The heart rate complexity is reduced with a significant decreasing trend as assessed by R-R interval entropy prior to the onset of AF. There is a need for well-defined studies with larger patient groups in order to assess the entropy changes further and to look for possible changes, which might predict impending AF episodes.

OBJECTIVE-Intraventricular hemorrhage remains an important problem among very low birth weight infants and may result in long-term neurodevelopmental disabilities. Neonatologists have been unable to accurately predict impending intraventricular hemorrhage. Because alterations in the autonomic nervous system's control of heart rhythm have been associated with intraventricular hemorrhage after its development, we sought to determine if early subtle alterations of heart rhythm could be predictive of impending intraventricular hemorrhage in very low birth weight infants.METHODS-This case-control study included 10 newborn very low birth weight infants with intraventricular hemorrhage (5 grade IV, 4 grade III, and 1 grade II) and 14 control infants without intraventricular hemorrhage. Heart rhythm data from the first day of life before the development of intraventricular hemorrhage were evaluated. Detrended fluctuation analysis, a nonlinear fractal heart rate variability method, was used to assess the fractal dynamics of the heart rhythm. Fractal scaling exponents were calculated by using this analysis.RESULTS-Twenty-four infants (mean ± SD, birth weight: 845 ± 213g: gestational age: 26.1 ± 1.9 weeks) participated in the study. The short-term scaling exponent was significantly larger in infants who later developed intraventricular hemorrhage compared with those who did not (0.60 ± 0.1 vs 0.45 ± 0.1). A value of 0.52 resulted in 70% sensitivity and positive predictive value and 79% specificity and negative predictive value. The short-term scaling exponent was the only significant predictor of intraventricular hemorrhage.CONCLUSIONS-Fractal dynamics of the heart rhythm is significantly altered in very low birth weight infants before developing intraventricular hemorrhage and may be predictive of impending intraventricular hemorrhage. 8,9 Given this important public health problem, it would be quite valuable to identify VLBW infants who are at highest risk for developing IVH, before they actually develop it, so that they may benefit from prevention and intervention strategies. Unfortunately, accurate prediction methodologies of impending IVH have not been developed.Altered autonomic function has been observed by heart rate variability (HRV) analysis in premature infants after IVH. 10-12 HRV refers to the beat-to-beat (R-R interval from the electrocardiogram) fluctuation of heart rate and reflects the balance between parasympathetic and sympathetic impulses to the heart that is under central nervous system control. Researchers have used HRV analysis as a tool to estimate autonomic neural control of the heart and for predicting impending arrhythmia 13 and long-term outcome of VLBW infants. 11,14 The objective of this study was to determine if impending IVH in VLBW infants may be predicted by altered autonomic function. We hypothesized that autonomic dysfunction precedes the development of IVH in VLBW infants. We used a nonlinear method, called detrended fluctuation analysis (DFA), 11,15 to examine the HRV characte...

In this age of growing importance for interdisciplinary studies, the field of computing, and its indispensable component, programming, have become increasingly important not only for STEM areas but also for many other fields. Computational chemistry, bio-informatics, computational linguistics, computational toxicology, etc. are just a few examples of the crossover disciplines that benefit significantly from the developments in the computing and Information Technology (IT). Instructors are facing more challenges today than ever in trying to come up with new, fresh and appealing methodologies to attract and retain students in delivering computing and IT related topics to a much broader audience. Computing courses and topics both for majors and non-majors need new approaches that motivate students to feel comfortable with the life-long learning of computing concepts and tools. The goal of this paper is to summarize our teaching experience in and the great potential of App Inventor for Android (AIA) in broadening the appeal and diffusion of fundamental computing and programming concepts. With a pedagogical foundation stemming from constructionist learning and contextualized computing education, we present our motivation and the details of courses that can greatly benefit from AIA.

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Computing products of large numbers has always been a challenging task in the field of computing. One such example would be the factorial function. Several methods have been implemented to compute this function including naive product, recursive product, Boiten split, and prime factorization, and linear difference. The method presented here is unique in the sense that it exploits finite order differences to reduce the number of multiplications necessary to compute the factorial. The differences generated are regrouped into a new sequence of numbers, which have at most half as many elements of the original sequence. When the terms of this new sequence are multiplied together, the factorial value is obtained. The cardinality of the new sequence can further be reduced by partitioning. The sequence is computed by using several difference tables that assist in establishing the pattern that determines the sequence. An analysis of the algorithm is presented. The analysis shows that the execution time can be reduced significantly by the algorithm presented.