3D Face Recognition Using Anthropometric and Curvelet Features Fusion

Curvelet transform can describe the signal by multiple scales, and multiple directions. In order to improve the performance of 3D face recognition algorithm, we proposed an Anthropometric and Curvelet features fusion-based algorithm for 3D face recognition (Anthropometric Curvelet Fusion Face Recognition, ACFFR). First, the eyes, nose, and mouth feature regions are extracted by the Anthropometric characteristics and curvature features of the human face. Second, Curvelet energy features of the facial feature regions at different scales and different directions are extracted by Curvelet transform. At last, Euclidean distance is used as the similarity between template and objectives. To verify the performance, the proposed algorithm is compared with Anthroface3D and Curveletface3D on the Texas 3D FR database. The experimental results have shown that the proposed algorithm performs well, with equal error rate of 1.75% and accuracy of 97.0%. The algorithm we proposed in this paper has better robustness to expression and light changes than Anthroface3D and Curveletface3D

RpoN (σ54) Is Required for Floc Formation but Not for Extracellular Polysaccharide Biosynthesis in a Floc-Forming Aquincola tertiaricarbonis Strain.

Some bacteria are capable of forming flocs, in which bacterial cells become self-flocculated by secreted extracellular polysaccharides and other biopolymers. The floc-forming bacteria play a central role in activated sludge, which has been widely utilized for the treatment of municipal sewage and industrial wastewater. Here, we use a floc-forming bacterium, Aquincolatertiaricarbonis RN12, as a model to explore the biosynthesis of extracellular polysaccharides and the regulation of floc formation. A large gene cluster for exopolysaccharide biosynthesis and a gene encoding the alternative sigma factor RpoN1, one of the four paralogues, have been identified in floc formation-deficient mutants generated by transposon mutagenesis, and the gene functions have been further confirmed by genetic complementation analyses. Interestingly, the biosynthesis of exopolysaccharides remained in the rpoN1-disrupted flocculation-defective mutants, but most of the exopolysaccharides were secreted and released rather than bound to the cells. Furthermore, the expression of exopolysaccharide biosynthesis genes seemed not to be regulated by RpoN1. Taken together, our results indicate that RpoN1 may play a role in regulating the expression of a certain gene(s) involved in the self-flocculation of bacterial cells but not in the biosynthesis and secretion of exopolysaccharides required for floc formation.IMPORTANCE Floc formation confers bacterial resistance to predation of protozoa and plays a central role in the widely used activated sludge process. In this study, we not only identified a large gene cluster for biosynthesis of extracellular polysaccharides but also identified four rpoN paralogues, one of which (rpoN1) is required for floc formation in A. tertiaricarbonis RN12. In addition, this RpoN sigma factor regulates the transcription of genes involved in biofilm formation and swarming motility, as previously shown in other bacteria. However, this RpoN paralogue is not required for the biosynthesis of exopolysaccharides, which are released and dissolved into culture broth by the rpoN1 mutant rather than remaining tightly bound to cells, as observed during the flocculation of the wild-type strain. These results indicate that floc formation is a regulated complex process, and other yet-to-be identified RpoN1-dependent factors are involved in self-flocculation of bacterial cells via exopolysaccharides and/or other biopolymers

The Impact of Carbon Emission Trading Policies on Enterprises’ Green Technology Innovation—Evidence from Listed Companies in China

At present, the Chinese government has successively launched various policies to control the emission standards of greenhouse gases. As one of the most important standards, carbon emission trading policies were implemented in some provinces and regions in China in 2013, aiming to restrict the carbon emissions of enterprises. However, the government’s control of corporate carbon emissions restricts their rapid economic growth to some extent. Enterprises’ green technology innovation can be an effective means to ensure the implementation of low-carbon policies and promote sustainable economic growth simultaneously. The Porter hypothesis holds that reasonable environmental regulations can stimulate enterprises’ green technology innovation. Based on the Porter hypothesis, this paper examines the impact of China’s carbon emission trading policies on local enterprises’ green technology innovation from a micro perspective, taking China’s listed companies from 2007 to 2020 as samples and adopting the differential method. The differences in the impact of carbon emission trading policies on green technology innovation in the context of different corporate environmental strategies are also studied. Our study found that China’s carbon emissions trading policies can effectively stimulate green technology innovation, as carbon emissions trading policies under different environmental strategies have a positive influence on the technical innovation of enterprises and, compared with reactive environmental strategies, promote a greater role for enterprises’ proactive environmental strategies. The conclusions of this study not only provide relevant suggestions for the Chinese government to enact environmental regulation policies but also provide references for enterprises to choose appropriate environmental strategies and achieve sustainable development under the constraints of environmental regulation

