Local Robust Sparse Representation for Face Recognition With Single Sample per Person

The purpose of this paper is to solve the problem of robust face recognition(FR) with single sample per person(SSPP). In the scenario of FR with SSPP, we present a novel model local robust sparse representation(LRSR) to tackle the problem of query images with various intra-class variations,e.g., expressions, illuminations, and occlusion. FR with SSPP is a very difficult challenge due to lacking of information to predict the possible intra-class variation of the query images.The key idea of the proposed method is to combine a local sparse representation model and a patch-based generic variation dictionary learning model to predict the possible facial intraclass variation of the query images. The experimental results on the AR database, Extended Yale B database, CMU-PIE database and LFW database show that the proposed method is robust to intra-class variations in FR with SSPP, and outperforms the state-of-art approaches.

Main geological and mining factors affecting ground cracks induced by underground coal mining in Shanxi Province, China

As one of the largest coal-rich provinces in China,Shanxi has extensive underground coal-mining operations.These operations have caused numerous ground cracks and substantial environmental damage.To study the main geological and mining factors influencing mining-related ground cracks in Shanxi,a detailed investigation was conducted on 13 mining-induced surface cracks in Shanxi.Based on the results,the degrees of damage at the study sites were empirically classified into serious,moderate,and minor,and the influential geological and mining factors(e.g.,proportions of loess and sandstone in the mining depth,ratio of rock thickness to mining thickness,and ground slope)were discussed.According to the analysis results,three factors(proportion of loess,ratio of rock thickness to mining thickness,and ground slope)play a decisive role in ground cracks and can be respectively considered as the critical material,mechanical,and geometric conditions for the occurrence of mining surface disasters.Together,these three factors have a strong influence on the occurrence of serious discontinuous ground deformation.The results can be applied to help prevent and control ground damage caused by coal mining.The findings also provide a direct reference for predicting and eliminating hidden ground hazards in mining areas.

Pose Robust Low-resolution Face Recognition via Coupled Kernel-based Enhanced Discriminant Analysis

Most face recognition techniques have been successful in dealing with high-resolution (HR) frontal face images. However, real-world face recognition systems are often confronted with the low-resolution (LR) face images with pose and illumination variations. This is a very challenging issue, especially under the constraint of using only a single gallery image per person. To address the problem, we propose a novel approach called coupled kernel-based enhanced discriminant analysis (CKEDA). CKEDA aims to simultaneously project the features from LR non-frontal probe images and HR frontal gallery ones into a common space where discrimination property is maximized. There are four advantages of the proposed approach: 1) by using the appropriate kernel function, the data becomes linearly separable, which is beneficial for recognition; 2) inspired by linear discriminant analysis (LDA), we integrate multiple discriminant factors into our objective function to enhance the discrimination property; 3) we use the gallery extended trick to improve the recognition performance for a single gallery image per person problem; 4) our approach can address the problem of matching LR non-frontal probe images with HR frontal gallery images, which is difficult for most existing face recognition techniques. Experimental evaluation on the multi-PIE dataset signifies highly competitive performance of our algorithm. © 2014 Chinese Association of Automation.

A review of monitoring,calculation,and simulation methods for ground subsidence induced by coal mining

Subsidence data acquisition methods are crucial to mining subsidence research and an essential component of achieving the goal of environmentally friendly coal mining.The origin and history of the existing methods of field monitoring,calcula-tion,and simulation were introduced.It summarized and analyzed the main applications,flaws and solutions,and improve-ments of these methods.Based on this analysis,the future developing directions of subsidence data acquisition methods were prospected and suggested.The subsidence monitoring methods have evolved from conventional ground monitoring to combined methods involving ground-based,space-based,and air-based measurements.While the conventional methods are mature in technology and reliable in accuracy,emerging remote sensing technologies have obvious advantages in terms of reducing field workload and increasing data coverage.However,these remote sensing methods require further technological development to be more suitable for monitoring mining subsidence.The existing subsidence calculation methods have been applied to various geological and mining conditions,and many improvements have already been made.In the future,more attention should be paid to unifying the studies of calculation methods and mechanical principles.The simulation methods are quite dependent on the similarity of the model to the site conditions and are generally used as an auxiliary data source for subsidence studies.The cross-disciplinary studies between subsidence data acquisition methods and other technologies should be given serious consideration,as they can be expected to lead to breakthroughs in areas such as theories,devices,software,and other aspects.

Erratum to"HLA-E-restricted Hantaan virus-specific CD8^(+)T cell responses enhance the control of infection in hemorrhagic fever with renal syndrome"[Biosaf.Health 5(2023)289-299]

The publisher regrets that during proofreading of the figure legend of Fig.6,the P value was misspelled in the sentence"while"n.s."indicates no significant difference P<0.05".It should be corrected to""while"n.s."indicates no significant difference(P>0.05)".

Research Progress on the Pathogenesis of Hemorrhagic Fever with Renal Syndrome

Hemorrhagic fever with renal syndrome(HFRS)is an acute natural focus epidemic disease characterized by fever,shock,hemorrhage and kidney injury caused by hantavirus infection.Hantavirus mainly infects human vascular endothelial cells,and induces extensive damage to small blood vessels and capillaries.Increased vascular permeability is the pathological basis for clinical manifestations of HFRS.Although domestic and foreign scholars have carried out many studies on the hantavirus pathogenesis,such as the immune pathological response induced by hantavirus,host genetics and apoptosis,thrombocytopenia,coagulation and fibrinolysis dysfunction,and the vascular endothelial damage,the pathogenesis of HFRS has not been fully elucidated and there is no effective drug yet.In-depth discussion of the molecular mechanism of HFRS and finding effective therapeutic drugs are still the research hotspots on the field of hantavirus/HFRS.This review will elaborate the research progress on the pathogenesis of HFRS in recent years.

