we propose a neural operator approximation of such a two-branch feedback law and prove the approximator to be semiglobally practically stabilizing. With numerical results we illustrate the training of the neural operator and its stabilizing capability., Comment: This 14 page paper contains 1 table and 20 figures

During the early stages of respiratory virus outbreaks, such as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the efficient utilize of limited nasopharyngeal swabs for rapid and accurate screening is crucial for public health. In this study, we present a methodology that integrates attenuated total reflection-Fourier transform infrared spectroscopy (ATR-FTIR) with the adaptive iteratively reweighted penalized least squares (airPLS) preprocessing algorithm and a channel-wise attention-based partial least squares one-dimensional convolutional neural network (PLS-1D-CNN) model, enabling accurate screening of infected individuals within 10 minutes. Two cohorts of nasopharyngeal swab samples, comprising 126 and 112 samples from suspected SARS-CoV-2 Omicron variant cases, were collected at Beijing You'an Hospital for verification. Given that ATR-FTIR spectra are highly sensitive to variations in experimental conditions, which can affect their quality, we propose a biomolecular importance (BMI) evaluation method to assess signal quality across different conditions, validated by comparing BMI with PLS-GBM and PLS-RF results. For the ATR-FTIR signals in cohort 2, which exhibited a higher BMI, airPLS was utilized for signal preprocessing, followed by the application of the channel-wise attention-based PLS-1D-CNN model for screening. The experimental results demonstrate that our model outperforms recently reported methods in the field of respiratory virus spectrum detection, achieving a recognition screening accuracy of 96.48%, a sensitivity of 96.24%, a specificity of 97.14%, an F1-score of 96.12%, and an AUC of 0.99. It meets the World Health Organization (WHO) recommended criteria for an acceptable product: sensitivity of 95.00% or greater and specificity of 97.00% or greater for testing prior SARS-CoV-2 infection in moderate to high volume scenarios.

Continuous, long-term monitoring of hazardous, noxious, explosive, and flammable gases in industrial environments using electronic nose (E-nose) systems faces the significant challenge of reduced gas identification accuracy due to time-varying drift in gas sensors. To address this issue, we propose a novel unsupervised attention-based multi-source domain shared-private feature fusion adaptation (AMDS-PFFA) framework for gas identification with drift compensation in E-nose systems. The AMDS-PFFA model effectively leverages labeled data from multiple source domains collected during the initial stage to accurately identify gases in unlabeled gas sensor array drift signals from the target domain. To validate the model's effectiveness, extensive experimental evaluations were conducted using both the University of California, Irvine (UCI) standard drift gas dataset, collected over 36 months, and drift signal data from our self-developed E-nose system, spanning 30 months. Compared to recent drift compensation methods, the AMDS-PFFA model achieves the highest average gas recognition accuracy with strong convergence, attaining 83.20% on the UCI dataset and 93.96% on data from our self-developed E-nose system across all target domain batches. These results demonstrate the superior performance of the AMDS-PFFA model in gas identification with drift compensation, significantly outperforming existing methods.

Thermoelectric materials can be designed to support optical resonances across multiple spectral ranges to enable ultra-wide band photodetection. For instance, antimony telluride (Sb2Te3) chalcogenide exhibits interband plasmonic resonances in the visible range and Mie resonances in the mid-infrared (mid-IR) range, while simultaneously possessing large thermoelectric Seebeck coefficients. In this paper, we designed and fabricated Sb2Te3 metasurface devices to achieve resonant absorption for enabling photodetectors operating across an ultra-wideband spectrum, from visible to mid-IR. Furthermore, relying on asymmetric Sb2Te3 metasurface, we demonstrated the thermoelectric photodetectors with polarization-selectivity. This work provides a potential platform towards the portable ultrawide band spectrometers at room temperature, for environmental sensing applications.

