Progressive Transfer Learning for Dexterous In-Hand Manipulation with Multi-Fingered Anthropomorphic Hand

Dexterous in-hand manipulation for a multi-fingered anthropomorphic hand is extremely difficult because of the high-dimensional state and action spaces, rich contact patterns between the fingers and objects. Even though deep reinforcement learning has made moderate progress and demonstrated its strong potential for manipulation, it is still faced with certain challenges, such as large-scale data collection and high sample complexity. Especially, for some slight change scenes, it always needs to re-collect vast amounts of data and carry out numerous iterations of fine-tuning. Remarkably, humans can quickly transfer learned manipulation skills to different scenarios with little supervision. Inspired by human flexible transfer learning capability, we propose a novel dexterous in-hand manipulation progressive transfer learning framework (PTL) based on efficiently utilizing the collected trajectories and the source-trained dynamics model. This framework adopts progressive neural networks for dynamics model transfer learning on samples selected by a new samples selection method based on dynamics properties, rewards and scores of the trajectories. Experimental results on contact-rich anthropomorphic hand manipulation tasks show that our method can efficiently and effectively learn in-hand manipulation skills with a few online attempts and adjustment learning under the new scene. Compared to learning from scratch, our method can reduce training time costs by 95%.Comment: 12 pages, 7 figures, submitted to TNNL

DVGG: Deep Variational Grasp Generation for Dextrous Manipulation

Grasping with anthropomorphic robotic hands involves much more hand-object interactions compared to parallel-jaw grippers. Modeling hand-object interactions is essential to the study of multi-finger hand dextrous manipulation. This work presents DVGG, an efficient grasp generation network that takes single-view observation as input and predicts high-quality grasp configurations for unknown objects. In general, our generative model consists of three components: 1) Point cloud completion for the target object based on the partial observation; 2) Diverse sets of grasps generation given the complete point cloud; 3) Iterative grasp pose refinement for physically plausible grasp optimization. To train our model, we build a large-scale grasping dataset that contains about 300 common object models with 1.5M annotated grasps in simulation. Experiments in simulation show that our model can predict robust grasp poses with a wide variety and high success rate. Real robot platform experiments demonstrate that the model trained on our dataset performs well in the real world. Remarkably, our method achieves a grasp success rate of 70.7\% for novel objects in the real robot platform, which is a significant improvement over the baseline methods.Comment: Accepted by Robotics and Automation Letters (RA-L, 2021

Terahertz Sensor via Ultralow-Loss Dispersion-Flattened Polymer Optical Fiber: Design and Analysis

A novel cyclic olefin copolymer (COC)-based polymer optical fiber (POF) with a rectangular porous core is designed for terahertz (THz) sensing by the finite element method. The numerical simulations showed an ultrahigh relative sensitivity of 89.73% of the x-polarization mode at a frequency of 1.2 THz and under optimum design conditions. In addition to this, they showed an ultralow confinement loss of 2.18 × 10−12 cm−1, a high birefringence of 1.91 × 10−3, a numerical aperture of 0.33, and an effective mode area of 1.65 × 105 μm2 was obtained for optimum design conditions. Moreover, the range dispersion variation was within 0.7 ± 0.41 ps/THz/cm, with the frequency range of 1.0–1.4 THz. Compared with the traditional sensor, the late-model sensor will have application value in THz sensing and communication

Design and optimization of dispersion-flattened microarray-core fiber with ultralow loss for terahertz transmission

The paper establishes a late-model of microarray-core based polymer optical fiber with flattened dispersion and ultra-low losses. Its transmission properties are calculated by virtue of the beam propagation approach. From the simulation results, it finds that the modelled fiber has a near-zero dispersion property of 0.29 ± 0.16 ps/THz/cm in a frequency area of 1.05 THz to 1.78 THz, a high birefringence of 1.6 × 10-3, an ultra-low confinement loss of 3.78 × 10-10 dB/m, an effective mode field zone of 4.6 × 105 μm2, and a nonlinear coefficient of 1.2 km-1·W−1. With these good properties, the modelled fiber could be applied for ethanol detection and polarization maintaining THz applications