Disclosing incoherent sparse and low-rank patterns inside homologous GPCR tasks for better modelling of ligand bioactivities

There are many new and potential drug targets in G protein-coupled receptors(GPCRs)without sufficient ligand associations,and accurately predicting and interpreting ligand bioactivities is vital for screening and optimizing hit compounds targeting these GPCRs.To efficiently address the lack of labeled training samples,we proposed a multi-task regression learning with incoherent sparse and low-rank patterns(MTR-ISLR)to model ligand bioactivities and identify their key substructures associated with these GPCRs targets.That is,MTR-ISLR intends to enhance the performance and interpretability of models under a small size of available training data by introducing homologous GPCR tasks.Meanwhile,the low-rank constraint term encourages to catch the underlying relationship among homologous GPCR tasks for greater model generalization,and the entry-wise sparse regularization term ensures to recognize essential discriminative substructures from each task for explanative modeling.We examined MTR-ISLR on a set of 31 important human GPCRs datasets from 9 subfamilies,each with less than 400 ligand associations.The results show that MTR-ISLR reaches better performance when compared with traditional single-task learning,deep multi-task learning and multi-task learning with joint feature learning-based models on most cases,where MTR-ISLR obtains an average improvement of 7%in correlation coefficient(r2)and 12%in root mean square error(RMSE)against the runner-up predictors.The MTR-ISLR web server appends freely all source codes and data for academic usages.^(1))

HLA-E-restricted Hantaan virus-specific CD8^(+)T cell responses enhance the control of infection in hemorrhagic fever with renal syndrome

Infection with the Hantaan virus(HTNV)may result in severe hemorrhagic fever with renal syndrome(HFRS).The functions of HLA-E-restricted CD8^(+)T lymphocytes in virus control and vaccine development have recently received increased attention.The purpose of this research is to discover HLA-E-restricted CD8^(+)T cell epitopes on HTNV as well as the features of these epitope-specific CD8^(+)T cells in HFRS patients.To anticipate HLA-Erestricted HTNV epitopes,the NetMHCpan servers were utilized.The K562/HLA-E cell binding test and the enzyme-linked immunospot assay were used to confirm epitope binding to HLA-E.The number and features of HLA-E-restricted epitope-specific CD8^(+)T lymphocytes in HFRS patients were investigated using tetramer staining,intracellular cytokine labeling,proliferation,and cytotoxicity assays.Six HTNV-derived HLA-Erestricted CD8^(+)T cell epitopes were found in this study.In mild/moderate HFRS patients,the frequency of HLA-E-restricted epitope-specific CD8^(+)T cells was greater than in severe/critical patients.CD38+HLA-DR+HLA-E-restricted CD8^(+)T cells were identified.Meanwhile,CD45RA^(+)CCR7^(-)effector memory-re-expressing CD45RA T cells with early and intermediate maturation and differentiation characteristics predominated.Notably,CD8^(+)T cells from milder HFRS patients produced more interferon-γ,interleukin-2,and granzyme B,had a stronger proliferative potential,and were inversely linked with the amount of plasma HTNV virus load.Furthermore,HLA-E-restricted epitope-specific CD8^(+)T cells demonstrated improved cytotoxic activity in vitro during the acute stage of HFRS.Taken together,the findings demonstrate the protective effects of HLA-E-restricted CD8^(+)T cells during HTNV infection,suggesting that HLA-E-targeted vaccines against HTNV might be developed for HLA-diverse populations.

Generation of tunable superchiral spot in metal-insulator-metal waveguide

The chiral feature of an optical field can be evaluated by the parameter of g-factor enhancement,which is helpful to enhance chiroptic signals from a chiral dipole.In this work,the superchiral spot has been theoretically proposed in metal-insulator-metal waveguides.The g-factor enhancement of the superchiral spot can be enhanced by 67-fold more than that of circularly polarized light,and the spot is confined in the deep wavelength scale along each spatial dimension.Moreover,the position of the superchiral spot can be tuned by manipulating the incident field.The tunable superchiral spot may find applications in chiral imaging and sensing.

Design of a sector bowtie nano-rectenna for optical power and infrared detection

We designed a sector bowtie nanoantenna integrated with a rectifier （Au-TiOx-Ti diode） for collect- ing infrared energy. The optical performance of the metallic bowtie nanoantenna was numerically investigated at infrared frequencies （5-30 μm） using three-dimensional frequency-domain electro- magnetic field calculation software based on the finite element method. The simulation results indi- cate that the resonance wavelength and local field enhancement are greatly affected by the shape and size of the bowtie nanoantenna, as well as the relative permittivity and conductivity of the dielectric layer. The output current of the rectified nano-rectenna is substantially at nanoampere magnitude with an electric field intensity of 1 V/m. Moreover, the power conversion efficiency for devices with three different substrates illustrates that a substrate with a larger refractive index yields a higher efficiency and longer infrared response wavelength. Consequently, the optimized structure can pro- vide theoretical support for the design of novel optical rectennas and fabrication of optoelectronic devices.

Metric learning for domain adversarial network

1 Introduction The existing domain adaptation methods[1,2]always aim to perform domain alignment between the source and target domain to alleviate the problem of domain shift[3].The target domain samples are likely to scatter on the classification boundary due to a lack of label information.Therefore,how to identify these overlapping classes in the target domain,called easily-confused classes,becomes the key to the improvement of classification performance.