Deep Koopman Learning of Nonlinear Time-Varying Systems

A data-driven method is developed to approximate an nonlinear time-varying system (NTVS) by a linear time-varying system (LTVS), based on Koopman Operator and deep neural networks. Analysis on the approximation error in system states of the proposed method is investigated. It is further shown by simulation on a simple NTVS that the resulted LTVS approximate the NTVS very well with small approximation errors in states. Furthermore, simulations on a cartpole further show that optimal controller developed based on the achieved LTVS works very well to control the original NTVS

Investigation of Key Parameters for Hydraulic Optimization of an Inlet Duct Based on a Whole Waterjet Propulsion Pump System

The hydraulic performance of an inlet duct directly affects the overall performance of a waterjet propulsion system. Key parameters for the hydraulic optimization of the inlet duct are explored using the computational fluid dynamics (CFD) technology to improve the hydraulic performance of the waterjet propulsion system. In the CFD simulation and experiment, an inlet duct with different flow and geometric parameters is simulated. By comparing grid sensitivity and different turbulence models, a suitable grid size and a turbulence model are determined. The comparison between the numerical simulation and the experiment shows that the numerical results are reliable. The results of the calculation and analysis of different speed cases show that the ship speed affects the efficiency of the waterjet propulsion system. In particular, the system efficiency increases first and then decreases with an increase in the ship speed. Under the conditions of constant ship speed and rotational speed, the influence of the length and dip angle of the inlet duct on the waterjet propulsion system is investigated using a single factor method. The results show that the dip angle has an obvious effect on the hydraulic performance of the inlet duct, and an extremely small angle of inclination will lead to poor flow patterns in the inlet passage. When the length is approximately six times the inlet duct outlet diameter, and the dip angle is 30°–35°, the hydraulic performance of the waterjet propulsion pump system is satisfactory

Vibration reduction in ballasted track using ballast mat: Nnmerical and experimental evaluation by wheelset drop test

Ballast mats are considered as an effective solution for reducing vehicle-induced vibrations. However, the research on the vibration characteristics of each part of the ballasted track with a ballast mat is limited. In this study, the ballast mat vibration reduction effects are evaluated by numerical and experimental analysis using wheelset drop tests. A three-dimensional model consisting of a wheel, track and the contact between them is built using a rigid–flexible coupling method. The accuracy of the numerical model is verified by comparison with the finite element model in terms of the track receptance and phase angle. Comparisons show that the proposed model is in good agreement with the finite element model, which allows validating the flexible-body model. Moreover, the track dynamic performance in the presence and absence of the ballast mat is studied with the wheelset drop tests in both time and frequency domains. The results from the wheelset drop excitation tests show that the use of the ballast mat decreases the mid- and high-frequency track vibration by 13–17 dB but increases the low-frequency track vibration by 5–15 dB.info:eu-repo/semantics/publishedVersio

LanPose: Language-Instructed 6D Object Pose Estimation for Robotic Assembly

Comprehending natural language instructions is a critical skill for robots to cooperate effectively with humans. In this paper, we aim to learn 6D poses for roboticassembly by natural language instructions. For this purpose, Language-Instructed 6D Pose Regression Network (LanPose) is proposed to jointly predict the 6D poses of the observed object and the corresponding assembly position. Our proposed approach is based on the fusion of geometric and linguistic features, which allows us to finely integrate multi-modality input and map it to the 6D pose in SE(3) space by the cross-attention mechanism and the language-integrated 6D pose mapping module, respectively. To validate the effectiveness of our approach, an integrated robotic system is established to precisely and robustly perceive, grasp, manipulate and assemble blocks by language commands. 98.09 and 93.55 in ADD(-S)-0.1d are derived for the prediction of 6D object pose and 6D assembly pose, respectively. Both quantitative and qualitative results demonstrate the effectiveness of our proposed language-instructed 6D pose estimation methodology and its potential to enable robots to better understand and execute natural language instructions.Comment: 8 page

Dual blockage of STAT3 and ERK1/2 eliminates radioresistant GBM cells.

