Real-Time Rotation-Invariant Face Detection with Progressive Calibration Networks

Rotation-invariant face detection, i.e. detecting faces with arbitrary rotation-in-plane (RIP) angles, is widely required in unconstrained applications but still remains as a challenging task, due to the large variations of face appearances. Most existing methods compromise with speed or accuracy to handle the large RIP variations. To address this problem more efficiently, we propose Progressive Calibration Networks (PCN) to perform rotation-invariant face detection in a coarse-to-fine manner. PCN consists of three stages, each of which not only distinguishes the faces from non-faces, but also calibrates the RIP orientation of each face candidate to upright progressively. By dividing the calibration process into several progressive steps and only predicting coarse orientations in early stages, PCN can achieve precise and fast calibration. By performing binary classification of face vs. non-face with gradually decreasing RIP ranges, PCN can accurately detect faces with full $360^{\circ}$ RIP angles. Such designs lead to a real-time rotation-invariant face detector. The experiments on multi-oriented FDDB and a challenging subset of WIDER FACE containing rotated faces in the wild show that our PCN achieves quite promising performance.Comment: Accepted by The IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2018). Code: \url{https://github.com/Jack-CV/PCN

A Novel Scoring System for Rupture Risk Stratification of Intracranial Aneurysms: A Hemodynamic and Morphological Study

Objective: The aim of the present study is to investigate the potential morphological and hemodynamic risk factors related to intracranial aneurysms (IAs) rupture and establish a system to stratify the risk of IAs rupture to help the clinical decision-making.Methods: Patients admitted to our hospital for single-IAs were selected from January 2012 and January 2018. A propensity score matching was conducted to match patients. The morphological parameters were obtained from high solution CTA images, and the hemodynamic parameters were obtained in accordance with the outcomes of computational fluid dynamics (CFDs) simulation. Differences in the morphologic and hemodynamic parameters were compared. The significant parameters were selected to establish a novel scoring system (Intracranial Aneurysm Rupture Score, IARS). The comparison was drawn between the discriminating accuracy of IARS and the Rupture Resemblance Score (RRS) system to verify the value of IARS. Then, a group of patients with unruptured IAs was stratified into the high risk and low risk groups by IARS and RRS system separately and was followed up for 18–27 months to verify the value of IARS. The outcome of different stratifications was compared.Results: The matching process yielded 167 patients in each group. Differences of statistical significance were found in aneurysm length (p = 0.001), perpendicular height (H) (p < 0.001), aspect ratio (AR) (p < 0.001), size ratio (SR) (p < 0.001), deviated angle (DA) (p < 0.001), normalized average wall shear stress (NWSSa) (p < 0.001), wall shear stress gradient (WSSG) (p < 0.001), low shear area ratio (LSAR) (p = 0.01), and oscillatory shear index (OSI) (p = 0.01). Logistic regression analysis further demonstrated that SR, DA, NWSSa, LSAR, and OSI were the independent risk factors of IAs rupture. SR, DA, LSAR, and OSI were finally selected to establish the IARS. Our present IARS showed a higher discriminating value (AUC 0.81 vs. 0.77) in comparison with the RRS (SR, NWSSa, and OSI). After follow-up, seven patients were subject to IAs rupture. 5/26 in high risk group stratified by IARS, yet 7/57 in high risk group stratified by RRS. The accuracy of IARS was further verified (19.2% vs. 12.3%, AUC for the IARS and the RRS was 0.723 and 0.673, respectively).Conclusion: SR, DA, NWSSa, LSAR, and OSI were considered the independent risk factors of IAs rupture. Our novel IARS showed higher accuracy in discriminating IA rupture in comparison with RRS

Secondary metabolites of Alternaria: A comprehensive review of chemical diversity and pharmacological properties

Fungi are considered to be one of the wealthiest sources of bio-metabolites that can be employed for yielding novel biomedical agents. Alternaria, including parasitic, saprophytic, and endophytic species, is a kind of dark fungi that can produce a broad array of secondary metabolites (SMs) widely distributed in many ecosystems. These are categorized into polyketides, nitrogen-containing compounds, quinones, terpenes, and others based on the unique structural features of the metabolites. New natural products derived from Alternaria exhibit excellent bioactivities characterized by antibacterial, antitumor, antioxidative, phytotoxic, and enzyme inhibitory properties. Thus, the bio-metabolites of Alternaria species are significantly meaningful for pharmaceutical, industrial, biotechnological, and medicinal applications. To update the catalog of secondary metabolites synthesized by Alternaria fungi, 216 newly described metabolites isolated from Alternaria fungi were summarized with their diverse chemical structures, pharmacological activity, and possible biosynthetic pathway. In addition, possible insights, avenues, and challenges for future research and development of Alternaria are discussed

Study on the gas–liquid annular vortex flow for liquid unloading of gas well

International audienceVortex tool is a new technique for the liquid unloading in gas wells. But it lacks a mathematical model to describe and predict the effect of vortex tools. In the present work, according to the axial, radial and circumferential momentum balance of the gas phase and liquid phase, the governing equations of vortex flow model have been established. Then thickness of liquid film and gas and liquid vortex flow intensity as well as the pressure drop gradient can be calculated. The calculation results and the previous experiments indicate that the pressure drop of the gas–liquid flow can be reduced by 5% ~ 25% with the vortex tool, and the vortex flow model has an average relative difference of 6.01%. The model results show that there are two mechanisms for reducing the pressure drop under the vortex flow condition. In addition, the research results show that vortex tools with bigger helical angle will lead to higher vortex flow intensity. The decay rate of vortex flow intensity decreases along the pipe as liquid velocity increases and the vortex flow working distance can be calculated by the vortex intensity gradient and initial vortex flow intensity

