Although reports of flow cytometry (FCM) applied to bacterial analysis are increasing, studies of FCM related to human cells still vastly outnumber other reports. However, current advances in FCM combined with a new generation of cellular reporter probes have made this technique suitable for analyzing physiological responses in bacteria. We review how FCM has been applied to characterize distin...

Fuzzy Cognitive Map (FCM) offers many advantages such intuitive knowledge representation and fast numerical reasoning ability, etc. It suits modeling and decision-making of dynamic systems. With the aims to effectively help to analyze and control system sustainable evolution, the paper defines the steady states of fixed point and limited cycle of a FCM modeling system. Accordingly, the rules of...

Segmentation in ultrasound images is challenging due to the interference from speckle noise and fuzziness of boundaries. In this paper, a segmentation scheme using fuzzy c-means (FCM) clustering incorporating both intensity and texture information of images is proposed to extract breast lesions in ultrasound images. Firstly, the nonlinear structure tensor, which can facilitate to refine the edg...

Dendritic cells (DCs) induce pathogen-specific T cell responses. We comprehensively studied the effects of addition of maturation stimulus, fibroblasts (fibroblast conditioned medium), PHA activated T cells (T cell conditioned medium), and mixture of fibroblast & PHA activated T cells (FCM-TCCM) conditioned media on maturation of DCs. Monocytes were cultured with GM-CSF and IL-4 for five days. ...

Robust methods for precise segmentation of breast region or volume from breast X-ray images, including mammogram and tomosynthetic image, is crucial for applications of these medical images. However, this task is challenging because the acquired images not only are inherent noisy and inhomogeneous, but there are also connected or overlapped artifacts, or noises on the images as well, due to loc...

As a powerful paradigm for knowledge representation and causal inference, Fuzzy Cognitive Map (FCM) has gradually emerged as a powerful modeling and simulation mechanism applicable to numerous research and application fields. However, conventional FCM theory greatly depends on the experts’ knowledge. The excessive subjective factors involved in the determination of FCM weights restrict accuracy...

The analysis of glucocorticoids excreted in feces is becoming a widespread technique for determining animal wellbeing in a wide variety of settings. In the present study an extraction protocol and an ELISA assay for quantifying fecal corticosterone metabolites (FCM) in BALB/c and C57bl/6 mice were validated. Lower ratios of solvent (ethanol) to mass of fecal sample were found to be sufficient i...

This paper proposes a new clustering algorithm which integrates Fuzzy C-means clustering with Markov random field (FCM). The density function of the first principal component which sufficiently reflects the class differences and is applied in determining of initial labels for FCM algorithm. Thus, the sensitivity to the random initial values can be avoided. Meanwhile, this algorithm takes into a...

To overcome the noise sensitiveness of conventional fuzzy c-means (FCM) clustering algorithm, a novel extended FCM algorithm for image segmentation is presented in this paper. The algorithm is developed by modifying the objective function of the standard FCM algorithm with a penalty term that takes into account the influence of the neighboring pixels on the centre pixels. The penalty term acts ...

background: flow cytometry (fcm) has been extensively used to study mammalian sperm in the areas of clinical andrology and reproductive toxicology. fcm provides a powerful advantage over microscopy technique in terms of rapid accurate and reproducible technology for the quantification of various cell characteristics including chromatin status. during spermiogenesis histones are replaced by prot...