A novel type of hybrid ultrasonic motor using longitudinal and torsional vibration modes with side panels

A novel type of hybrid ultrasonic motor using longitudinal and torsional vibration modes is presented, which has four side panels uniformly distributed along the circumference of the stator cylinder. There is rectangle piezoelectric ceramics (PZTs) based on d31 effect bonded on both sides of each side panels, which can be used to convert the first bending vibration mode of the side panels into the second torsional vibration mode of the stator when the exciting voltage is applied. Meanwhile, there are rectangle PZTs based on d31 effect bonded on the surfaces of the stator cylinder between every two side panels, which can be used to excite the first longitudinal vibration mode of the stator. The simulation results using finite element method (FEM) software Workbench reveals the suitable polarization arrangement of PZTs and the final designed structure of the motor. The appearance size of the prototype is 28.2 mm×28.2 mm×68 mm, while the outer diameter of the stator cylinder is 20 mm. The major vibration and mechanical characteristics of the prototype have been measured. The working frequency of the prototype measured in experiment is around 43.12 kHz, which is consistent with the numerical results. When operating voltage of 350 Vp-p is applied, the no-load speed of the prototype is 103 rpm and the stalling torque is 48 mN·m

Mode of anesthesia for cesarean delivery with pernicious placenta previa — a retrospective study

Objectives: Anesthesia for cesarean delivery in parturients diagnosed with pernicious placenta previa remains controversial. This study aimed to review pernicious placenta previa cases to evaluate anesthetic management strategies. Material and methods: This retrospective analysis included patients who underwent cesarean delivery (CD) for pernicious placenta previa at the Affiliated Hospital of Zunyi Medical University between December 1, 2012 and November 31, 2017. Patient demographic data, obstetric characteristics, anesthetic management, and maternal outcomes were extracted from the hospital’s computerized database. Results: In all, 61 consecutive cases of pernicious placenta previa were identified among 9512 cesarean deliveries. General anesthesia was performed on 27 of the 61 patients (44.3%). Among GA group, 16 (59.3%) had placenta accreta, 8 of whom required cesarean hysterectomy. Also, 13 of the 27 (48.1%) GA patients required transfer to the intensive care unit. The other 34 patients (55.7%) were given regional anesthesia, 9 of whom were converted to general anesthesia due to excessive bleeding and prolonged operation times. Statistical results indicated that regional anesthesia was associated with a significantly shorter operation time, less perioperative blood loss, fewer intraoperative red blood cell transfusions, and a lower incidence of complications. Conclusions: Anesthetic management is important for parturients with pernicious placenta previa. Although regional anesthesia was our preferred method for these patients, general anesthesia is safe for patients with pernicious placenta previa who experience massive blood loss and prolonged operation times

Polarization-entangled photon pair sources based on spontaneous four wave mixing assisted by polarization mode dispersion

Photonic-based qubits and integrated photonic circuits have enabled demonstrations of quantum information processing (QIP) that promises to transform the way in which we compute and communicate. To that end, sources of polarization-entangled photon pair states are an important enabling technology, especially for polarization-based protocols. However, such states are difficult to prepare in an integrated photonic circuit. Scalable semiconductor sources typically rely on nonlinear optical effects where polarization mode dispersion (PMD) degrades entanglement. Here, we directly generate polarization-entangled states in an AlGaAs waveguide, aided by the PMD and without any compensation steps. We perform quantum state tomography and report a raw concurrence as high as 0.91$\pm$0.01 observed in the 1100-nm-wide waveguide. The scheme allows direct Bell state generation with an observed maximum fidelity of 0.90$\pm$0.01 from the 800-nm-wide waveguide. Our demonstration paves the way for sources that allow for the implementation of polarization-encoded protocols in large-scale quantum photonic circuits

