A Two-Degree-Of-Freedom Time-Optimal Solution for Hard Disk Drive Servo Problems

This paper deals with the hard disk drive (HDD) servo problems. A novel discrete time-optimal control solution is proposed in a two-degree-of-freedom (2DOF) structure, employing both the feedback and feedforward controllers. The time-optimal feedback controller, derived from a simple, double integral plant model, shows remarkable robustness and disturbance rejection in the presence of resonant modes, measurement noises and position and torque disturbances. It eliminates the needs for two separate controllers for track-seeking and track-following operations. The proposed feedforward controller in this 2DOF structure proves to be quite beneficial in reducing the seek time. It also allows the feedback controller to be tuned more aggressively, which helps to improve the quality of track following. The proposed control scheme offers a novel basic control structure for HDD servo, upon which numerous further improvements can be made. It is successfully tested in simulation on an industrial 13.0-kTPI HDD

Herding Effect based Attention for Personalized Time-Sync Video Recommendation

Time-sync comment (TSC) is a new form of user-interaction review associated with real-time video contents, which contains a user's preferences for videos and therefore well suited as the data source for video recommendations. However, existing review-based recommendation methods ignore the context-dependent (generated by user-interaction), real-time, and time-sensitive properties of TSC data. To bridge the above gaps, in this paper, we use video images and users' TSCs to design an Image-Text Fusion model with a novel Herding Effect Attention mechanism (called ITF-HEA), which can predict users' favorite videos with model-based collaborative filtering. Specifically, in the HEA mechanism, we weight the context information based on the semantic similarities and time intervals between each TSC and its context, thereby considering influences of the herding effect in the model. Experiments show that ITF-HEA is on average 3.78\% higher than the state-of-the-art method upon F1-score in baselines.Comment: ACCEPTED for ORAL presentation at IEEE ICME 201

Orientation-dependent adhesion strength of a rigid cylinder in non-slipping contact with a transversely isotropic half-space

Recently, Chen and Gao [Chen, S., Gao, H., 2007. Bio-inspired mechanics of reversible adhesion: orientation-dependent adhesion strength for non-slipping adhesive contact with transversely isotropic elastic materials. J. Mech. Phys. solids 55, 1001–1015] studied the problem of a rigid cylinder in non-slipping adhesive contact with a transversely isotropic solid subjected to an inclined pulling force. An implicit assumption made in their study was that the contact region remains symmetric with respect to the center of the cylinder. This assumption is, however, not self-consistent because the resulting energy release rates at two contact edges, which are supposed to be identical, actually differ from each other. Here we revisit the original problem of Chen and Gao and derive the correct solution by removing this problematic assumption. The corrected solution provides a proper insight into the concept of orientation-dependent adhesion strength in anisotropic elastic solids

Minimalist and High-Quality Panoramic Imaging with PSF-aware Transformers

High-quality panoramic images with a Field of View (FoV) of 360-degree are essential for contemporary panoramic computer vision tasks. However, conventional imaging systems come with sophisticated lens designs and heavy optical components. This disqualifies their usage in many mobile and wearable applications where thin and portable, minimalist imaging systems are desired. In this paper, we propose a Panoramic Computational Imaging Engine (PCIE) to address minimalist and high-quality panoramic imaging. With less than three spherical lenses, a Minimalist Panoramic Imaging Prototype (MPIP) is constructed based on the design of the Panoramic Annular Lens (PAL), but with low-quality imaging results due to aberrations and small image plane size. We propose two pipelines, i.e. Aberration Correction (AC) and Super-Resolution and Aberration Correction (SR&AC), to solve the image quality problems of MPIP, with imaging sensors of small and large pixel size, respectively. To provide a universal network for the two pipelines, we leverage the information from the Point Spread Function (PSF) of the optical system and design a PSF-aware Aberration-image Recovery Transformer (PART), in which the self-attention calculation and feature extraction are guided via PSF-aware mechanisms. We train PART on synthetic image pairs from simulation and put forward the PALHQ dataset to fill the gap of real-world high-quality PAL images for low-level vision. A comprehensive variety of experiments on synthetic and real-world benchmarks demonstrates the impressive imaging results of PCIE and the effectiveness of plug-and-play PSF-aware mechanisms. We further deliver heuristic experimental findings for minimalist and high-quality panoramic imaging. Our dataset and code will be available at https://github.com/zju-jiangqi/PCIE-PART.Comment: The dataset and code will be available at https://github.com/zju-jiangqi/PCIE-PAR

