Recommending Analogical APIs via Knowledge Graph Embedding

Library migration, which re-implements the same software behavior by using a different library instead of using the current one, has been widely observed in software evolution. One essential part of library migration is to find an analogical API that could provide the same functionality as current ones. However, given the large number of libraries/APIs, manually finding an analogical API could be very time-consuming and error-prone. Researchers have developed multiple automated analogical API recommendation techniques. Documentation-based methods have particularly attracted significant interest. Despite their potential, these methods have limitations, such as a lack of comprehensive semantic understanding in documentation and scalability challenges. In this work, we propose KGE4AR, a novel documentation-based approach that leverages knowledge graph (KG) embedding to recommend analogical APIs during library migration. Specifically, KGE4AR proposes a novel unified API KG to comprehensively and structurally represent three types of knowledge in documentation, which can better capture the high-level semantics. Moreover, KGE4AR then proposes to embed the unified API KG into vectors, enabling more effective and scalable similarity calculation. We build KGE4AR' s unified API KG for 35,773 Java libraries and assess it in two API recommendation scenarios: with and without target libraries. Our results show that KGE4AR substantially outperforms state-of-the-art documentation-based techniques in both evaluation scenarios in terms of all metrics (e.g., 47.1%-143.0% and 11.7%-80.6% MRR improvements in each scenario). Additionally, we explore KGE4AR' s scalability, confirming its effective scaling with the growing number of libraries.Comment: Accepted by FSE 202

Active Triggering of Pneumatic Rehabilitation Gloves Based on Surface Electromyography Sensors

The portable and inexpensive hand rehabilitation robot has become a practical rehabilitation device for patients with hand dysfunction. A pneumatic rehabilitation glove with an active trigger control system is proposed, which is based on surface electromyography (sEMG) signals. It can trigger the hand movement based on the patient's hand movement trend, which may improve the enthusiasm and efficiency of patient training. Firstly, analysis of sEMG sensor installation position on human's arm and signal acquisition process was carried out. Then according to the statistical law, three optimal eigenvalues of sEMG signals were selected as the follow-up neural network classification input. Using the back propagation (BP) neural network, the classifier of hand movement is established. Moreover, the mapping relationship between hand sEMG signals and hand actions is built by training and testing. According to individual differences, the corresponding BP neural network model database of different people was established. Finally, based on sEMG signal trigger, the pneumatic glove training control algorithm was proposed. The combination of the trigger signal waveform and the motion signal waveform indicates that the pneumatic rehabilitation glove is triggered to drive the patient's hand movement. Preliminary tests have confirmed that the device has a high accuracy rate of trend recognition for hand movement. In the future, clinical trials of patients will be conducted to prove the effectiveness of this system

Design and Research of Electron Cyclotron Resonance Heating and Current Dive System on HL-2M Tokamak

A research has been conducted to develop an 8MW electron cyclotron resonance heating and current drive (ECRH/ECCD) system on HL-2M tokamak. The ECRH system compromise eight 1MW gyrotrons, eight evacuated transmission lines and three launchers. The main purpose of the ECRH system was to suppress the neo-classical tearing modes and control the plasma profile. This paper presents an overview of the design and studies performed in this framework. Some primary test results of the critical components have been released in this paper, e.g. polarizers, power monitor and fast steering launchers

Thyroid function and associated mood changes after COVID-19 vaccines in patients with Hashimoto thyroiditis

ContextSevere acute respiratory syndrome-coronavirus 2 (COVID-19) vaccines may incur changes in thyroid functions followed by mood changes, and patients with Hashimoto thyroiditis (HT) were suggested to bear a higher risk.ObjectivesWe primarily aim to find whether COVID-19 vaccination could induce potential subsequent thyroid function and mood changes. The secondary aim was to find inflammatory biomarkers associated with risk.MethodsThe retrospective, multi-center study recruited patients with HT receiving COVID-19–inactivated vaccines. C-reactive proteins (CRPs), thyroid-stimulating hormones (TSHs), and mood changes were studied before and after vaccination during a follow-up of a 6-month period. Independent association was investigated between incidence of mood state, thyroid functions, and inflammatory markers. Propensity score–matched comparisons between the vaccine and control groups were carried out to investigate the difference.ResultsFinal analysis included 2,765 patients with HT in the vaccine group and 1,288 patients in the control group. In the matched analysis, TSH increase and mood change incidence were both significantly higher in the vaccine group (11.9% versus 6.1% for TSH increase and 12.7% versus 8.4% for mood change incidence). An increase in CRP was associated with mood change (p< 0.01 by the Kaplan–Meier method) and severity (r = 0.75) after vaccination. Baseline CRP, TSH, and antibodies of thyroid peroxidase (anti-TPO) were found to predict incidence of mood changes.ConclusionCOVID-19 vaccination seemed to induce increased levels and incidence of TSH surge followed by mood changes in patients with HT. Higher levels of pre-vaccine serum TSH, CRP, and anti-TPO values were associated with higher incidence in the early post-vaccine phase

