On wave diffraction of two-dimensional moonpools in a two-layer fluid with finite depth

This paper studies the wave diffraction problem of two-dimensional moonpools in a two-layer fluid by using domain decomposition scheme and the method of eigenfunction expansion. Wave exciting forces, free surface and internal wave elevations are computed and analyzed for both surface wave and internal wave modes. The present model is validated by comparing a limiting case with a single-layer fluid case. Both piston mode and sloshing mode resonances have been identified and analyzed. It is observed that, compared with the solutions in surface wave mode, the wave exciting forces in internal wave mode are much smaller, and show more peaks and valleys in low-frequency region. As the wave frequency increases, the bandwidth of sloshing mode resonances decreases. Extensive parametric studies have been performed to examine the effects of moonpool geometry and density stratification on the resonant wave motion and exciting forces. It is found that, for twin bodies with deep draft in surface wave mode, the decreasing density ratio has little effects on the sloshing mode resonance frequencies but can somehow suppress the horizontal wave exciting forces and surface wave elevations around piston mode resonance region. In addition, the presence of lower-layer fluid can lead to the reduction of piston mode resonance frequency

LIO-GVM: an Accurate, Tightly-Coupled Lidar-Inertial Odometry with Gaussian Voxel Map

This letter presents an accurate and robust Lidar Inertial Odometry framework. We fuse LiDAR scans with IMU data using a tightly-coupled iterative error state Kalman filter for robust and fast localization. To achieve robust correspondence matching, we represent the points as a set of Gaussian distributions and evaluate the divergence in variance for outlier rejection. Based on the fitted distributions, a new residual metric is proposed for the filter-based Lidar inertial odometry, which demonstrates an improvement from merely quantifying distance to incorporating variance disparity, further enriching the comprehensiveness and accuracy of the residual metric. Due to the strategic design of the residual metric, we propose a simple yet effective voxel-solely mapping scheme, which only necessities the maintenance of one centroid and one covariance matrix for each voxel. Experiments on different datasets demonstrate the robustness and accuracy of our framework for various data inputs and environments. To the benefit of the robotics society, we open source the code at https://github.com/Ji1Xingyu/lio_gvm

InstructMol: Multi-Modal Integration for Building a Versatile and Reliable Molecular Assistant in Drug Discovery

The rapid evolution of artificial intelligence in drug discovery encounters challenges with generalization and extensive training, yet Large Language Models (LLMs) offer promise in reshaping interactions with complex molecular data. Our novel contribution, InstructMol, a multi-modal LLM, effectively aligns molecular structures with natural language via an instruction-tuning approach, utilizing a two-stage training strategy that adeptly combines limited domain-specific data with molecular and textual information. InstructMol showcases substantial performance improvements in drug discovery-related molecular tasks, surpassing leading LLMs and significantly reducing the gap with specialized models, thereby establishing a robust foundation for a versatile and dependable drug discovery assistant

Multi-objective optimization of semi-submersible platforms using particle swam optimization algorithm based on surrogate model

An Innovative Semi-submersible platform Optimization Program (ISOP) has been developed to solve the multi-objective optimization problem for semi-submersible platforms (SEMI). Three types of SEMIs, including semi-submersible floating production unit (SEMI FPU), heave and vortex induced motion (VIM) suppressed semi-submersible (HVS) and semi-submersible floating drilling unit (SEMI FDU) are selected for case studies. The hydrodynamic performances of three types of semi-submersible platforms are analyzed by using panel method and Morison's equation. In order to improve the computing efficiency, the hydrodynamic performances for different hull forms during optimization process are estimated by the surrogate models, which are built by artificial neural network prediction method and Inverse Multi-Quadric (IMQ) radial basis function (RBF). The accuracy of surrogate models is ensured by performing leave-one-out cross validation (LOOCV). The most probable maximum (MPM) heave motion and total weight, representing the safety and economy, respectively, are chosen as the two objectives for optimization. The transverse metacentric height, the MPM surge motion, and the most probable minimum (MPMin) airgap are selected as constraints. Based on surrogate models, multi-objective particle swarm optimization (MOPSO) is employed to search for the Pareto-optimal solutions. A Computational Fluid Dynamics (CFD) tool is adopted to validate the proposed model for the prediction of the motion responses. By comparing the obtained Pareto-optimal solutions with the initial design using simple panel method plus Morison's equation, it is confirmed that the MPM heave motions for SEMI FPU, HVS and SEMI FDU can be suppressed by up to 12.68%, 11.92%, and 14.96%, respectively, and the total weights can be reduced by up to 12.16%, 13.00%, and 24.91%, respectively. Through the detailed analyses of optimization results, the most efficient design strategies for semi-submersible platforms are discussed and proposed