This study investigates the substitution of cerium (Ce) with mischmetal (MM) in cast Al-MM alloys, focusing on microstructure, hardness, tensile and compression properties, creep resistance, and coarsening resistance. Al-MM alloys with various MM compositions (Ce, Ce-50La, Ce-33La, and Ce-27La-19Nd, weight percent) exhibit near-eutectic and hyper-eutectic microstructures for Al-9MM and Al-12MM compositions, respectively, with similar as-cast hardness (~525 MPa). All Al-9MM alloys show tensile yield stress ~55 MPa, ultimate tensile strength ~130 MPa, and fracture strain ~8%.The microstructural and mechanical properties consistency demonstrates the flexibility of MM compositions in Al-MM alloys. Al-9MM exhibits excellent coarsening resistance, with minimal hardness reduction when exposed to 300 and 350 C for up to 11 weeks, and a modest ~15% hardness reduction at 400 C for 8 weeks, outperforming eutectic Al-12.6Si and Al-6.4Ni alloys. Additionally, Al-9MM shows higher creep resistance at 300 C compared to most precipitate-strengthened Al-Sc-Zr and solid-solution-strengthened Al-Mg/Mn alloys, but is outperformed by eutectic-strengthened Al-6.4Ni and Al-10Ce-5Ni alloys.The effect of casting cooling rate is investigated through wedge casting: Al-9Ce transitions from hypo- to hyper-eutectic as cooling rates decrease, while Al-12Ce consistently shows hyper-eutectic microstructures. Al11Ce3 lamellae become finer and more closely spaced with increasing cooling rates. Al-9Ce maintains steady hardness at high to moderate cooling rates but shows reduced hardness at lower rates, whereas Al-12Ce shows no change in hardness.With a 15% reduction in energy consumption and CO2 emissions, Al-Ce alloys where Ce is replaced with MM offer comparable mechanical properties and enhanced environmental benefits, highlighting the potential of MM as a sustainable alternative., Comment: 21 pages, 9 figures, 2 tables

Identifying gene splicing is a core and significant task confronted in modern collaboration between artificial intelligence and bioinformatics. Past decades have witnessed great efforts on this concern, such as the bio-plausible splicing pattern AT-CG and the famous SpliceAI. In this paper, we propose a novel framework for the task of gene splicing identification, named Horizon-wise Gene Splicing Identification (H-GSI). The proposed H-GSI follows the horizon-wise identification paradigm and comprises four components: the pre-processing procedure transforming string data into tensors, the sliding window technique handling long sequences, the SeqLab model, and the predictor. In contrast to existing studies that process gene information with a truncated fixed-length sequence, H-GSI employs a horizon-wise identification paradigm in which all positions in a sequence are predicted with only one forward computation, improving accuracy and efficiency. The experiments conducted on the real-world Human dataset show that our proposed H-GSI outperforms SpliceAI and achieves the best accuracy of 97.20\%. The source code is available from this link.

Among the most intriguing features of non-Hermitian (NH) systems is the ability of complex energies to form braids under parametric variation. Several braiding behaviors, including link and knot formation, have been observed in experiments on synthetic NH systems, such as looped optical fibers. The exact conditions for these phenomena remain unsettled, but existing demonstrations have involved long-range nonreciprocal hoppings, which are hard to implement on many experimental platforms. Here, we present a route to realizing complex energy braids using 1D NH Aubry-Andr\'e-Harper lattices. Under purely local gain and loss modulation, the eigenstates exhibit a variety of braiding behaviors, including unknots, Hopf links, trefoil knots, Solomon links and catenanes. We show how these are created by the interplay between non-Hermiticity and the lattice's bulk states and topological edge states. The transitions between different braids are marked by changes in the global Berry phase of the NH lattice.

The focus of this paper is to develop a methodology that enables an unmanned surface vehicle (USV) to efficiently track a planned path. The introduction of a vector field-based adaptive line of-sight guidance law (VFALOS) for accurate trajectory tracking and minimizing the overshoot response time during USV tracking of curved paths improves the overall line-of-sight (LOS) guidance method. These improvements contribute to faster convergence to the desired path, reduce oscillations, and can mitigate the effects of persistent external disturbances. It is shown that the proposed guidance law exhibits k-exponential stability when converging to the desired path consisting of straight and curved lines. The results in the paper show that the proposed method effectively improves the accuracy of the USV tracking the desired path while ensuring the safety of the USV work.