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With their high-fidelity scene representation capability, the attention of SLAM field is deeply attracted by the Neural Radiation Field (NeRF) and 3D Gaussian Splatting (3DGS). Recently, there has been a surge in NeRF-based SLAM, while 3DGS-based SLAM is sparse. A novel 3DGS-based SLAM approach with a fusion of deep visual feature, dual keyframe selection and 3DGS is presented in this paper. Compared with the existing methods, the proposed tracking is achieved by feature extraction and motion filter on each frame. The joint optimization of poses and 3D Gaussians runs through the entire mapping process. Additionally, the coarse-to-fine pose estimation and compact Gaussian scene representation are implemented by dual keyframe selection and novel loss functions. Experimental results demonstrate that the proposed algorithm not only outperforms the existing methods in tracking and mapping, but also has less memory usage.

In this paper, we construct exact solutions that character three-dimensional, nonlinear trapped lee waves propagation superimposed on longitudinal atmospheric currents in the $\beta$-plane approximation. The solutions obtained are presented in Lagrangian coordinates, and are Gerstner-like solutions. In the process, we also derive the dispersion relation and analyze the density, pressure and the vorticity qualitatively.

Industrial Cyber-Physical Systems (ICPS) integrate the disciplines of computer science, communication technology, and engineering, and have emerged as integral components of contemporary manufacturing and industries. However, ICPS encounters various challenges in long-term operation, including equipment failures, performance degradation, and security threats. To achieve efficient maintenance and management, prognostics and health management (PHM) finds widespread application in ICPS for critical tasks, including failure prediction, health monitoring, and maintenance decision-making. The emergence of large-scale foundation models (LFMs) like BERT and GPT signifies a significant advancement in AI technology, and ChatGPT stands as a remarkable accomplishment within this research paradigm, harboring potential for General Artificial Intelligence. Considering the ongoing enhancement in data acquisition technology and data processing capability, LFMs are anticipated to assume a crucial role in the PHM domain of ICPS. However, at present, a consensus is lacking regarding the application of LFMs to PHM in ICPS, necessitating systematic reviews and roadmaps to elucidate future directions. To bridge this gap, this paper elucidates the key components and recent advances in the underlying model.A comprehensive examination and comprehension of the latest advances in grand modeling for PHM in ICPS can offer valuable references for decision makers and researchers in the industrial field while facilitating further enhancements in the reliability, availability, and safety of ICPS., Comment: Authors of the paper to be re-established

Monolithic integration of novel materials for unprecedented device functions without modifying the existing photonic component library is the key to advancing heterogeneous silicon photonic integrated circuits. To achieve this, the introduction of a silicon nitride etching stop layer at selective area, coupled with low-loss oxide trench to waveguide surface, enables the incorporation of various functional materials without disrupting the reliability of foundry-verified devices. As an illustration, two distinct chalcogenide phase change materials (PCM) with remarkable nonvolatile modulation capabilities, namely Sb2Se3 and Ge2Sb2Se4Te1, were monolithic back-end-of-line integrated into silicon photonics. The PCM enables compact phase and intensity tuning units with zero-static power consumption. Taking advantage of these building blocks, the phase error of a push-pull Mach-Zehnder interferometer optical switch could be trimmed by a nonvolatile phase shifter with a 48% peak power consumption reduction. Mirco-ring filters with a rejection ratio >25dB could be applied for >5-bit wavelength selective intensity modulation, and waveguide-based >7-bit intensity-modulation photonic attenuators could achieve >39dB broadband attenuation. The advanced "Zero change" back-end-of-line integration platform could not only facilitate the integration of PCMs for integrated reconfigurable photonics but also open up the possibilities for integrating other excellent optoelectronic materials in the future silicon photonic process design kits., Comment: 20 pages, 4 figures, submitted to Nature Photonics

Optical neural networks (ONNs) herald a new era in information and communication technologies and have implemented various intelligent applications. In an ONN, the activation function (AF) is a crucial component determining the network performances and on-chip AF devices are still in development. Here, we first demonstrate on-chip reconfigurable AF devices with phase activation fulfilled by dual-functional graphene/silicon (Gra/Si) heterojunctions. With optical modulation and detection in one device, time delays are shorter, energy consumption is lower, reconfigurability is higher and the device footprint is smaller than other on-chip AF strategies. The experimental modulation voltage (power) of our Gra/Si heterojunction achieves as low as 1 V (0.5 mW), superior to many pure silicon counterparts. In the photodetection aspect, a high responsivity of over 200 mA/W is realized. Special nonlinear functions generated are fed into a complex-valued ONN to challenge handwritten letters and image recognition tasks, showing improved accuracy and potential of high-efficient, all-component-integration on-chip ONN. Our results offer new insights for on-chip ONN devices and pave the way to high-performance integrated optoelectronic computing circuits.

In this paper, we aim to derive an exact solution to the three-dimensional governing equations for wind-induced equatorial flows in the $\beta$-plane approximation with a depth-dependent density distribution and subjected to centripetal terms. The obtained explicit solution represents a steady purely azimuthal stratified flow with a flat surface and an impermeable flat bed that is suitable for describing the Equatorial Current. Resorting to a functional analysis, we show that the thermocline exhibits some monotonicity properties.

A Hamiltonian model for the propagation of internal water waves interacting with surface waves, a current and an uneven bottom is examined. Using the so-called Dirichlet-Neumann operators, the water wave system is expressed in the Hamiltonian form, and thus the motions of the internal waves and surface waves are determined by the Hamiltonian formulation. Choosing an appropriate scaling of the variables and employing the Hamiltonian perturbation theory from Hamiltonian formulation of the dynamics, we derive a KdV-type equation with variable coefficients depending on the bottom topography to describe the internal waves.