Efficient 3D Face Recognition with Gabor Patched Spectral Regression

In this paper, we utilize a novel framework for 3D face recognition, called 3D Gabor Patched Spectral Regression (3D GPSR), which can overcome some of the continuing challenges encountered with 2D or 3D facial images. In this active field, some obstacles, like expression variations, pose correction and data noise deteriorate the performance significantly. Our proposed system addresses these problems by first extracting the main facial area to remove irrelevant information corresponding to shoulders and necks. Pose correction is used to minimize the influence of large pose variations and then the normalized depth and gray images can be obtained. Due to better time-frequency characteristics and a distinctive biological background, the Gabor feature is extracted on depth images, known as 3D Gabor faces. Data noise is mainly caused by distorted meshes, varieties of subordinates and misalignment. To solve these problems, we introduce a Patched Spectral Regression strategy, which can make good use of the robustness and efficiency of accurate patched discriminant low-dimension features and minimize the effect of noise term. Computational analysis shows that spectral regression is much faster than the traditional approaches. Our experiments are based on the CASIA and FRGC 3D face databases which contain a huge number of challenging data. Experimental results show that our framework consistently outperforms the other existing methods with the distinctive characteristics of efficiency, robustness and generality

Cross-Modality 2D-3D Face Recognition via Multiview Smooth Discriminant Analysis Based on ELM

In recent years, 3D face recognition has attracted increasing attention from worldwide researchers. Rather than homogeneous face data, more and more applications require flexible input face data nowadays. In this paper, we propose a new approach for cross-modality 2D-3D face recognition (FR), which is called Multiview Smooth Discriminant Analysis (MSDA) based on Extreme Learning Machines (ELM). Adding the Laplacian penalty constrain for the multiview feature learning, the proposed MSDA is first proposed to extract the cross-modality 2D-3D face features. The MSDA aims at finding a multiview learning based common discriminative feature space and it can then fully utilize the underlying relationship of features from different views. To speed up the learning phase of the classifier, the recent popular algorithm named Extreme Learning Machine (ELM) is adopted to train the single hidden layer feedforward neural networks (SLFNs). To evaluate the effectiveness of our proposed FR framework, experimental results on a benchmark face recognition dataset are presented. Simulations show that our new proposed method generally outperforms several recent approaches with a fast training speed

Helpful to Live Healthier? Intermittent Hypoxic/Ischemic Training Benefits Vascular Homeostasis and Lipid Metabolism with Activating SIRT1 Pathways in Overweight/Obese Individuals

Introduction: The present study aimed to investigate whether and how normobaric intermittent hypoxic training (IHT) or remote ischemic preconditioning (RIPC) plus normoxic training (RNT) has a synergistic protective effect on lipid metabolism and vascular function compared with normoxic training (NT) in overweight or obese adults. Methods: A total of 37 overweight or obese adults (36.03 ± 10.48 years) were randomly assigned to 3 groups: NT group (exercise intervention in normoxia), IHT group (exercise intervention in normobaric hypoxic chamber), and RNT group (exercise intervention in normoxia + RIPC twice daily). All participants carried out the same 1-h exercise intervention for a total of 4 weeks, 5 days per week. Physical fitness parameters were evaluated at pre- and postexercise intervention. Results: After training, all three groups had a significantly decreased body mass index (p < 0.05). The IHT group had reduced body fat percentage, visceral fat mass (p < 0.05), blood pressure (p < 0.01), left ankle-brachial index (ABI), maximal heart rate (HRmax) (p < 0.05), expression of peroxisome proliferator-activated receptor-γ (PPARγ) (p < 0.01) and increased expression of SIRT1 (p < 0.05), VEGF (p < 0.01). The RNT group had lowered waist-to-hip ratio, visceral fat mass, blood pressure (p < 0.05), and HRmax (p < 0.01). Conclusion: IHT could effectively reduce visceral fat mass and improve vascular elasticity in overweight or obese individuals than pure NT with the activation of SIRT1-related pathways. And RNT also produced similar benefits on body composition and vascular function, which were weaker than those of IHT but stronger than NT. Given the convenience and economy of RNT, both intermittent hypoxic and ischemic training have the potential to be successful health promotion strategies for the overweight/obese population

AD-linked R47H-TREM2 mutation induces disease-enhancing microglial states via AKT hyperactivation

The hemizygous R47H variant of triggering receptor expressed on myeloid cells 2 (TREM2), a microglia-specific gene in the brain, increases risk for late-onset Alzheimer’s disease (AD). Using transcriptomic analysis of single nuclei from brain tissues of patients with AD carrying the R47H mutation or the common variant (CV)–TREM2, we found that R47H-associated microglial subpopulations had enhanced inflammatory signatures reminiscent of previously identified disease-associated microglia (DAM) and hyperactivation of AKT, one of the signaling pathways downstream of TREM2. We established a tauopathy mouse model with heterozygous knock-in of the human TREM2 with the R47H mutation or CV and found that R47H induced and exacerbated TAU-mediated spatial memory deficits in female mice. Single-cell transcriptomic analysis of microglia from these mice also revealed transcriptomic changes induced by R47H that had substantial overlaps with R47H microglia in human AD brains, including robust increases in proinflammatory cytokines, activation of AKT signaling, and elevation of a subset of DAM signatures. Pharmacological AKT inhibition with MK-2206 largely reversed the enhanced inflammatory signatures in primary R47H microglia treated with TAU fibrils. In R47H heterozygous tauopathy mice, MK-2206 treatment abolished a tauopathy-dependent microglial subcluster and rescued tauopathy-induced synapse loss. By uncovering disease-enhancing mechanisms of the R47H mutation conserved in human and mouse, our study supports inhibitors of AKT signaling as a microglial modulating strategy to treat AD

Load Dependent Fatigue Crack Initiation in High Purity Al

Fatigue crack initiation sites and mechanisms in metals and alloys have long been investigated, since metal components are often subjected to cyclic loading, and fatigue cracking is one of the major causes of failure. Therefore, understanding the dominant cracking mechanism under different conditions is essential for tailoring the composition and microstructure of metal components for better fatigue resistance under various loading conditions. Load dependent fatigue response in high purity aluminum (Al) is investigated. In low cycle fatigue, extrusions and intrusions are found to form on grain boundaries (GBs), especially prevalently at triples junctions. However, contrary to theories on extrusion formation from persistent slip bands (PSBs), no slip bands are observed in these specimens. Dislocation cells, on the other hand, are observed to form in higher densities and smaller sizes as stress amplitude increases. As extrusion formation occurs only after a threshold number of cycles, it might be a result of the progression of dislocation cell formation. In high cycle fatigue, no extrusions are observed at GBs, while microcracks form within grains. Therefore, high cycle fatigue life may be controlled by mechanisms other than dislocation cell formation, and involves transgranular, rather than intergranular, fracture.Undergraduat