3D Face Recognition Using Anthropometric and Curvelet Features Fusion

Curvelet transform can describe the signal by multiple scales, and multiple directions. In order to improve the performance of 3D face recognition algorithm, we proposed an Anthropometric and Curvelet features fusion-based algorithm for 3D face recognition (Anthropometric Curvelet Fusion Face Recognition, ACFFR). First, the eyes, nose, and mouth feature regions are extracted by the Anthropometric characteristics and curvature features of the human face. Second, Curvelet energy features of the facial feature regions at different scales and different directions are extracted by Curvelet transform. At last, Euclidean distance is used as the similarity between template and objectives. To verify the performance, the proposed algorithm is compared with Anthroface3D and Curveletface3D on the Texas 3D FR database. The experimental results have shown that the proposed algorithm performs well, with equal error rate of 1.75% and accuracy of 97.0%. The algorithm we proposed in this paper has better robustness to expression and light changes than Anthroface3D and Curveletface3D

Corrosion Behavior of SMA490BW Steel and Welded Joints for High-Speed Trains in Atmospheric Environments

Currently, high-speed trains work under various atmospheric environments, and the bogie as a key component suffers serious corrosion. To investigate the corrosion behavior of bogies in industrial atmospheric environments, the periodic immersion wet/dry cyclic corrosion test for SMA490BW steel and automatic metal active gas (MAG) welded joints used for bogies was conducted in the present work. Corrosion weight loss rate, structure, and composition of rust layers as well as electrochemistry parameters were investigated. The results showed that the corrosion weight loss rate decreased with increasing corrosion time; furthermore, the corrosion weight loss rate of the welded joints was lower than that of SMA490BW steel. The XRD results showed that the rust layers formed on SMA490BW steel and its welded joints were mainly composed of α-FeOOH, γ-FeOOH, Fe2O3, and Fe3O4. The observation of surface morphology indicated that the rust layers of the welded joints were much denser and had a much finer microstructure compared with those of SMA490BW steel. After corrosion for 150 h, the corrosion potential of the welded joints with rust layers was higher than that of SMA490BW steel. In short, the welded joints exhibited better corrosion resistance than SMA490BW steel because of the higher content of alloy elements, as shown in this work

Target Tracking Algorithm Using Angular Point Matching Combined with Compressive Tracking

To solve the problems of tracking errors such as target missing that emerged in compressive tracking (CT) algorithm due to factors such as pose variation, illumination change, and occlusion, a novel tracking algorithm combined angular point matching with compressive tracking (APMCCT) was proposed. A sparse measurement matrix was adopted to extract the Haar-like features. The offset of the predicted target position was integrated into the angular point matching, and the new target position was calculated. Furthermore, the updating mechanism of the template was optimized. Experiments on different video sequences have shown that the proposed APMCCT performs better than CT algorithm in terms of accuracy and robustness and adaptability to pose variation, illumination change, and occlusion

Gait Recognition Using GEI and AFDEI

Gait energy image (GEI) preserves the dynamic and static information of a gait sequence. The common static information includes the appearance and shape of the human body and the dynamic information includes the variation of frequency and phase. However, there is no consideration of the time that normalizes each silhouette within the GEI. As regards this problem, this paper proposed the accumulated frame difference energy image (AFDEI), which can reflect the time characteristics. The fusion of the moment invariants extracted from GEI and AFDEI was selected as the gait feature. Then, gait recognition was accomplished using the nearest neighbor classifier based on the Euclidean distance. Finally, to verify the performance, the proposed algorithm was compared with the GEI + 2D-PCA and SFDEI + HMM on the CASIA-B gait database. The experimental results have shown that the proposed algorithm performs better than GEI + 2D-PCA and SFDEI + HMM and meets the real-time requirements

An extracytoplasmic function sigma factor-dependent periplasmic glutathione peroxidase is involved in oxidative stress response of Shewanella oneidensis

