A Review on the Application of 3D Printing Technology in Pavement Maintenance

To examine the application and significance of 3D printing technology in pavement maintenance engineering, a review of the current developments in principles, types, materials, and equipment for 3D printing was conducted. A comparison and analysis of traditional methods and 3D printing for asphalt pavement maintenance led to an investigation of 3D asphalt printing technologies and equipment. As a result, the following suggestions and conclusions are proposed: 3D printing technology can increase the level of automation and standardization of pavement maintenance engineering, leading to effective improvements in worker safety, climate adaptability, repair accuracy, etc. For on-site repair of cracks and minor potholes, utilizing material extrusion technology a mobile 3D asphalt printing robot with a screw extrusion device can be used for accuracy and flexibility. For efficient repair of varying cracks, material jetting technology with a UAV equipped with a 3D printing air-feeding device can be employed

Constraints on peculiar velocity distribution of binary black holes using gravitational waves with GWTC-3

The peculiar velocity encodes rich information about the formation, dynamics, evolution, and merging history of binary black holes. In this work, we employ a hierarchical Bayesian model to infer the peculiar velocity distribution of binary black holes for the first time using GWTC-3 by assuming a Maxwell-Boltzmann distribution for the peculiar velocities. The constraint on the peculiar velocity distribution parameter is rather weak and uninformative with the current GWTC-3 data release. However, the measurement of the peculiar velocity distribution can be significantly improved with the next-generation ground-based gravitational wave detectors. For instance, the uncertainty on the peculiar velocity distribution parameter will be measured within $\sim$ 10\% with $10^3$ golden binary black hole events for the Einstein Telescope. We, therefore, conclude that our statistical approach provides a robust inference for the peculiar velocity distribution.Comment: 15 pages, 2 figures

Strongly enhanced light-matter interaction in a hybrid photonic-plasmonic resonator

We propose a hybrid photonic-plasmonic resonant structure which consists of a metal nanoparticle (MNP) and a whispering gallery mode (WGM) microcavity. It is found that the hybrid mode enables a strong interaction between the light and matter, and the single-atom cooperativity is enhanced by more than two orders of magnitude compared to that in a bare WGM microcavity. This remarkable improvement originates from two aspects: (1) the MNP offers a highly enhanced local field in the vicinity of an emitter, and (2), surprisingly, the high-\textit{Q} property of WGMs can be maintained in the presence of the MNP. Thus the present system has great advantages over a single microcavity or a single MNP, and holds great potential in quantum optics, nonlinear optics and highly sensitive biosening.Comment: 5 pages, 4 figure

Elevated alanine transaminase is nonlinearly associated with in-hospital death in ICU-admitted diabetic ketoacidosis patients

Aims: To investigate the association between alanine transaminase (ALT) and in-hospital death in patients admitted to the intensive care unit for diabetic ketoacidosis (DKA). Methods: A cohort of 2,684 patients was constructed from the eICU Collaborative Research Database. Baseline demographic and clinical characteristics were summarized. Cox regression with restricted cubic spline functions was modelled to explore the nonlinear association between alanine transaminase and in-hospital death. Subgroup analyses were conducted between sexes, age groups, and people with/without obesity. Results: After adjusting multiple confounders, a nonlinear, S-shaped association between ALT and in-hospital death was found. Compared to patients at median ALT, patients at the 90th percentile of ALT have a 1.88 (95% CI: 1.34–2.62) times higher hazard of in-hospital death in the unstratified cohort. Similar results were found in males (hazard ratio (HR)=1.69, 95% confidence interval (CI): 1.24–2.30); patients aged under 65 years (HR=1.65, 95% CI: 1.09–2.49); patients aged 65 years or above (HR=3.45, 95% CI: 1.67–7.14); non-obese patients (HR=1.52, 95% CI: 1.00–2.32); and obese patients (HR=2.76, 95% CI: 1.38–5.54). Conclusions: Elevated ALT is robustly associated with in-hospital death in ICU-admitted DKA patients across several subgroups. Close monitoring of ALT in these patients is recommended

Ship Hull Principal Dimensions Optimization Employing Fuzzy Decision-Making Theory

The paper presents an optimization method for the ship hull principal dimensions scheme employing the fuzzy decision-making theory. First of all, the paper establishes the fuzzy decision-making model of the ship hull principal dimensions optimization, and then a series of ship hull principal dimensions schemes are accordingly constructed by employing the variable value method. On the basis of this, the fuzzy decision-making method is employed to evaluate the series ship hull principal dimensions schemes. Finally, the optimal ship hull principal dimensions scheme is obtained. The example demonstration verified the proposed method’s validity for ship hull principal dimensions optimization economic performance

Detection of spin bias in four-terminal quantum-dot ring

In this work, we show that in a four-quantum-dot ring, via introducing a local Rashba spin-orbit interaction the spin bias in the transverse terminals can be detected by observing the charge currents in the longitudinal probes. It is found that due to the Rashba interaction, the quantum interference in this system becomes spin-dependent and the opposite-spin currents induced by the spin bias can present different magnitudes, so charge currents emerge. Besides, the charge currents rely on both the magnitude and spin polarization direction of the spin bias. It is believed that this method provides an electrical but practical scheme to detect the spin bias (or the spin current).Comment: 6 pages, 5 figure

Federated Learning of Shareable Bases for Personalization-Friendly Image Classification

Personalized federated learning (PFL) aims to harness the collective wisdom of clients' data while building personalized models tailored to individual clients' data distributions. Existing works offer personalization primarily to clients who participate in the FL process, making it hard to encompass new clients who were absent or newly show up. In this paper, we propose FedBasis, a novel PFL framework to tackle such a deficiency. FedBasis learns a set of few shareable ``basis'' models, which can be linearly combined to form personalized models for clients. Specifically for a new client, only a small set of combination coefficients, not the model weights, needs to be learned. This notion makes FedBasis more parameter-efficient, robust, and accurate than competitive PFL baselines, especially in the low data regime, without increasing the inference cost. To demonstrate the effectiveness and applicability of FedBasis, we also present a more practical PFL testbed for image classification, featuring larger data discrepancies across clients in both the image and label spaces as well as more faithful training and test splits.Comment: Preprin

Discrete approximate optimal vibration control for nonlinear vehicle active suspension

This paper presents the approximate optimal vibration control methodology for discrete nonlinear vehicle active suspension subject to persistent road disturbances. Based on a dynamic model of nonlinear vehicle active suspension and a linear exogenous system model of the persistent road disturbances, a nonlinear two-point boundary value (TPBV) problem is introduced. By introducing a sensitive parameter, the original TPBV problem is reformed as a series of TPBV problems without nonlinear items. A discrete approximate optimal vibration controller (DAOVC) can be obtained by solving a Riccati equation, Stein equation, and nonlinear compensation item, respectively. An iteration algorithm is designed to realize the computational realizability of DAOVC based on the control performance. It is demonstrated that the control performance of ride comfort, road holding ability, and suspension deflection under the DAOVC are much smaller than the ones under the classical feedforward and feedback optimal vibration controller (FFOVC) and open-loop vehicle suspension system