Quartz sand surface morphology of granitic tafoni at Laoshan, China

43-48In this study, a SEM method was used to analyze the surface morphology of the quartz sand granitic tafoni at Laoshan, for the purpose of exploring the weathering process of this tafoni. Present study showed that granitic tafoni at Laoshan, the quartz sand roundness was dominated by angular and sub-angular morphologies. Massive Hydrodynamic features had been developed on the quartz sand surfaces, as well as wind and chemistry forms, which were more developed. It was determined that granitic tafoni at Laoshan, the quartz sand had suffered long-term rainy and windy mechanical erosion, as well as chemical dissolution from residual pit water. These findings differed from the earlier views that the tafone was formed by the glacial melt water

Neutron Energy Spectrum Measurements with a Compact Liquid Scintillation Detector on EAST

A neutron detector based on EJ301 liquid scintillator has been employed at EAST to measure the neutron energy spectrum for D-D fusion plasma. The detector was carefully characterized in different quasi-monoenergetic neutron fields generated by a 4.5 MV Van de Graaff accelerator. In recent experimental campaigns, due to the low neutron yield at EAST, a new shielding device was designed and located as close as possible to the tokamak to enhance the count rate of the spectrometer. The fluence of neutrons and gamma-rays was measured with the liquid neutron spectrometer and was consistent with 3He proportional counter and NaI (Tl) gamma-ray spectrometer measurements. Plasma ion temperature values were deduced from the neutron spectrum in discharges with lower hybrid wave injection and ion cyclotron resonance heating. Scattered neutron spectra were simulated by the Monte Carlo transport Code, and they were well verified by the pulse height measurements at low energies.Comment: 19 pages,10 figures, 1 tabl

The combination of bioactive herbal compounds with biomaterials for regenerative medicine

Regenerative medicine aims to restore the function of diseased or damaged tissues and organs by cell therapy, gene therapy, and tissue engineering, along with the adjunctive application of bioactive molecules. Traditional bioactive molecules, such as growth factors and cytokines, have shown great potential in the regulation of cellular and tissue behavior, but have the disadvantages of limited source, high cost, short half-life, and side effects. In recent years, herbal compounds extracted from natural plants/herbs have gained increasing attention. This is not only because herbal compounds are easily obtained, inexpensive, mostly safe, and reliable, but also owing to their excellent effects, including anti-inflammatory, antibacterial, antioxidative, proangiogenic behavior and ability to promote stem cell differentiation. Such effects also play important roles in the processes related to tissue regeneration. Furthermore, the moieties of the herbal compounds can form physical or chemical bonds with the scaffolds, which contributes to improved mechanical strength and stability of the scaffolds. Thus, the incorporation of herbal compounds as bioactive molecules in biomaterials is a promising direction for future regenerative medicine applications. Herein, an overview on the use of bioactive herbal compounds combined with different biomaterial scaffolds for regenerative medicine application is presented. We first introduce the classification, structures, and properties of different herbal bioactive components and then provide a comprehensive survey on the use of bioactive herbal compounds to engineer scaffolds for tissue repair/regeneration of skin, cartilage, bone, neural, and heart tissues. Finally, we highlight the challenges and prospects for the future development of herbal scaffolds toward clinical translation. Overall, it is believed that the combination of bioactive herbal compounds with biomaterials could be a promising perspective for the next generation of regenerative medicine