AbstractBackgroundBacteria use alternative sigma factors (σs) to regulate condition-specific gene expression for survival and Shewanella harbors multiple ECF (extracytoplasmic function) σ genes and cognate anti-sigma factor genes. Here we comparatively analyzed two of the rpoE-like operons in the strain MR-1: rpoE-rseA-rseB-rseC and rpoE2-chrR.ResultsRpoE was important for bacterial growth at low and high temperatures, in the minimal medium, and high salinity. The degP/htrA orthologue, required for growth of Escherichia coli and Pseudomonas aeruginosa at high temperature, is absent in Shewanella, while the degQ gene is RpoE-regulated and is required for bacterial growth at high temperature. RpoE2 was essential for the optimal growth in oxidative stress conditions because the rpoE2 mutant was sensitive to hydrogen peroxide and paraquat. The operon encoding a ferrochelatase paralogue (HemH2) and a periplasmic glutathione peroxidase (PgpD) was identified as RpoE2-dependent. PgpD exhibited higher activities and played a more important role in the oxidative stress responses than the cytoplasmic glutathione peroxidase CgpD under tested conditions. The rpoE2-chrR operon and the identified regulon genes, including pgpD and hemH2, are coincidently absent in several psychrophilic and/or deep-sea Shewanella strains.ConclusionIn S. oneidensis MR-1, the RpoE-dependent degQ gene is required for optimal growth under high temperature. The rpoE2 and RpoE2-dependent pgpD gene encoding a periplasmic glutathione peroxidase are involved in oxidative stress responses. But rpoE2 is not required for bacterial growth at low temperature and it even affected bacterial growth under salt stress, indicating that there is a tradeoff between the salt resistance and RpoE2-mediated oxidative stress responses

Rotational paper-based electrochemiluminescence immunodevices for sensitive and multiplexed detection of cancer biomarkers

This paper describes a novel rotational paper-based analytical device (RPAD) to implement multi-step electrochemiluminescence (ECL) immunoassays. The integrated paper-based rotational valves can be easily controlled by rotating paper discs manually and this advantage makes it user-friendly to untrained users to carry out the multi-step assays. In addition, the rotational valves are reusable and the response time can be shortened to several seconds, which promotes the rotational paper-based device to have great advantages in multi-step operations. Under the control of rotational valves, multi-step ECL immunoassays were conducted on the rotational device for the multiplexed detection of carcinoembryonic antigen (CEA) and prostate specific antigen (PSA). The rotational device exhibited excellent analytical performance for CEA and PSA, and they could be detected in the linear ranges of 0.1-100 ngmL(-1) and 0.1-50 ng mL(-1) with detection limits down to 0.07 ng mL(-1) and 0.03 ng mL(-1), respectively, which were within the ranges of clinical concentrations. We hope this technique will open a new avenue for the fabrication of paper-based valves and provide potential application in clinical diagnostics. (C) 2017 Elsevier B.V. All rights reserved

Ratiometric fluorescent and electrochemiluminescent dual modal assay for detection of 2,6-pyridinedicarboxylic acid as an<i> anthrax</i> biomarker

2,6-pyridinedicarboxylic acid (DPA) is an excellent biomarker of Bacillus anthracis (B. anthracis). The sensitive detection of DPA, especially through visual point -of -care testing, was significant for accurate and rapid diagnosis of anthrax to timely prevent anthrax disease or biological terrorist attack. Herein, a ratiometric fluorescent (RFL) and electrochemiluminescent (ECL) dual -mode detection platform with a lanthanide ion -based metal -organic framework (Ln-MOF, i.e., M/Y-X: M = Eu, Y = Tb, and X = 4,4 ',4 ''-s-triazine-1,3,5-triyltri-m-aminobenzoic acid) was developed. Eu/Tb-TATAB nanoparticles were constructed to identify DPA. The R -FL detection platform quantitatively detected DPA by monitoring the I545/I617 ratio of the characteristic fluorescence peak intensities of Tb3+ ions and Eu3+ ions. The ECL sensing platform successfully quantified DPA by exploiting the burst effect of DPA on the ECL signal. The above methods had highly sensitive and rapid detection of DPA in water and serum samples. The results showed that this dual -mode detection platform may be projected to be a powerful instrument for preventing related biological warfare and bio-terrorism