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Oscillations of coefficients of symmetric square L-functions over primes

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Frontiers of Mathematics in China 2015年第6期10卷 1325-1341页

作者： fei hou School of Mathematics Shandong University Jinan 250100 China

Let L（s, sym2f） be the symmetric-square L-function associated to a primitive holomorphic cusp form f for SL（2, Z）, with tf（n, 1） denoting the nthcoefficient of the Dirichlet series for it. It is proved that, forN≥2and anyα∈ there exists an effective positive constant c such that ∑n≤N∧（n）tf（n,1）e（nα）〈〈N exp （-c√logN,where ∧（n） is the von Mangoldt function, and the implied constant only depends on f. We also study the analogue of Vinogradov＇s three primes theorem associated to the coefficients of Rankin-Selberg L-functions.

关键词： symmetric-square L-function primitive holomorphic cusp form,Fourier coefficient

肺泡巨噬细胞对屋尘螨诱导的过敏性气道炎症的影响

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中国免疫学杂志 2025年第2期41卷 276-280,286页

作者：程百合杨文婷侯飞唐丽青岛大学基础医学院青岛266071 军事科学院军事医学研究院生命组学研究所蛋白质组学国家重点实验室北京102206

目的:研究屋尘螨(HDM)诱导的过敏性气道炎症小鼠模型中免疫细胞的变化,并对肺泡巨噬细胞(AM)在其中的效应功能进行初步探索。方法:气管注射HDM诱导过敏性气道炎症,并在建模前通过气管注射氯膦酸盐脂质体(CL)特异性地对AM进行清除;心脏... 详细信息

目的:研究屋尘螨(HDM)诱导的过敏性气道炎症小鼠模型中免疫细胞的变化,并对肺泡巨噬细胞(AM)在其中的效应功能进行初步探索。方法:气管注射HDM诱导过敏性气道炎症,并在建模前通过气管注射氯膦酸盐脂质体(CL)特异性地对AM进行清除;心脏灌注分离小鼠全肺免疫细胞;气管灌洗分离小鼠肺泡灌洗液免疫细胞;ELISA检测肺泡灌洗液Ⅱ型细胞因子的水平;流式细胞术检测肺脏或肺泡灌洗液免疫细胞的变化;HE染色、PAS染色评价HDM建模后肺脏炎症粒细胞浸润、杯状细胞增生以及黏液分泌情况。结果:在HDM诱导的过敏性气道炎症中,Ⅱ型免疫反应的效应细胞如Ⅱ型先天性淋巴细胞(ILC2)、嗜酸性粒细胞显著增加,组织学分析表明肺组织有大量炎症细胞浸润,杯状细胞增生,黏液分泌增加。而清除AM减缓了HDM诱导的Ⅱ型免疫反应,但促进了中性粒细胞的浸润,加重了肺脏的病理损伤。结论:AM在HDM诱导过敏性气道炎症中发挥重要作用。

关键词：屋尘螨过敏性气道炎症肺泡巨噬细胞嗜酸性粒细胞 Ⅱ型先天性淋巴细胞

Hierarchical vectorization for facial images

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Computational Visual Media 2024年第1期10卷 97-118页

作者： Qian Fu Linlin Liu fei hou Ying He School of Computer Science and Engineering Nanyang Technological University639798SingaporeSingapore Data61 Commonwealth Scientific and Industrial Research OrganisationSydney2015Australia Interdisciplinary Graduate School Nanyang Technological University and Alibaba Group639798SingaporeSingapore State Key Laboratory of Computer Science Institute of SoftwareChinese Academy of SciencesBeijing100190China University of Chinese Academy of Sciences Beijing100049China

The explosive growth of social media means portrait editing and retouching are in high *** portraits are commonly captured and stored as raster images,editing raster images is non-trivial and requires the user to be highly *** at developing intuitive and easy-to-use portrait editing tools,we propose a novel vectorization method that can automatically convert raster images into a 3-tier hierarchical *** base layer consists of a set of sparse diffusion curves(DCs)which characterize salient geometric features and low-frequency colors,providing a means for semantic color transfer and facial expression *** middle level encodes specular highlights and shadows as large,editable Poisson regions(PRs)and allows the user to directly adjust illumination by tuning the strength and changing the shapes of *** top level contains two types of pixel-sized PRs for high-frequency residuals and fine details such as pimples and *** train a deep generative model that can produce high-frequency residuals *** to the inherent meaning in vector primitives,editing portraits becomes easy and *** particular,our method supports color transfer,facial expression editing,highlight and shadow editing,and automatic *** quantitatively evaluate the results,we extend the commonly used FLIP metric(which measures color and feature differences between two images)to consider *** new metric,illumination-sensitive FLIP,can effectively capture salient changes in color transfer results,and is more consistent with human perception than FLIP and other quality measures for portrait *** evaluate our method on the FFHQR dataset and show it to be effective for common portrait editing tasks,such as retouching,light editing,color transfer,and expression editing.

