An approach to melodic segmentation and classification based on filtering with the Haar wavelet

We present a novel method of classification and segmentation of melodies in symbolic representation. The method is based on filtering pitch as a signal over time with the Haar-wavelet, and we evaluate it on two tasks. The filtered signal corresponds to a single-scale signal ws from the continuous Haar wavelet transform. The melodies are first segmented using local maxima or zero-crossings of ws. The segments of ws are then classified using the k–nearest neighbour algorithm with Euclidian and city-block distances. The method proves more effective than using unfiltered pitch signals and Gestalt-based segmentation when used to recognize the parent works of segments from Bach’s Two-Part Inventions (BWV 772–786). When used to classify 360 Dutch folk tunes into 26 tune families, the performance of the method is comparable to the use of pitch signals, but not as good as that of string-matching methods based on multiple features

Self-Similarity in General Relativity \endtitle

The different kinds of self-similarity in general relativity are discussed, with special emphasis on similarity of the ``first'' kind, corresponding to spacetimes admitting a homothetic vector. We then survey the various classes of self-similar solutions to Einstein's field equations and the different mathematical approaches used in studying them. We focus mainly on spatially homogenous and spherically symmetric self-similar solutions, emphasizing their possible roles as asymptotic states for more general models. Perfect fluid spherically symmetric similarity solutions have recently been completely classified, and we discuss various astrophysical and cosmological applications of such solutions. Finally we consider more general types of self-similar models.Comment: TeX document, 53 page

Cesarean sections in Brazil: will they ever stop increasing?

OBJECTIVE: To describe trends, geographic distribution, and risk factors for cesarean deliveries in Brazil in 2000-2011, and to determine if efforts to curtail rates have had a measurable impact. METHODS: This was an observational study using nationwide information from the Department of Informatics of the Unified Health System (DATASUS). Individual level analyses were based on data regarding maternal education, age, parity, and skin color. Ecological analyses at the level of 431 health districts investigated the relationships with health facility density and poverty level. RESULTS: Cesarean rates increased markedly, from 37.9% in 2000 to 53.9% in 2011. Preliminary results from 2012 showed a rate of 55.8%, with the richest geographic areas showing the highest rates. Rates at the municipal level varied from 9%-96%. Cesareans were more common in women with higher education, white skin color, older age, and in primi- paras. In the ecological analyses, the number of health facilities per 1 000 population was strongly and positively correlated with cesarean rates, with an increase of 16.1 percentage points (95% Confidence Interval [95%CI] = 4.3-17.8) for each facility. An increase of 1 percentage point in the poverty rate was associated with a decline of 0.5 percentage point in cesarean rates (95%CI = 0.5-0.6). CONCLUSIONS: The strong associations with maternal education and health facility density suggest that the vast majority of cesareans are not medically indicated. A number of policies and programs have been launched to counteract this trend, but have had virtually no impact