Radiotherapy (RT) is the major modality for control of glioblastoma multiforme (GBM), the most aggressive brain tumor in adults with poor prognosis and low patient survival rate. To improve the RT efficacy on GBM, the mechanism causing tumor adaptive radioresistance which leads to the failure of tumor control and lethal progression needs to be further elucidated. Here, we conducted a comparative analysis of RT-treated recurrent tumors versus primary counterparts in GBM patients, RT-treated orthotopic GBM tumors xenografts versus untreated tumors and radioresistant GBM cells versus wild type cells. The results reveal that activation of STAT3, a well-defined redox-sensitive transcriptional factor, is causally linked with GBM adaptive radioresistance. Database analysis also agrees with the worse prognosis in GBM patients due to the STAT3 expression-associated low RT responsiveness. However, although the radioresistant GBM cells can be resensitized by inhibition of STAT3, a fraction of radioresistant cells can still survive the RT combined with STAT3 inhibition or CRISPR/Cas9-mediated STAT3 knockout. A complementally enhanced activation of ERK1/2 by STAT3 inhibition is identified responsible for the survival of the remaining resistant tumor cells. Dual inhibition of ERK1/2 and STAT3 remarkably eliminates resistant GBM cells and inhibits tumor regrowth. These findings demonstrate a previously unknown feature ofSTAT3-mediated ERK1/2 regulation and an effective combination of two targets in resensitizing GBM to RT

Teleportation protocol with non-ideal conditional local operations

In the standard protocol for quantum teleportation, one assumes that Bob is able to perform ideal operations on his qubit. Here, we analyze the case in which some of these operations are more reliable than others. Moreover, we consider the channel shared by Alice and Bob as non-maximally entangled. In this context, the average fidelity of teleportation can be maximized by properly choosing the basis in which Alice performs her two-qubit measurement.Comment: 12 pages, 2 figures, RevTeX

Light-Induced TripletTriplet Electron Resonance Spectroscopy

We present a new technique, light-induced triplet-triplet electron resonance spectroscopy (LITTER), which measures the dipolar interaction between two photoexcited triplet states, enabling both the distance and angular distributions between the two triplet moieties to be determined on a nanometer scale. This is demonstrated for a model bis-porphyrin peptide that renders dipolar traces with strong orientation selection effects. Using simulations and density functional theory calculations, we extract distance distributions and relative orientations of the porphyrin moieties, allowing the dominant conformation of the peptide in a frozen solution to be identified. LITTER removes the requirement of current light-induced electron spin resonance pulse dipolar spectroscopy techniques to have a permanent paramagnetic moiety, becoming more suitable for in-cell applications and facilitating access to distance determination in unmodified macromolecular systems containing photoexcitable moieties. LITTER also has the potential to enable direct comparison with Förster resonance energy transfer and combination with microscopy inside cells

Piezo-photoelectronic coupling effect of BaTiO₃@TiO₂ nanowires for highly concentrated dye degradation

The induced built-in electric field by piezoelectric materials has proven to be one of the most effective strategies for modulating the charge-transfer pathway and inhibiting carrier recombination. In this work, a series of core-shell structured BaTiO3@TiO2 nanowires (BT@TiO2 NWs) heterojunctions were synthesized and the significant coupling effects between BaTiO3 (BT) and TiO2 resulted in surperior piezo-photocatalytic performance, which was demonstrated by three typical types of dyes with high concentrations. The degradation efficiency of 30 mg/L Rhodamine B (RhB), Methylene blue (MB) and Indigo Carmine (IC) solutions by 0.5 g/L BT@TiO2 NWs reached 99.5% in 75 min, 99.8% in 105 min and 99.7% in 45 min, respectively, which are much higher than piezo-photocatalysis systems reported before. To reveal the coupling mechanisms, photoelectrochemical measurements and band diagram analysis were carried out. The carrier concentration was increased from 2.28 × 1017 cm−3 to 4.91 × 1018 cm−3 and the lifetime of charges was improved from 50.37 ms to 60.98 ms due to the construction of a heterojunction between TiO2 and BT. It was proposed that the tilting and bending of the energy band caused by the introduction of a piezoelectric polarization can facilitate carrier separation both in the bulk phase and at the surfaces of semiconductors, resulting in outstanding piezo-photocatalytic properties for highly concentrated dye degradation. This work provides a universal catalyzer for highly concentrated dye degradation.</p