atigue reliability evaluation technique using probabilistic stress-life method for stress range frequency distribution of a steel welding member

In this paper, we present a technique for fatigue reliability evaluation of a steel welding member. The probabilistic stress-life method is an important one for the fatigue reliability evaluation of a steel welding member. In this method, the stress range frequency distribution of the stress history of a steel welding member defined as a loading block is obtained from the stress frequency analysis and the parameters of the probability distribution for the stress range frequency distribution are used for numerical simulation. The probability of failure of the steel welding member under loading block is obtained from the Monte Carlo Simulation in conjunction with the Miner’s Rule, the Modified Miner’s Rule, and the Haibach’s Rule for fatigue damage evaluation. Through this procedure, a fatigue reliability evaluation that can predict the number of loading block of failure and the residual fatigue life is possible

Customs Import Declaration Datasets

Given the huge volume of cross-border flows, effective and efficient control of trade becomes more crucial in protecting people and society from illicit trade. However, limited accessibility of the transaction-level trade datasets hinders the progress of open research, and lots of customs administrations have not benefited from the recent progress in data-based risk management. In this paper, we introduce an import declaration dataset to facilitate the collaboration between domain experts in customs administrations and researchers from diverse domains, such as data science and machine learning. The dataset contains 54,000 artificially generated trades with 22 key attributes, and it is synthesized with conditional tabular GAN while maintaining correlated features. Synthetic data has several advantages. First, releasing the dataset is free from restrictions that do not allow disclosing the original import data. The fabrication step minimizes the possible identity risk which may exist in trade statistics. Second, the published data follow a similar distribution to the source data so that it can be used in various downstream tasks. Hence, our dataset can be used as a benchmark for testing the performance of any classification algorithm. With the provision of data and its generation process, we open baseline codes for fraud detection tasks, as we empirically show that more advanced algorithms can better detect fraud.Comment: Datasets: https://github.com/Seondong/Customs-Declaration-Dataset

RGB-D Mapping and Tracking in a Plenoxel Radiance Field

Building on the success of Neural Radiance Fields (NeRFs), recent years have seen significant advances in the domain of novel view synthesis. These models capture the scene's volumetric radiance field, creating highly convincing dense photorealistic models through the use of simple, differentiable rendering equations. Despite their popularity, these algorithms suffer from severe ambiguities in visual data inherent to the RGB sensor, which means that although images generated with view synthesis can visually appear very believable, the underlying 3D model will often be wrong. This considerably limits the usefulness of these models in practical applications like Robotics and Extended Reality (XR), where an accurate dense 3D reconstruction otherwise would be of significant value. In this technical report, we present the vital differences between view synthesis models and 3D reconstruction models. We also comment on why a depth sensor is essential for modeling accurate geometry in general outward-facing scenes using the current paradigm of novel view synthesis methods. Focusing on the structure-from-motion task, we practically demonstrate this need by extending the Plenoxel radiance field model: Presenting an analytical differential approach for dense mapping and tracking with radiance fields based on RGB-D data without a neural network. Our method achieves state-of-the-art results in both the mapping and tracking tasks while also being faster than competing neural network-based approaches.Comment: *The two authors contributed equally to this pape

HaRiM+^+: Evaluating Summary Quality with Hallucination Risk

One of the challenges of developing a summarization model arises from the difficulty in measuring the factual inconsistency of the generated text. In this study, we reinterpret the decoder overconfidence-regularizing objective suggested in (Miao et al., 2021) as a hallucination risk measurement to better estimate the quality of generated summaries. We propose a reference-free metric, HaRiM+, which only requires an off-the-shelf summarization model to compute the hallucination risk based on token likelihoods. Deploying it requires no additional training of models or ad-hoc modules, which usually need alignment to human judgments. For summary-quality estimation, HaRiM+ records state-of-the-art correlation to human judgment on three summary-quality annotation sets: FRANK, QAGS, and SummEval. We hope that our work, which merits the use of summarization models, facilitates the progress of both automated evaluation and generation of summary.Comment: 9 pages (+ 21 pages of Appendix), AACL 202

CO ameliorates cellular senescence and aging by modulating the miR-34a/Sirt1 pathway

Oxidative stress is recognised as a key factor that can lead to cellular senescence and aging. Carbon monoxide (CO) is produced by haemoxygenase-1 (HO-1), which exerts cytoprotective effects in aging-related diseases, whereas the effect of CO on cellular senescence and aging has not been elucidated. In the current study, we clearly demonstrated that CO delays the process of cellular senescence and aging through regulation of miR-34a and Sirt1 expression. CO reduced H2O2-induced premature senescence in human diploid fibroblast WI-38 cells measured with SA-beta-Gal-staining. Furthermore, CO significantly decreased the expression of senescence-associated secretory phenotype (SASP), including TNF-alpha IL-6, and PAI-1 and increased the transcriptional levels of antioxidant genes, such as HO-1 and NQO1. Moreover, CO apparently enhanced the expression of Sirt1 through down-regulation of miR-34a. Next, to determine whether Sirt1 mediates the inhibitory effect of CO on cellular senescence, we pre-treated WI-38 cells with the Sirt1 inhibitor Ex527 and a miR-34a mimic followed by the administration of H2O2 and evaluated the expression of SASP and antioxidant genes as well as ROS production. According to our results, Sirt1 is crucial for the antiaging and antioxidant effects of CO. Finally, CO prolonged the lifespan of Caenorhabditis elegans and delayed high-fat diet-induced liver aging. Taken together, these findings demonstrate that CO reduces cellular senescence and liver aging through the regulation of miR-34a and Sirt1.

GSK-3β inhibition by curcumin mitigates amyloidogenesis via TFEB activation and anti-oxidative activity in human neuroblastoma cells

© 2020 Informa UK Limited, trading as Taylor & Francis Group.The translocation of transcription factor EB (TFEB) to the nucleus plays a pivotal role in the regulation of basic cellular processes, such as lysosome biogenesis and autophagy. Autophagy is an intracellular degradation system that delivers cytoplasmic constituents to the lysosome, which is important in maintaining cellular homeostasis during environmental stress. Furthermore, oxidative stress is a critical cause for the progression of neurodegenerative diseases. Curcumin has anti-oxidative and anti-inflammatory activities, and is expected to have potential therapeutic effects in various diseases. In this study, we demonstrated that curcumin regulated TFEB export signalling via inhibition of glycogen synthase kinase-3β (GSK-3β); GSK-3β was inactivated by curcumin, leading to reduced phosphorylation of TFEB. We further showed that H2O2-induced oxidative stress was reduced by curcumin via the Nrf2/HO-1 pathway in human neuroblastoma cells. In addition, we showed that curcumin induced the degradation of amyloidogenic proteins, including amyloid-β precursor protein and α-synuclein, through the TFEB-autophagy/lysosomal pathway. In conclusion, curcumin regulates autophagy by controlling TFEB through the inhibition of GSK-3β, and increases antioxidant gene expression in human neuroblastoma cells. These results contribute to the development of novel cellular therapies for neurodegenerative diseases.