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The American Institute of Physics, Bulletin of Physics News.



The American Institute of Physics, Bulletin of Physics News Number 575 January 30, 2002 by Phillip F. Schewe and Ben Stein

SPIRAL WAVES BREAK HEARTS. Sudden cardiac death kills more than 300,000 Americans each year. Ordinarily, electrical impulses cause the heart's muscle fibers to contract. In a healthy heart, these impulses pass through cardiac tissue as a smooth wave of electricity. However, sometimes these waves get stuck and form troublesome, whirlpool-like spirals of electrical activity in the heart. Investigating these spiral waves, Canadian scientists (Leon Glass, McGill University, 514-398-4338, glass@cnd.mcgill.ca) have studied chick-embryo cardiac cells grown as a sheet of tissue. Such arrangements of cells often exhibit spiral waves in their first two days. When the cardiac tissue was subjected to a drug that impairs communication between the cells, rotating spiral waves broke up into multiple rotating spirals (movies at www.aip.org/mgr/png). The spiral wave breakup is believed to be similar to the processes that lead to ventricular fibrillation, a potentially fatal cardiac rhythm that often occurs when communication between cells is impaired. Reduced intercellular communication may also be caused by a heart attack or by other cardiac diseases. To explain the experimental findings, the researchers devised a simplified computer model consisting of cells irregularly distributed in space. As their model shows, the spread of electrical activity in cardiac tissue is similar to the spread of a fire in a forest: Cells become active if enough neighboring cells are active (however, active cells are "refractory," or electrically inactive, for some time afterwards). When the neighboring cells interact strongly, electrical waves pass through the tissue at a high velocity; when weak, wave propagation is completely blocked. At intermediate levels of interaction, electrical waves break up into multiple spiral waves. These observations should help to explain the appearance of multiple spiral waves in a host of other physical and biological systems, including corrosion on metal surfaces, aggregation of slime molds, and "Belousov-Zhabotinsky" chemical reactions that exhibit oscillating spatial patterns. (Bub, Shrier, and Glass, Phys. Rev. Lett., 4 February 2002)

SQUEEZING INFORMATION FROM ZIPPING PROGRAMS. Data compression programs, such as the file zipping applications found on many personal computers, provide an unusual means to analyze information. Researchers at the La Sapienza University in Rome (Emanuele Caglioti, caglioti@mat.uniromal.it, 39-06-4991-4972) have demonstrated how compression routines can accurately identify the language, and even the author, of a document without requiring anyone to bother reading the composition. The key to the analysis is the measurement of the compression efficiency that a program achieves when an unknown document is appended to various reference documents. Zipping programs typically compress data by searching for repeated strings of information in a file. The programs record a single copy of the information and note the locations of subsequent instances of the string. Unzipping a file consists of replacing various bits of information at the locations recorded by the zipped file. Such file compression routines work better on long files because programs are, in effect, learning about the type of information they are encoding as they move through the data. Add a page of Italian text to an Italian document, and a zipping program achieves good efficiency because it finds words and phrases that appear earlier in the file. If, however, Italian text is appended to an English document, the program is forced to learn a new language on the fly, and compression efficiency is reduced. The researchers found that file compression analysis worked well in identifying the language of files as short as twenty characters in length, and could correctly sort books by author more than 93% of the time. Because subject matter often dictates vocabulary, a program based on the analysis could automatically classify documents by semantic content, leading to sophisticated search engines. The technique also provides a rigorous method for various linguistic applications, such as the study of the relationships between different languages. Although they are currently focusing on text files, the researchers note that their analysis should work equally well for any information string, whether it records DNA sequences, geological processes, medical data, or stock market fluctuations. (D. Benedetto, E. Caglioti, and V. Loreto, Physical Review Letters, 28 January 2002)

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