Search Results (7)

Automatic anomaly detection plays a critical role in surveillance systems but requires datasets comprising large amounts of annotated data to train and evaluate models. Gathering and annotating these data is a labor-intensive task that can become costly. A way to circumvent this is to use synthetic data to augment anomalies directly into existing datasets. This far more diverse scenario can be created and come directly with annotations. This however also poses new issues for the computer-vision engineer and researcher end users, who are not readily familiar with 3D modeling, game development, or computer graphics methodologies and must rely on external specialists to use or tweak such pipelines. In this paper, we extend our previous work of an application that synthesizes dataset variations using 3D models and augments anomalies on real backgrounds using the Unity Engine. We developed a high-usability user interface for our application through a series of RITE experiments and evaluated the final product with the help of deep-learning specialists who provided positive feedback regarding its usability, accessibility, and user experience. Finally, we tested if the proposed solution can be used in the context of traffic surveillance by augmenting the train data from the challenging Street Scene dataset. We found that by using our synthetic data, we could achieve higher detection accuracy. We also propose the next steps to expand the proposed solution for better usability and render accuracy through the use of segmentation pre-processing. Full article

Al₂O₃-forming austenitic steel (AFA steel) is an important candidate material for advanced reactor core components due to its excellent corrosion resistance and high temperature strength. Al is a strong ferrite-forming element. Therefore, it is necessary to increase the Ni content to stabilize austenite. Ni is expensive and highly active, and so increasing the Ni content not only increases the costs but also damages the radiation resistance. Mn is a low-cost austenitic stable element. Its substitution for Ni will not only help to improve the irradiation resistance of austenitic steel, but also reduce the cost. In order to explore the feasibility of Mn-substituted Ni-stabilized austenite in AFA steel, this paper summarized the research progress of Mn-added AFA steels, whilst the research status of traditional Mn-added austenitic steels are also referred to and compared herein. The effect of the addition of Mn on the microstructure and properties of AFA steel was analyzed. The results show that Mn can promote the precipitation of the M₂₃C₆ phase and inhibit the precipitation of the B2-NiAl phase and secondary NbC phase. With the increase in Mn content, the strength of AFA steel at room temperature and high temperature decreased slightly, the room temperature elongation increased slightly, while the high temperature elongation and creep resistance decreased obviously. In addition, for austenitic steel free of Al, the addition of Mn will destroy the oxide layer of Cr₂O₃, which will decrease the oxidation resistance of the steel. But the preliminary study shows that Mn has little effect on the Al₂O₃ oxide layer. It is worth studying the effect of Mn-substituted Ni on the oxidation resistance of AFA steel. In summary, more efforts are necessary to investigate the optimal Mn content to balance the advantages and disadvantages of introducing Mn instead of Ni. Full article

Enzymes are essential catalysts for various chemical reactions in biological systems and often rely on metal ions or cofactors to stabilize their structure or perform functions. Improving enzyme performance has always been an important direction of protein engineering. In recent years, various artificial small molecules have been successfully used in enzyme engineering. The types of enzymatic reactions and metabolic pathways in cells can be expanded by the incorporation of these artificial small molecules either as cofactors or as building blocks of proteins and nucleic acids, which greatly promotes the development and application of biotechnology. In this review, we summarized research on artificial small molecules including biological metal cluster mimics, coenzyme analogs (mNADs), designer cofactors, non-natural nucleotides (XNAs), and non-natural amino acids (nnAAs), focusing on their design, synthesis, and applications as well as the current challenges in synthetic biology. Full article

Megabalanus coccopoma (Darwin, 1854) is a globally invasive species in Balanomorpha (Crustacea). This species is a model organism for studying marine pollution and ecology. However, its mitogenome remains unknown. The mitogenome sequencing of M. coccopoma is completed in the present study. It has a 15,098 bp in length, including 13 protein-coding genes (PCGs), 2 ribosomal RNAs (rRNAs), 22 transfer RNAs (tRNAs), along with a putative regulatory area. A substantial A+T bias was observed in the genome composition (68.2%), along with a negative AT (0.82) and GC (−0.136) skew. Compared to the gene sequence of the ground model of pan-crustacea, 13 gene clusters (or genes), such as 10 tRNAs and 3 PCGs, were observed in a different order. This was in line with the previously observed large-scale gene rearrangements of Balanomorpha. Among the 37 genes, the gene cluster (M-nad2-W-cox1-L₂-cox2-D-atp8-atp6-cox3-G- nad3-R-N-A-E-S₁) Balanomorpha was conserved. Furthermore, phylogeny analysis indicated that the existing Balanomorpha species family was divided into nine rearrangement patterns, supporting the polyphyly of Balanoidea. Full article

