Lifespan extension and increased resistance to environmental stressors by N-Acetyl-L-Cysteine in Caenorhabditis elegans

OBJECTIVE: This study was performed to determine the effect of N-acetyl-L-cysteine, a modified sulfur-containing amino acid that acts as a strong cellular antioxidant, on the response to environmental stressors and on aging in C. elegans. METHOD: The survival of worms under oxidative stress conditions induced by paraquat was evaluated with and without in vivo N-acetyl-L-cysteine treatment. The effect of N-acetyl-L-cysteine on the response to other environmental stressors, including heat stress and ultraviolet irradiation (UV), was also monitored. To investigate the effect on aging, we examined changes in lifespan, fertility, and expression of age-related biomarkers in C. elegans after N-acetyl-L-cysteine treatment. RESULTS: Dietary N-acetyl-L-cysteine supplementation significantly increased resistance to oxidative stress, heat stress, and UV irradiation in C. elegans. In addition, N-acetyl-L-cysteine supplementation significantly extended both the mean and maximum lifespan of C. elegans. The mean lifespan was extended by up to 30.5% with 5 mM N-acetyl-L-cysteine treatment, and the maximum lifespan was increased by 8 days. N-acetyl-L-cysteine supplementation also increased the total number of progeny produced and extended the gravid period of C. elegans. The green fluorescent protein reporter assay revealed that expression of the stress-responsive genes, sod-3 and hsp-16.2, increased significantly following N-acetyl-L-cysteine treatment. CONCLUSION: N-acetyl-L-cysteine supplementation confers a longevity phenotype in C. elegans, possibly through increased resistance to environmental stressors

Jamming transition in a highly dense granular system under vertical vibration

The dynamics of the jamming transition in a three-dimensional granular system under vertical vibration is studied using diffusing-wave spectroscopy. When the maximum acceleration of the external vibration is large, the granular system behaves like a fluid, with the dynamic correlation function G(t) relaxing rapidly. As the acceleration of vibration approaches the gravitational acceleration g, the relaxation of G(t) slows down dramatically, and eventually stops. Thus the system undergoes a phase transition and behaves like a solid. Near the transition point, we find that the structural relaxation shows a stretched exponential behavior. This behavior is analogous to the behavior of supercooled liquids close to the glass transition.Comment: 5 pages, 5 figures, accepted by Phys. Rev.

Co-occurrence matrix analysis-based semi-supervised training for object detection

One of the most important factors in training object recognition networks using convolutional neural networks (CNNs) is the provision of annotated data accompanying human judgment. Particularly, in object detection or semantic segmentation, the annotation process requires considerable human effort. In this paper, we propose a semi-supervised learning (SSL)-based training methodology for object detection, which makes use of automatic labeling of un-annotated data by applying a network previously trained from an annotated dataset. Because an inferred label by the trained network is dependent on the learned parameters, it is often meaningless for re-training the network. To transfer a valuable inferred label to the unlabeled data, we propose a re-alignment method based on co-occurrence matrix analysis that takes into account one-hot-vector encoding of the estimated label and the correlation between the objects in the image. We used an MS-COCO detection dataset to verify the performance of the proposed SSL method and deformable neural networks (D-ConvNets) as an object detector for basic training. The performance of the existing state-of-the-art detectors (DConvNets, YOLO v2, and single shot multi-box detector (SSD)) can be improved by the proposed SSL method without using the additional model parameter or modifying the network architecture.Comment: Submitted to International Conference on Image Processing (ICIP) 201

Mechanochemical Synthesis and Rapid Consolidation of Nanocrystalline 3NiAl- Al

Nanopowders of 3NiAl and Al2O3 were synthesized from 3NiO and 5Al powders by high-energy ball milling. Nanocrystalline Al2O3 reinforced composite was consolidated by high-frequency induction-heated sintering within 3 minutes from mechanochemically synthesized powders of Al2O3 and 3NiAl. The advantage of this process is that it allows very quick densification to near theoretical density and inhibition grain growth. Nanocrystalline materials have received much attention as advanced engineering materials with improved physical and mechanical properties. The relative density of the composite was 97%. The average Vickers hardness and fracture toughness values obtained were 804 kg/mm2 and 7.5 MPa⋅m1/2, respectively