关键词： face editing vectorization Poisson editing color transfer illumination editing expression editing

A CADe system for nodule detection in thoracic CT images based on artificial neural network

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Science China(Information Sciences) 2017年第7期60卷 177-194页

作者： Xinglong LIU fei hou Hong QIN Aimin HAO State Key Laboratory of Virtual Reality Technology and Systems Beihang University School of Computer Science and Engineering Nanyang Technological University Department of Computer Science Stony Brook University

Lung cancer has been the leading cause of cancer-related deaths in 2015 in United States. Early detection of lung nodules will undoubtedly increase the five-year survival rate for lung cancer according to prior studies. In this paper, we propose a novel rating method based on geometrical and statistical features to extract initial nodule candidates and an artificial neural network approach to the detection of lung nodules. The novel method is solely based on 3D distribution of neighboring voxels instead of user-specified features. During initial candidates detection, we combine organized region properties calculated from connected component analysis with corresponding voxel value distributions from statistical analysis to reduce false positives while retaining true nodules. Then we devise multiple artificial neural networks(ANNs) trained from massive voxel neighbor sampling of different types of nodules and organize the outputs using a 3D scoring method to identify final nodules. The experiments on 107 CT cases with 252 nodules in LIDC-IDRI data sets have shown that our new method achieves sensitivity of 89.4% while reducing the false positives to 2.0 per case. Our comprehensive experiments have demonstrated our system would be of great assistance for diagnosis of lung nodules in clinical treatments.

关键词： artificial neutral network Lung nodule computed tomography computer aided detection nodule detection

Designing planar cubic B-spline curves with monotonic curvature for curve interpolation

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Computational Visual Media 2020年第3期6卷 349-354页

作者： Aizeng Wang Chuan He fei hou Zhanchuan Cai Gang Zhao School of Mechanical Engineering&Automation Beihang UniversityBeijing 100191China State Key Laboratory of Virtual Reality Technology&Systems Beihang UniversityBeijing 100191China State Key Laboratory of Computer Science Institute of SoftwareChinese Academy of SciencesBeijing 100190China University of Chinese Academy of Sciences Beijing 100049China Faculty of Information Technology Macao University of Science and TechnologyMacao 999078China

Monotonic curvature plays an important role in industrial design and styling of curves with aesthetic shapes,e.g.,in automobile and aircraft design[1].Used in conventional parametric CAD/CAM systems,general B-splines are not adequate for aesthetic *** for the straight line and circle,monotonic curvature distribution,associated with pleasing shape,is very difficult to achieve.

关键词： curvature monotonic curves

Dynamic ocean inverse modeling based on differentiable rendering

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Computational Visual Media 2024年第2期10卷 279-294页

作者： Xueguang Xie Yang Gao fei hou Aimin Hao Hong Qin State Key Lab of Virtual Reality Technology and Systems Beihang UniversityBeijing 100191China Qingdao Research Institute Beihang UniversityQingdao 266100Chinaand Peng Cheng LabShenzhen 518000China SKLCS Institute of SoftwareChinese Academy of SciencesBeijing 100190Chinaand University of Chinese Academy of SciencesBeijing 100049China Department of Computer Science Stony Brook University(SUNY at Stony Brook)Stony BrookNew York 11794-2424USA

Learning and inferring underlying motion patterns of captured 2D scenes and then re-creating dynamic evolution consistent with the real-world natural phenomena have high appeal for graphics and *** bridge the technical gap between virtual and real environments,we focus on the inverse modeling and reconstruction of visually consistent and property-verifiable oceans,taking advantage of deep learning and differentiable physics to learn geometry and constitute waves in a self-supervised ***,we infer hierarchical geometry using two networks,which are optimized via the differentiable *** extract wave components from the sequence of inferred geometry through a network equipped with a differentiable ocean ***,ocean dynamics can be evolved using the reconstructed wave *** extensive experiments,we verify that our new method yields satisfactory results for both geometry reconstruction and wave ***,the new framework has the inverse modeling potential to facilitate a host of graphics applications,such as the rapid production of physically accurate scene animation and editing guided by real ocean scenes.