Research on Monocular-Vision-Based Finger-Joint-Angle-Measurement System

The quantitative measurement of finger-joint range of motion plays an important role in assessing the level of hand disability and intervening in the treatment of patients. An industrial monocular-vision-based knuckle-joint-activity-measurement system is proposed with short measurement time and the simultaneous measurement of multiple joints. In terms of hardware, the system can adjust the light-irradiation angle and the light-irradiation intensity of the marker by actively adjusting the height of the light source to enhance the difference between the marker and the background and reduce the difficulty of segmenting the target marker and the background. In terms of algorithms, a combination of multiple-vision algorithms is used to compare the image-threshold segmentation and Hough outer- and inner linear detection as the knuckle-activity-range detection method of the system. To verify the accuracy of the visual-detection method, nine healthy volunteers were recruited for experimental validation, and the experimental results showed that the average angular deviation in the flexion/extension of the knuckle was 0.43° at the minimum and 0.59° at the maximum, and the average angular deviation in the adduction/abduction of the knuckle was 0.30° at the minimum and 0.81° at the maximum, which were all less than 1°. In the multi-angle velocimetry experiment, the time taken by the system was much less than that taken by the conventional method

The α₂δ Calcium Channel Subunit Accessorily and Independently Affects the Biological Function of <i>Ditylenchus destructor</i>

The α2δ subunit is a high-voltage activated (HVA) calcium channel (Cav1 and Cav2) auxiliary subunit that increases the density and function of HVA calcium channels in the plasma membrane of mammals. However, its function in plant parasitic nematodes remains unknown. In this study, we cloned the full-length cDNA sequence of the voltage-gated calcium channel (VGCC) α2δ subunit (named DdCavα2δ) in Ditylenchus destructor. We found that DdCavα2δ tends to be expressed in the egg stage, followed by the J3 stage. RNA-DIG in situ hybridization experiments showed that the DdCavα2δ subunit was expressed in the body wall, esophageal gland, uterus, post uterine, and spicules of D. destructor. The in vitro application of RNA interference (RNAi) affected the motility, reproduction, chemotaxis, stylet thrusting, and protein secretion of D. destructor to different degrees by targeting DdCα1D, DdCα1A, and DdCavα2δ in J3 stages, respectively. Based on the results of RNAi experiments, it was hypothesized that L-type VGCC may affect the motility, chemotaxis, and stylet thrusting of D. destructor. Non-L-type VGCC may affect the protein secretion and reproduction of D. destructor. The DdCavα2δ subunit gene also affected the motility, chemotaxis, and reproduction of D. destructor. These findings reveal the independent function of the VGCC α2δ subunit in D. destructor as well as give a theoretical foundation for future research on plant parasitic nematode VGCC

A Fast Binocular Localisation Method for AUV Docking

Docking technology plays a critical role in realising the long-time operation of autonomous underwater vehicles (AUVs). In this study, a binocular localisation method for AUV docking is presented. An adaptively weighted OTSU method is developed for feature extraction. The foreground object is extracted precisely without mixing or missing lamps, which is independent of the position of the AUV relative to the station. Moreover, this extraction process is more precise compared to other segmentation methods with a low computational load. The mass centre of each lamp on the binary image is used as matching feature for binocular vision. Using this fast feature matching method, the operation frequency of the binocular localisation method exceeds 10 Hz. Meanwhile, a relative pose estimation method is suggested for instances when the two cameras cannot capture all the lamps. The localisation accuracy of the distance in the heading direction as measured by the proposed binocular vision algorithm was tested at fixed points underwater. A simulation experiment using a ship model has been conducted in a laboratory pool to evaluate the feasibility of the algorithm. The test result demonstrates that the average localisation error is approximately 5 cm and the average relative location error is approximately 2% in the range of 3.6 m. As such, the ship model was successfully guided to the docking station for different lateral deviations

A MEMS-Based Co-Oscillating Electrochemical Vector Hydrophone

Aiming at the development needs of low-frequency and high-sensitivity vector hydrophones, this paper has developed a micro-electro-mechanical system (MEMS) based co-oscillating electrochemical vector hydrophone. We obtained the optimized geometric parameters through simulation analysis of the diameter of the rubber membrane, the length of the flow channel and the diameter of the flow holes. Based on the simulation results, electrodes were fabricated using MEMS technology, and were then assembled and tested. Device characterization was conducted, where the sensitivity and bandwidth were quantified as 0.5–150 Hz, −187 dB ref. 1 V/μPa, respectively. Compared with a previously reported co-oscillating vector hydrophone, the co-oscillating vector hydrophone developed in this article featured a lower working frequency band