An intelligent tropical cyclone eye fix system using motion field analysis

Tropical cyclones (TCs) are weather systems with vast destructive power. Accurate location of their circulation centers, or "eyes", is thus important to forecasters. However, the eye fix process is often done manually in practice. While multiple factors are considered in the process, with subjective elements in these methods, forecasters could disagree. This paper describes a TC eye fix system that uses a novel motion field structure analysis method. It can handle TCs without well-defined structure that are partially out of the image. The systems also adapts user inputs and past results to improve its accuracy. Implemented on a commodity desktop computer, the system can process about 5 images per minute, giving an average error of about 0.16 degrees in latitude/longitude on Mercator projected map for TCs that are completely inside the radar image. This is well within the relative error of about 0.3-0.4 degrees given by different TC warning centers. This TC eye fix system is useful in giving an objective TC center location in contrast to traditional manual analysis. © 2005 IEEE.published_or_final_versio

Fast rotation center identification methods for video sequences

Rotational motion can often be seen in video. However, comparatively little research has been done to investigate rotational motions in video, whose analysis could be useful. For example, if we can efficiently identify the rotation center of a spinning object, extraction and tracking of it can be made easier by grouping points moving at the same radial speed. It could also improve compression by synthesizing analyzed spin transitions, and help tracking of rotating objects. In this paper, we introduce a set of rotation center location methods using only the motion field constructed during video encoding, along with a few methods for improving their performances. These methods can be implemented using integer operations only. They are up to 1.81 times faster than the traditional circulation analysis method with little sacrifice in accuracy, and are not affected by asymmetric fields caused by translational motions. © 2005 IEEE.published_or_final_versio

On discovery of extremely low-dimensional clusters using semi-supervised projected clustering

Recent studies suggest that projected clusters with extremely low dimensionality exist in many real datasets. A number of projected clustering algorithms have been proposed in the past several years, but few can identify clusters with dimensionality lower than 10% of the total number of dimensions, which are commonly found in some real datasets such as gene expression profiles. In this paper we propose a new algorithm that can accurately identify projected clusters with relevant dimensions as few as 5% of the total number of dimensions. It makes use of a robust objective function that combines object clustering and dimension selection into a single optimization problem. The algorithm can also utilize domain knowledge in the form of labeled objects and labeled dimensions to improve its clustering accuracy. We believe this is the first semi-supervised projected clustering algorithm. Both theoretical analysis and experimental results show that by using a small amount of input knowledge, possibly covering only a portion of the underlying classes, the new algorithm can be further improved to accurately detect clusters with only 1% of the dimensions being relevant. The algorithm is also useful in getting a target set of clusters when there are multiple possible groupings of the objects. © 2005 IEEE.published_or_final_versio

HARP: A practical projected clustering algorithm

In high-dimensional data, clusters can exist in subspaces that hide themselves from traditional clustering methods. A number of algorithms have been proposed to Identify such projected clusters, but most of them rely on some user parameters to guide the clustering process. The clustering accuracy can be seriously degraded If incorrect values are used. Unfortunately, in real situations, it is rarely possible for users to supply the parameter values accurately, which causes practical difficulties in applying these algorithms to real data. In this paper, we analyze the major challenges of projected clustering and suggest why these algorithms need to depend heavily on user parameters. Based on the analysis, we propose a new algorithm that exploits the clustering status to adjust the internal thresholds dynamically without the assistance of user parameters. According to the results of extensive experiments on real and synthetic data, the new method has excellent accuracy and usability. It outperformed the other algorithms even when correct parameter values were artificially supplied to them. The encouraging results suggest that projected clustering can be a practical tool for various kinds of real applications.published_or_final_versio

Rhinovirus – From bench to bedside

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Growth and endocrine disrupting effects of the mycotoxins zeralenone and aflatoxin B1 on breast cancer cells

Zearalenone (ZEA) and aflatoxin B1 (AFB1) are secondary metabolites produced by the fungi Fusarium and Aspergillus respectively. ZEA is proven to be an estrogenic endocrine disruptor since 1950s, while AFB1 is recently found to disrupt steroidogenesis in placenta. Both mycotoxins are constant contaminants of cereals worldwide and can both be found at significant levels in human plasma/urine of people in developing countries. Due to the co-occurrence of ZEA and AFB1 in food and human samples and the possibility of endocrine disruptors to modulate the growth of hormonal dependent breast cancer, we hypothesized that exposure to ZEA and AFB1 would affect the growth and cell cycle progression of breast cancer cells by modulating gene expressions and disrupting steroidogenesis and hormone …postprin

A new semiquantitative culture method for early detection of surgical incisional wound infection

A semiquantitative culture technique for early detection of surgical wound infection was done by rolling a segment of a plastic intravenous catheter across a blood agar plate after insertion into the most inflamed part of the wound on postoperative day 3. Patients were monitored daily for purulent discharge until healing. Of the 53 wounds studied, 44 (83%) had no growth or low-density superficial colonization on the blood agar (generally 15 colony-forming units and a diffuse subcutaneous pattern (colonies below the upper 1.5 cm of the catheter), all developed purulent discharge with a positive culture of the same organisms found by semiquantitative culture. This result differed significantly (P < .01) from the 44 wounds without subsequent infection. This semiquantitative technique has the potential to distinguish infection from colonization and may be useful in diagnosing surgical wound infection.published_or_final_versio

Complete genomic sequence of Epstein-Barr virus in nasopharyngeal carcinoma cell line C666-1

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Human enterovirus 71 and hand, foot and mouth disease

Hand, foot and mouth disease (HFMD) is generally a benign febrile exanthematous childhood disease caused by human enteroviruses. The route of transmission is postulated to be faeco-oral in developing areas but attributed more to respiratory droplet in developed areas. Transmission is facilitated by the prolonged environmental survival of these viruses and their greater resistance to biocides. Serious outbreaks with neurological and cardiopulmonary complications caused by human enterovirus 71 (HEV-71) seem to be commoner in the Asian Pacific region than elsewhere in the world. This geographical predilection is unexplained but could be related to the frequency of intra- and inter-typic genetic recombinations of the virus, the host populations' genetic predisposition, environmental hygiene, and standard of healthcare. Vaccine development could be hampered by the general mildness of the illness and rapid genetic evolution of the virus. Antivirals are not readily available; the role of intravenous immunoglobulin in the treatment of serious complications should be investigated. Monitoring of this disease and its epidemiology in the densely populated Asia Pacific epicentre is important for the detection of emerging epidemics due to enteroviruses. Copyright © 2010 Cambridge University Press.published_or_final_versio

Identifying projected clusters from gene expression profiles

In microarray gene expression data, clusters may hide in subspaces. Traditional clustering algorithms that make use of similarity measurements in the full input space may fail to detect the clusters. In recent years a number of algorithms have been proposed to identify this kind of projected clusters, but many of them rely on some critical parameters whose proper values are hard for users to determine. In this paper a new algorithm that dynamically adjusts its internal thresholds is proposed. It has a low dependency on user parameters while allowing users to input some domain knowledge should they be available. Experimental results show that the algorithm is capable of identifying some interesting projected clusters from real microarray data.published_or_final_versio