In the ship and offshore structure design, age-related problems such as corrosion damage, local denting, and fatigue damage are important factors to be considered in building a reliable structure as they have a significant influence on the residual structural capacity. In shipping, corrosion addition methods are widely adopted in structural design to prevent structural capacity degradation. The present study focuses on the historical trend of corrosion addition rules for ship structural design and investigates their effects on the ultimate strength performance such as hull girder and stiffened panel of double hull oil tankers. Three types of rules based on corrosion addition models, namely historic corrosion rules (pre-CSR), Common Structural Rules (CSR), and harmonised Common Structural Rules (CSRH) are considered and compared with two other corrosion models namely UGS model, suggested by the Union of Greek Shipowners (UGS), and Time-Dependent Corrosion Wastage Model (TDCWM). To identify the general trend in the effects of corrosion damage on the ultimate longitudinal strength performance, the corrosion addition rules are applied to four representative sizes of double hull oil tankers namely Panamax, Aframax, Suezmax, and VLCC. The results are helpful in understanding the trend of corrosion additions for tanker structures
The present study is aimed at testing the antidepressant--like effects and probable mechanisms of action of low molecular mass chondroitin sulfate (LMMCS) on depression induced by chronic unpredictable mild stress (CUMS) in mice. Four weeks of CUMS exposure resulted in depressive-like behavior, expressed by a significant decrease in the locomotor activity and sucrose consumption and increased immobility time in the forced swim test. Further, there was a significant reduction of 5-HT level in the hippocampus region of depressed mice. Treatment of mice for four weeks with LMMCS ameliorated significantly both the behavioral and biochemical changes induced by CUMS. These novel results suggest that LMMCS produces an antidepressant-like effect in mice subjected to CUMS, which might be related, at least in part, to the increase of 5-HT concentration in the hippocampus.
Sparse coding is currently an active topic in signal processing and pattern recognition. Meta Face Learning (MFL) isatypical sparse coding method and exhibits promising performance for classification. Unfortunately, due to using the l1-norm minimization, MFLis expensive to compute and is not robust enough. To address these issues, this paper proposesafaster and more robust version of MFLwith the l2-norm regularization constraint on coding coefficients. The proposed method is used to learnaclass-specific dictionary for facial expression recognition. Extensive experiments on two popular facial expression databases, i.e., the JAFFEdatabase and the Cohn-Kanade database, demonstrate that our method shows promising computational efficiency and robustness on facial expression recognition tasks.