In this paper, a novel composite fault diagnosis method combining adaptive feature mode decomposition (FMD) and minimum noise amplitude deconvolution (MNAD) is proposed. Firstly, chaos mapping and leader mutation selection strategy were introduced to improve the Northern Goshawk algorithm (NGO), and a chaotic leadership Northern Goshawk optimization (CLNGO) algorithm was proposed. The advantages of the CLNGO algorithm in convergence accuracy and speed were verified by 12 benchmark functions. Then, a new index called sparse pulse and cyclicstationarity (SPC) is proposed to evaluate signal sparsity. Finally, SPC is used as the fitness function of CLNGO to optimize FMD and MNAD. The optimal decomposition mode n and filter length of FMD, and filter length L and noise ratio $\rho$ of MNAD are selected. The CLNGO-FMD is used to decompose signal into different modes. The signal is reconstructed based on the kurtosis criterion and the CLNGO-MNAD method is used to reduce the noise of the reconstructed signal twice. The experimental results show that the proposed method can achieve the enhancement of weak features and the removal of noise to extract the fault feature frequency adaptively. Compared with EMD, VMD, MOMEDA, MCKD and other methods, the proposed method has better performance in fault feature frequency extraction, and it is effective for the diagnosis of single faults and composite faults. Full article

Microstructure and corrosion behavior of the Mg-3Al-xMn (x = 0, 0.12, 0.21, 0.36, 0.45) (hereafter in wt.%) alloys were experimentally investigated by electron probe microanalysis (EPMA), scanning electron microscope equipped with energy dispersive X-ray spectroscopy (SEM/EDX), X-ray diffraction (XRD), electrochemical, and hydrogen evolution tests. A new self-constructed Mg-Al-Mn-Fe thermodynamic database was used to predict the solidification paths of the alloys. The addition of Mn showed no grain refinement in the cast Mg-3Al alloys. According to the microstructure observation, Al-Fe phases were observed in the non-Mn-added alloy, while Al₈Mn₅(LT) (Al₈Mn₅ in low temperature) became the main intermetallic phase in the Mn-added alloys, and the amount increased gradually with the Mn addition. The τ–Al_0.89Mn_1.11 phase with lower Al/(Fe + Mn) ratio was observed in the alloys with 0.36 and 0.45 wt.% Mn content. According to the electrochemical tests, all five alloys showed localized corrosion characteristics in 3.5 wt.% NaCl solution. Compared with the Mg-3Al alloy, the corrosion resistance of Mn-added alloys were significantly improved and increased gradually with the Mn addition, which was due to the variation of Al-containing intermetallic compounds. The present experimental investigations and thermodynamic calculations confirmed the mechanism that the increasing amount of Al₈Mn₅(LT) with Mn addition could encapsulate the B2-Al(Mn,Fe) phase with higher Fe. Therefore, it could prevent this detrimental phase from contacting magnesium matrix, thus suppressing micro-galvanic corrosion and improving corrosion resistance gradually. Full article

The process of using fungal-colored wood (spalted wood) for marquetry and intarsia woodworks in Italy and Germany was very popular from the 1400–1600s, with some instances continuing as late as the 1800s. While spalted marquetry in these countries is relatively well documented, less is known about its use in other parts of Europe. One of the primary reasons for this lack of knowledge is the difficulty in identifying spalted wood, especially the blue-green variety produced from Chlorociboria species, from wood dyed with copper-based compounds or other synthetics. The most reliable testing method involves destructive sampling, where a small piece is taken from the work, the pigment extracted, and an analysis performed. Such sampling is simply not feasible, nor often allowed, on ancient artwork. To make a reliable, non-destructive identification of spalted wood, a visual method based on anatomical characteristics of spalted wood was developed to differentiate spalted wood from dyed wood. High-resolution pictures were taken from wooden artifacts containing blue-green colored wood in collections at the National Museum of Decorative Arts (MNAD), the Royal Site Monastery El Escorial and the Bilbao Museum of Fine Arts in Spain. The concentration of pigment in the rays, the color distribution, the size of the piece and the date of production, were analyzed. With the use of this new visual method, it was possible to determine that intarsia artifacts, held in Spain but of Augsburg origin from the 1500–1600s, contained spalted wood details. Meanwhile, Spanish and Italian intarsia artifacts from the 1800s were found to only contain dyed wood. Full article