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With digitisation and the development of computer-aided diagnosis, histopathological image analysis has attracted considerable interest in recent years. In this article, we address the problem of the automated annotation of skin biopsy images, a special type of histopathological image analysis. In contrast to previous well-studied methods in histopathology, we propose a novel annotation method based on a multi-instance learning framework. The proposed framework first represents each skin biopsy image as a multi-instance sample using a graph cutting method, decomposing the image to a set of visually disjoint regions. Then, we construct two classification models using multi-instance learning algorithms, among which one provides determinate results and the other calculates a posterior probability. We evaluate the proposed annotation framework using a real dataset containing 6691 skin biopsy images, with 15 properties as target annotation terms. The results indicate that the proposed method is effective and medically acceptable. [ABSTRACT FROM AUTHOR]

Individuals often predict consequences, particularly emotional consequences, according to emotional or non-emotional signals conveyed by environmental cues (i.e., emotional and non-emotional cues, respectively). Some of these cues signify the consequences with certainty (i.e., certain cues), whereas others do not (i.e., uncertain cues). Several event-related potential (ERP) studies regarding non-emotional cues have suggested that the effects of cue uncertainty on attention to emotional events occur in both perception and evaluation processes. However, due to the limitations of previous studies, it is unclear what the effects of cue uncertainty would be in an emotional cue condition. Moreover, it is uncertain whether the effects of cue uncertainty are affected by cue valence (i.e., emotional and non-emotional cues). To address these questions, we asked participants to view cues and then to view emotional (positive or negative) pictures. The cues either did or did not indicate the emotional content of the picture. In the emotional cue condition, happy and fearful faces were used as certain cues indicating upcoming positive and negative pictures, respectively, and neutral faces were used as uncertain cues. In the non-emotional cue condition, scrambled faces outlined in red and blue indicated upcoming positive and negative pictures, respectively, and scrambled faces outlined in green served as uncertain cues. The results showed that for negative pictures, ERP responses in a time range between 60 and 1,000 ms were shifted to a more negative direction in a certain condition than in the uncertain condition when the cues were emotional. However, the effect was the reverse for positive pictures. This effect of cue uncertainty was similar in the non-emotional cue—negative condition. In contrast, there was no effect of cue uncertainty in the non-emotional cue—positive condition. Therefore, the findings indicate that cue uncertainty modulates attention toward emotional events when the events are signified by emotional cues. The findings may also suggest that cue valence modulates the effects of cue uncertainty on attention to emotional events.

The modification of protein cysteine residues underlies some of the diverse biological functions of nitric oxide (NO) in physiology and disease. The formation of stable nitrosothiols occurs under biologically relevant conditions and time scales. However, the factors that determine the selective nature of this modification remain poorly understood, making it difficult to predict thiol targets and thus construct informatics networks. In this review, the biological chemistry of NO will be considered within the context of nitrosothiol formation and degradation whilst considering how specificity is achieved in this important post-translational modification. Since nitrosothiol formation requires a formal one-electron oxidation, a classification of reaction mechanisms is proposed regarding which species undergoes electron abstraction: NO, thiol or S-NO radical intermediate. Relevant kinetic, thermodynamic and mechanistic considerations will be examined and the impact of sources of NO and the chemical nature of potential reaction targets is also discussed.

Nuclear thermal propulsion (NTP) is regarded as the preferred option for the upcoming crewed interstellar exploration due to its excellent performance compared to the current most advanced chemical propulsion systems. Over the past several decades, many novel concepts have been proposed, among which the particle bed reactor (PBR) is the most efficient, compact, and lightweight method. Its unique features, such as the extremely high power density and the radial flow path of coolant in the fuel region, introduce many challengeable issues to the thermal hydraulic design of PBR, with the flow distribution being representative. In this work, the flow distribution process within the core is analyzed based on the understanding of the axial pressure profile in a dummy PBR. A “flow shift” phenomenon leading to the hot spot in the core is introduced first, and three methods, i.e., decreasing the pressure drop within the hot gas channel, increasing the flow resistance on the cold frit or hot frit, and changing the flow pattern from “Z” to “U”, are proposed to reduce the “flow shift” and the consequent temperature mal-distribution. The pros and cons of using cold frit or hot frit to distribute the coolant are also discussed. Finally, by using three numerical examples, these analyses are demonstrated. The findings here may provide technical support for PBR design.