Axial Force Calculation Model for Completion String with Multiple Point Resistances in Horizontal Well

Frequent accidents may happen during the string run-down and pull process due to the lack of accuracy in the prediction of string force analysis. In order to precisely predict the completion string axial force in horizontal wells, a new model is established, and an in-house software has been developed. The model aims to predict the multiple local resistances that occur at different points on the completion string, which makes up for the technical defects of the commonly used software. It can calculate resistance at different points of the string, which will lead to varying hook load amplification. This method can also predict the axial force of the completion string. By changing the hook load, location, and direction, the resistance can be determined more accurately. Based on the calculation and analysis, the relationship between local resistance, the blocking point, and the amplification factor is also obtained. Furthermore, this model is used to analyze the local resistance of a horizontal well with multiple external packers in the low-permeability Sadi Reservoir of Halfaya Oilfield, Iraq. The recorded data from in-site operations are compared with the predicted results from this model. The results show that the relative errors between the recorded data and model calculation are within the range of 10%, which indicates that the calculated values are reliable. Meanwhile, the results indicate the success of the subsequent completion design and the construction of the oilfield

Research on Uncertainty Evolution of Ship Collision Status Based on Navigation Environment

There is a need to study the evolutionary laws of the risks in the navigation environments of complex marine areas. This can promote shipping safety using an early-warning system. The present study determines shipping flows and meteorological conditions in a marine area on the basis of meteorological and automatic identification system (AIS) data. It also determines the uncertainty evolution law of the navigation environment’s influencing factors. Moreover, a navigation risk evolution system for ships in complex marine areas was developed. A case study was carried out in a coastal area of China on the basis of the determined evolutionary laws. Evolution in the navigational environment risk within the case study area was analyzed. The results showed that the hydrometeorology wind factor has the greatest impact on the risk of ship collisions. This work was not only able to show advances in navigational collision environmental evolution laws but also provides a theoretical reference for the evaluation and early warning of risks in shipping environments

Cluster Ensemble-Based Image Segmentation

Image segmentation is the foundation of computer vision applications. In this paper, we propose a new cluster ensemble-based image segmentation algorithm, which overcomes several problems of traditional methods. We make two main contributions in this paper. First, we introduce the cluster ensemble concept to fuse the segmentation results from different types of visual features effectively, which can deliver a better final result and achieve a much more stable performance for broad categories of images. Second, we exploit the PageRank idea from Internet applications and apply it to the image segmentation task. This can improve the final segmentation results by combining the spatial information of the image and the semantic similarity of regions. Our experiments on four public image databases validate the superiority of our algorithm over conventional single type of feature or multiple types of features-based algorithms, since our algorithm can fuse multiple types of features effectively for better segmentation results. Moreover, our method is also proved to be very competitive in comparison with other state-of-the-art segmentation algorithms

Research on Uncertainty Evolution of Ship Collision Status Based on Navigation Environment

There is a need to study the evolutionary laws of the risks in the navigation environments of complex marine areas. This can promote shipping safety using an early-warning system. The present study determines shipping flows and meteorological conditions in a marine area on the basis of meteorological and automatic identification system (AIS) data. It also determines the uncertainty evolution law of the navigation environment’s influencing factors. Moreover, a navigation risk evolution system for ships in complex marine areas was developed. A case study was carried out in a coastal area of China on the basis of the determined evolutionary laws. Evolution in the navigational environment risk within the case study area was analyzed. The results showed that the hydrometeorology wind factor has the greatest impact on the risk of ship collisions. This work was not only able to show advances in navigational collision environmental evolution laws but also provides a theoretical reference for the evaluation and early warning of risks in shipping environments

An experimental study of liquid unloading in the curve section of horizontal gas wells

Liquid unloading is a very common and important issue in horizontal gas wells, and the presence of curve sections increases the complexity of the phenomenon and its study. Liquid loading in a gas well will sharply reduce production, therefore, the liquid-unloading onset of different curved pipes is essential to gas production. In this work, liquid-unloading onset experiments were conducted in curved pipes with different curvatures. Then, the critical gas velocity VsgCR can be determined according to the measured pressure gradients, liquid holdup, and liquid film reversal. This work analyzes the factors which will lead to the liquid unloading and explores the trend of the pipe curvature’s influence on the liquid unloading under laboratory conditions. The experimental results show that the critical gas velocity rises with the increase of pipe curvature, the increase is mainly due to the centrifugal force. The present work also compares the predicted results of the OLGA model and Beggs–Brill model with experimental data. The comparison results indicate that both models fit relatively well to the experimental data at the low superficial gas velocity, and both models have poor performance at high superficial gas velocity. The OLGA model fits the experimental data better than the Beggs–Brill model at high superficial gas velocity. The error analysis shows that most of the predicted data is not in good agreement with experimental data. Some errors between experimental data and calculation results are out of the range of 50%