Identification and characterization of bovine regulator of telomere length elongation helicase gene (RTEL): molecular cloning, expression distribution, splice variants and DNA methylation profile

BACKGROUND: The genetic basis of telomere length heterogeneity among mammalian species is still not well understood. Recently, a gene named regulator of telomere length elongation helicase (RTEL) was identified and predicted to be an essential participant in species-specific telomere length regulation in two murine species. To obtain broader insights into its structure and biological functions and to ascertain whether RTEL is also a candidate gene in the regulation of telomere length diversity in other mammalian species, data from other mammals may be helpful. RESULTS: Here we report the cDNA cloning, genomic structure, chromosomal location, alternative splicing pattern, expression distribution and DNA methylation profile of the bovine homolog of RTEL. The longest transcript of bovine RTEL is 4440 nt, encompassing 24.8 kb of genomic sequence that was mapped to chromosome 13q2.2. It encodes a conserved helicase-like protein containing seven characterized helicase motifs in the first 750 aa and a PIP box in the C-terminus. Four splice variants were identified within the transcripts in both the coding and 5'-untranslated regions; Western blot revealed that the most abundant splice variant SV-1 was translated to a truncated isoform of RTEL. The different 5'UTRs imply alternative transcription start sites in the promoter; Bovine RTEL was transcribed at the blastocyst stage, and expression levels were highest in adult testis, liver and ovary. DNA methylation analysis of tissues that differed significantly in expression level indicated that relatively low DNA methylation is associated with higher expression. CONCLUSION: In this study, we have identified and characterized a bovine RTEL homolog and obtained basic information about it, including gene structure, expression distribution, splice variants and profile of DNA methylation around two putative transcription start sites. These data may be helpful for further comparative and functional analysis of RTEL in mammals

When Less is Enough: Positive and Unlabeled Learning Model for Vulnerability Detection

Automated code vulnerability detection has gained increasing attention in recent years. The deep learning (DL)-based methods, which implicitly learn vulnerable code patterns, have proven effective in vulnerability detection. The performance of DL-based methods usually relies on the quantity and quality of labeled data. However, the current labeled data are generally automatically collected, such as crawled from human-generated commits, making it hard to ensure the quality of the labels. Prior studies have demonstrated that the non-vulnerable code (i.e., negative labels) tends to be unreliable in commonly-used datasets, while vulnerable code (i.e., positive labels) is more determined. Considering the large numbers of unlabeled data in practice, it is necessary and worth exploring to leverage the positive data and large numbers of unlabeled data for more accurate vulnerability detection. In this paper, we focus on the Positive and Unlabeled (PU) learning problem for vulnerability detection and propose a novel model named PILOT, i.e., PositIve and unlabeled Learning mOdel for vulnerability deTection. PILOT only learns from positive and unlabeled data for vulnerability detection. It mainly contains two modules: (1) A distance-aware label selection module, aiming at generating pseudo-labels for selected unlabeled data, which involves the inter-class distance prototype and progressive fine-tuning; (2) A mixed-supervision representation learning module to further alleviate the influence of noise and enhance the discrimination of representations.Comment: This paper is accepted by ASE 202

Estimation of N2 and N2O ebullition from eutrophic water using an improved bubble trap device

