A local electrochemical impedance study of the self-healing properties of waterborne coatings on 2024 aluminium alloy

In the present work the processes involved in the degradation of a coated 2024 aluminium alloy from an artificial scratch were investigated by local electrochemical impedance spectroscopy (LEIS). The aim was to assess the self-healing process linked to the release of inhibitive pigments from the coatings. A comparison is provided for the local behaviour of a chromated coating, currently used in the aeronautic industry, and a Cr-free system. Local impedance diagrams were obtained above the scratched areas for different exposure times to the electrolyte (1mM NaCl). For the chromated sample, the impedance values were high and increased with time, clearly showing a significant inhibition in the scratch. In contrast, for the Cr-free coating, impedance values were lower and in several areas, corrosion products appeared in the scratch. In these corroded zones, after several days of immersion, the diagrams have similar shape as that observed on bare 2024 aluminium alloy. Mappings, performed at 3Hz, for different exposure times to the electrolyte also clearly showed the self-healing process in the presence of chromates or the development of the corrosion for the unchromated coating. At 1kHz, similar mappings were observed for the two systems providing support to the fact that the coatings presented good adhesion to the substrate. It must be emphasized that LEIS gives a fast response on the efficacy of the inhibitive pigments and thus, complements the information obtained from the conventional EIS technique

Incorporating Stratified Negation into Query-Subquery Nets for Evaluating Queries to Stratified Deductive Databases

Most of the previously known evaluation methods for deductive databases are either breadth-first or depth-first (and recursive). There are cases when these strategies are not the best ones. It is desirable to have an evaluation framework for stratified DatalogN that is goal-driven, set-at-a-time (as opposed to tuple-at-a-time) and adjustable w.r.t. flow-of-control strategies. These properties are important for efficient query evaluation on large and complex deductive databases. In this paper, by incorporating stratified negation into so-called query-subquery nets, we develop an evaluation framework, called QSQNSTR, with such properties for evaluating queries to stratified DatalogN databases. A variety of flow-of-control strategies can be used for QSQNSTR. The generic evaluation method QSQNSTR for stratified DatalogN is sound, complete and has a PTIME data complexity

THE REAL-WORLD-SEMANTICS INTERPRETABILITY OF LINGUISTIC RULE BASES AND THE APPROXIMATE REASONING METHOD OF FUZZY SYSTEMS

The real-world-semantics interpretability concept of fuzzy systems introduced in [1] is new for the both methodology and application and is necessary to meet the demand of establishing a mathematical basis to construct computational semantics of linguistic words so that a method developed based on handling the computational semantics of linguistic terms to simulate a human method immediately handling words can produce outputs similar to the one produced by the human method. As the real world of each application problem having its own structure which is described by certain linguistic expressions, this requirement can be ensured by imposing constraints on the interpretation assigning computational objects in the appropriate computational structure to the words so that the relationships between the computational semantics in the computational structure is the image of relationships between the real-world objects described by the word-expressions. This study will discuss more clearly the concept of real-world-semantics interpretability and point out that such requirement is a challenge to the study of the interpretability of fuzzy systems, especially for approaches within the fuzzy set framework. A methodological challenge is that it requires both the computational expression representing a given linguistic fuzzy rule base and an approximate reasoning method working on this computation expression must also preserve the real-world semantics of the application problem. Fortunately, the hedge algebra (HA) based approach demonstrates the expectation that the graphical representation of the rule of fuzzy systems and the interpolation reasoning method on them are able to preserve the real-world semantics of the real-world counterpart of the given application problem

Effect of cerium salt-activated ceria on the UV degradation resistance of waterborne epoxy coatings

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Bake hardening effect of the low strength interstitial free steel

This paper investigates the influence of pre-strain and temperature on the bake hardening (BH) effect of the low strength interstitial free (IF) steel with the yield strength of 137 MPa. The tensile specimens were pre-strained to 2-4-6 % at room temperature followed by baking at temperatures of 150-200-250 oC for 20 minutes. The BH strength was determined by a standard procedure based on the difference between the lower yield strength of the baked specimen and the flow stress of the initial one. The microstructure of the IF steels was characterized by optical microscopy and scanning electron microscopy for the purpose of explaining the BH effect. All the initial and baked steels show a microstructure that includes the ferrite phase, of an average grains size of 45 µm. This observation was consistent with the mechanical properties of the initial steel. The BH strengths have been achieved from 12 to 35 MPa, in which the maximum value was found for the specimen that pre-strained to 6 % and baked at 200 oC. The BH strengths increased with increasing the pre-strain, but slightly decreased when the baking temperature was 250 oC. This mechanism is attributed to pinning of dislocation by carbon solute atoms during the baking process, and the BH strength was correlated with grain boundary segregation

Channel and spatial attention mechanism for fashion image captioning

Image captioning aims to automatically generate one or more description sentences for a given input image. Most of the existing captioning methods use encoder-decoder model which mainly focus on recognizing and capturing the relationship between objects appearing in the input image. However, when generating captions for fashion images, it is important to not only describe the items and their relationships, but also mention attribute features of clothes (shape, texture, style, fabric, and more). In this study, one novel model is proposed for fashion image captioning task which can capture not only the items and their relationship, but also their attribute features. Two different attention mechanisms (spatial-attention and channel-wise attention) is incorporated to the traditional encoder-decoder model, which dynamically interprets the caption sentence in multi-layer feature map in addition to the depth dimension of the feature map. We evaluate our proposed architecture on Fashion-Gen using three different metrics (CIDEr, ROUGE-L, and BLEU-1), and achieve the scores of 89.7, 50.6 and 45.6, respectively. Based on experiments, our proposed method shows significant performance improvement for the task of fashion-image captioning, and outperforms other state-of-the-art image captioning methods