关键词： inverse modeling surface reconstruction wave modeling ocean waves differentiable rendering(DR)

PIGN mutation multiple congenital anomalies-hypotonia-seizures syndrome 1:A case report

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World Journal of Clinical Cases 2022年第16期10卷 5441-5445页

作者： fei hou Shan Shan Hua Jin Department of Prenatal Diagnosis Jinan Maternal and Child Health HospitalJinan 250001Shandong ProvinceChina

BACKGROUND Multiple congenital anomalies-hypotonia-seizures syndrome 1(MCAHS1)associated with mutations in PIGN *** SUMMARY The authors report 1 case of a 16 years old girl who was presented with epilepsy,developmental delay and cerebellar *** harbors a compound heterozygous variant in the PIGN gene,include a nonsense splice site mutation(c.2557A>C)which was inherited from her mother,and a novel site mutation(c.980del)which was inherited from her *** This case report expands the mutation spectrum found in PIGN gene,and strengthens the association between PIGN mutation and *** in PIGN gene may be an underestimated cause of *** authors recommend that,for patients with epilepsy or prenatal diagnosis of highly suspicious fetus,gene sequencing should be the preferred detection method.

关键词： PIGN Multiple congenital anomalies-hypotonia-seizures Syndrome 1 MCAHS1 Whole-exome sequencing

Three-dimensional reconstruction of industrial parts from a single image

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Visual Computing for Industry,Biomedicine,and Art 2024年第1期7卷 340-351页

作者： Zhenxing Xu Aizeng Wang fei hou Gang Zhao School of Mechanical Engineering and Automation Beihang UniversityBeijing 100191China Key Laboratory of Aeronautics Smart Manufacturing Beihang UniversityBeijing 100191China State Key Laboratory of Computer Science Institute of SoftwareChinese Academy of SciencesBeijing 100190China

This study proposes an image-based three-dimensional(3D)vector reconstruction of industrial parts that can gener-ate non-uniform rational B-splines(NURBS)surfaces with high fidelity and *** contributions of this study include three parts:first,a dataset of two-dimensional images is constructed for typical industrial parts,including hex-agonal head bolts,cylindrical gears,shoulder rings,hexagonal nuts,and cylindrical roller bearings;second,a deep learning algorithm is developed for parameter extraction of 3D industrial parts,which can determine the final 3D parameters and pose information of the reconstructed model using two new nets,CAD-ClassNet and CAD-ReconNet;and finally,a 3D vector shape reconstruction of mechanical parts is presented to generate NURBS from the obtained shape *** final reconstructed models show that the proposed approach is highly accurate,efficient,and practical.

关键词： Three-dimensional reconstruction Non-uniform rational B-splines Industrial parts Deep learning

Defect detection of gear parts in virtual manufacturing

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Visual Computing for Industry,Biomedicine,and Art 2023年第1期6卷 76-87页

作者： Zhenxing Xu Aizeng Wang fei hou Gang Zhao School of Mechanical Engineering&Automation Beihang UniversityBeijing 100191China State Key Laboratory of Computer Science Institute of SoftwareChinese Academy of SciencesBeijing 100190China University of Chinese Academy of Sciences Beijing 100049China

Gears play an important role in virtual manufacturing systems for digital twins;however,the image of gear tooth defects is difficult to acquire owing to its non-convex *** this study,a deep learning network is proposed to detect gear defects based on their point cloud *** approach mainly consists of three steps:(1)Various types of gear defects are classified into four cases(fracture,pitting,glue,and wear);A 3D gear dataset was constructed with 10000 instances following the aforementioned classification.(2)Gear-PCNet++introduces a novel Combinational Convolution Block,proposed based on the gear dataset for gear defect detection to effectively extract the local gear information and identify its complex topology;(3)Compared with other methods,experiments show that this method can achieve better recognition results for gear defects with higher efficiency and practicability.

关键词： Defect detection Gear surface Gear dataset Combinational Convolution Block