AbstractEbullition pathway of N2 and N2O emission and its importance on nitrogen loss were quantified during a survey of a eutrophic pond located at the subtropical climate zone in China. Using an improved bubble trap device, in situ collection of N2 bubbles was achieved by avoiding the contamination of N2 in the air. Measurements using the device indicated very high ebullition rates (36.3–366.7mlm−2h−1) and N2 ebullition flux (0.025–0.297gm−2h−1) at warmer months of September and October. The ebullition rates and N2 ebullition fluxes dropped sharply in colder months of December and January, ranged 2.5–15.9mlm−2h−1 and 0.002–0.016gm−2h−1, respectively. Distinct spatial variation of ebullition rates, and N2 and N2O ebullition fluxes were observed, with the highest rate at the heavy sediment location. Ebullition of N2O was a very minor fraction of total gaseous nitrogen released to air. The data demonstrated that ebullition could contribute greatly to biogenic N2 fluxes in eutrophic waters with significant bubble emission

Computational Optics Meet Domain Adaptation: Transferring Semantic Segmentation Beyond Aberrations

Semantic scene understanding with Minimalist Optical Systems (MOS) in mobile and wearable applications remains a challenge due to the corrupted imaging quality induced by optical aberrations. However, previous works only focus on improving the subjective imaging quality through computational optics, i.e. Computational Imaging (CI) technique, ignoring the feasibility in semantic segmentation. In this paper, we pioneer to investigate Semantic Segmentation under Optical Aberrations (SSOA) of MOS. To benchmark SSOA, we construct Virtual Prototype Lens (VPL) groups through optical simulation, generating Cityscapes-ab and KITTI-360-ab datasets under different behaviors and levels of aberrations. We look into SSOA via an unsupervised domain adaptation perspective to address the scarcity of labeled aberration data in real-world scenarios. Further, we propose Computational Imaging Assisted Domain Adaptation (CIADA) to leverage prior knowledge of CI for robust performance in SSOA. Based on our benchmark, we conduct experiments on the robustness of state-of-the-art segmenters against aberrations. In addition, extensive evaluations of possible solutions to SSOA reveal that CIADA achieves superior performance under all aberration distributions, paving the way for the applications of MOS in semantic scene understanding. Code and dataset will be made publicly available at https://github.com/zju-jiangqi/CIADA.Comment: Code and dataset will be made publicly available at https://github.com/zju-jiangqi/CIAD

Smoking behaviours and cessation services among male physicians in China: Evidence from a structural equation model

Objective To investigate smoking prevalence and cessation services provided by male physicians in hospitals in three Chinese cities. Methods Data were collected from a survey of male physicians employed at 33 hospitals in Changsha, Qingdao and Wuxi City (n=720). Exploratory factor analysis was performed to identify latent variables, and confirmatory structural equation modelling analysis was performed to test the relationships between predictor variables and smoking in male physicians, and their provision of cessation services. Results Of the sampled male physicians, 25.7% were current smokers, and 54.0% provided cessation services by counselling (18.8%), distributing self-help materials (17.1%), and providing traditional remedies or medication (18.2%). Factors that predicted smoking included peer smoking (OR 1.14 95% CI 1.03 to 1.26) and uncommon knowledge (OR 0.94 95% CI 0.89 to 0.99), a variable measuring awareness of the association of smoking with stroke, heart attack, premature ageing and impotence in male adults as well as the role of passive smoking in heart attack. Factors that predicted whether physicians provided smoking cessation services included peer smoking (OR 0.82 95% CI 0.76 to 0.89), physicians’ own smoking (OR 0.87 95% CI 0.81 to 0.93), training in cessation (OR 1.36 95% CI 1.27 to 1.45) and access to smoking cessation resources (OR 1.69 95% CI 1.58 to 1.82). Conclusions The smoke-free policy is not strictly implemented at healthcare facilities, and smoking remains a public health problem among male physicians. A holistic approach, including a stricter implementation of the smoke-free policy, comprehensive education on the hazards of smoking, training in standard smoking-cessation techniques and provision of cessation resources, is needed to curb the smoking epidemic among male physicians and to promote smoking cessation services in China