Towards a General Framework for Continual Learning with Pre-training

In this work, we present a general framework for continual learning of sequentially arrived tasks with the use of pre-training, which has emerged as a promising direction for artificial intelligence systems to accommodate real-world dynamics. From a theoretical perspective, we decompose its objective into three hierarchical components, including within-task prediction, task-identity inference, and task-adaptive prediction. Then we propose an innovative approach to explicitly optimize these components with parameter-efficient fine-tuning (PEFT) techniques and representation statistics. We empirically demonstrate the superiority and generality of our approach in downstream continual learning, and further explore the applicability of PEFT techniques in upstream continual learning. We also discuss the biological basis of the proposed framework with recent advances in neuroscience.Comment: This is a generalized version of our HiDe-Prompt and will be presented in the IMOL workshop in NeurIPS 2023. arXiv admin note: text overlap with arXiv:2310.0723

Precise Orbit and Clock Products of Galileo, BDS and QZSS from MGEX Since 2018: Comparison and PPP Validation

In recent years, the development of new constellations including Galileo, BeiDou Navigation Satellite System (BDS) and Quasi-Zenith Satellite System (QZSS) have undergone dramatic changes. Since January 2018, about 30 satellites of the new constellations have been launched and most of the new satellites have been included in the precise orbit and clock products provided by the Multi Global Navigation Satellite System (Multi-GNSS) Experiment (MGEX). Meanwhile, critical issues including antenna parameters, yaw-attitude models and solar radiation pressure models have been continuously refined for these new constellations and updated into precise MGEX orbit determination and precise clock estimation solutions. In this context, MGEX products since 2018 are herein assessed by orbit and clock comparisons among individual analysis centers (ACs), satellite laser ranging (SLR) validation and precise point positioning (PPP) solutions. Orbit comparisons showed 3D agreements of 3–5 cm for Galileo, 8–9 cm for BDS-2 inclined geosynchronous orbit (IGSO), 12–18 cm for BDS-2 medium earth orbit (MEO) satellites, 24 cm for BDS-3 MEO and 11–16 cm for QZSS IGSO satellites. SLR validations demonstrated an orbit accuracy of about 3–4 cm for Galileo and BDS-2 MEO, 5–6 cm for BDS-2 IGSO, 4–6 cm for BDS-3 MEO and 5–10 cm for QZSS IGSO satellites. Clock products from different ACs generally had a consistency of 0.1–0.3 ns for Galileo, 0.2–0.5 ns for BDS IGSO/MEO and 0.2–0.4 ns for QZSS satellites. The positioning errors of kinematic PPP in Galileo-only mode were about 17–19 mm in the north, 13–16 mm in the east and 74–81 mm in the up direction, respectively. As for BDS-only PPP, positioning accuracies of about 14, 14 and 49 mm could be achieved in kinematic mode with products from Wuhan University applied

ViewFool: Evaluating the Robustness of Visual Recognition to Adversarial Viewpoints

Recent studies have demonstrated that visual recognition models lack robustness to distribution shift. However, current work mainly considers model robustness to 2D image transformations, leaving viewpoint changes in the 3D world less explored. In general, viewpoint changes are prevalent in various real-world applications (e.g., autonomous driving), making it imperative to evaluate viewpoint robustness. In this paper, we propose a novel method called ViewFool to find adversarial viewpoints that mislead visual recognition models. By encoding real-world objects as neural radiance fields (NeRF), ViewFool characterizes a distribution of diverse adversarial viewpoints under an entropic regularizer, which helps to handle the fluctuations of the real camera pose and mitigate the reality gap between the real objects and their neural representations. Experiments validate that the common image classifiers are extremely vulnerable to the generated adversarial viewpoints, which also exhibit high cross-model transferability. Based on ViewFool, we introduce ImageNet-V, a new out-of-distribution dataset for benchmarking viewpoint robustness of image classifiers. Evaluation results on 40 classifiers with diverse architectures, objective functions, and data augmentations reveal a significant drop in model performance when tested on ImageNet-V, which provides a possibility to leverage ViewFool as an effective data augmentation strategy to improve viewpoint robustness.Comment: NeurIPS 202