Clinical Findings in Patients With Persistent Positional Nystagmus: The Designation of “Heavy and Light Cupula”

Objective: Direction-changing positional nystagmus (DCPN) had been observed as persistent horizontal apogeotropic and was considered as “cupulolithiasis or heavy cupula. ” Recently, the concept of “light cupula” exhibiting persistent geotropic DCPN has been introduced. However, the light cupula is not systematically described, while the identification and diagnosis of “light cupula” should be improved. Here we investigated the underlying characteristics and therapeutic options designed to the “light” and “heavy” cupula, respectively; and summarized the clinical characteristics and therapeutic effect in the two groups.Methods: A total of 359 cases with vertigo and bilateral DCPN were found in the supine roll test. Only 25 patients with persistent DCPN were enrolled and followed up. According to the direction of nystagmus, we further divided the patients into “heavy cupula” (apogeotropic) and “light cupula” (geotropic) groups. We compared the incidence, characteristics of nystagmus and the efficacy of repositioning maneuver in the two groups.Results: Nine patients with persistent horizontal geotropic DCPN were confirmed as “light cupula,” other 16 patients with persistent horizontal ageotropic DCPN were confirmed as heavy cupula. All 25 patients had null plane; the mean value and standard deviation of the null plane in light cupula and heavy cupula was 25.67 ± 9.31° and 27.06 ± 6.29°, respectively. The mean value and standard deviation of the termination plane in light cupula was 28.78 ± 10.00°, and 30.25 ± 6.53° in heavy cupula. There was no statistical significance between the two groups. We found that the direction of evoked nystagmus in the supine position was toward the intact side in light cupula, while in heavy cupula, it was toward the lesion side. The null plane appeared on the lesion side. For light cupula patients, the effect was not obvious at Day-7 after the treatment, however, treatment for most heavy cupula patients were effective. All patients recovered after 30 days of treatment.Conclusion: The null plane is crucial in determining the lesion side for light or heavy cupula. Although the short-term therapeutic effect of the light cupula is not as promising as the effect seen in heavy cupula, the long-term prognosis in both groups is comparable; with all patients recovered after 30 days of treatment.Study design: This is a retrospective cohort study

High-temperature and stress response behavior of femtosecond laser pulses inscribed eccentric fiber Bragg gratings

Eccentric fiber Bragg grating (EFBG) is inscribed in standard communication single-mode fiber using femtosecond laser pulses, and the temperature and strain sensing characteristics are experimentally demonstrated and analyzed. The EFBG exhibits strong thermal stability and good robustness in high-temperature measurement up to 1000 °C, and undergoes different thermal sensitivities during Bragg peak and the strong resonance coupled cladding spectral comb. The temperature sensitivity linearly increases with respect to the effective index of the resonant modes. Such a situation also occurs in axial strain measurement. These characteristics are of high interest for multiparametric sensing at high temperatures

1,7-Bis(4-hydroxyphenyl)-1,4,6-heptatrien-3-one inhibits SARS-CoV-2 by targeting the nucleocapsid protein

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread globally since 2020. The nucleocapsid (N) protein plays a crucial role in the life cycle of SARS-CoV-2. Here, we established a method to screen inhibitors of N protein by using microscale thermophoresis assays to obtain potential anti-SARS-CoV-2 agents. We identified 1,7-bis(4-hydroxyphenyl)-1,4,6-heptatrien-3-one (N-17, a diphenylheptane) as a compound with outstanding inhibitory activity. We further validated the binding of N-17 to the N-terminal domain of N protein (N-NTD) by using drug affinity responsive target stability assays. We evaluated the ability of N-17 to bind N protein and predicted the affinity of N-17 to the N-NTD with molecular docking and molecular dynamics simulation. N-17 exhibited excellent anti-viral activity against HCoV-OC43 and SARS-CoV-2, with EC50 values of 0.16 ± 0.01 μM and 0.17 ± 0.07 μM, respectively. Thus, we discovered a novel SARS-CoV-2 inhibitor targeting the N protein and validated its anti-viral activity in vitro. Our results may contribute to the development of promising therapeutic agents for COVID-19