Reconfiguration problems arise when we wish to find a stepby-step transformation between two feasible solutions of a problem such that all intermediate results are also feasible. We demonstrate that a host of reconfiguration problems derived from NP-complete problems are PSPACE-complete, while some are also NP-hard to approximate. In contrast, several reconfiguration versions of problems in P are solvable in polynomial time.

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Preeclampsia (PE) is a pregnancy-induced hypertension with proteinuria that typically develops after 20 weeks of gestation. A reduction in uterine blood flow causes placental ischemia and placental release of anti-angiogenic factors such as sFlt-1 followed by PE. Although the reduced uterine perfusion pressure (RUPP) model is widely used in rats, investigating the role of genes on PE using genetically engineered animals has been problematic because it has been difficult to make a useful RUPP model in mice. To establish a RUPP model of PE in mice, we bilaterally ligated ovarian vessels distal to ovarian branches, uterine vessels, or both in ICR-strain mice at 14.5 days post coitum (dpc). Consequently, these mice had elevated BP, increased urinary albumin excretion, severe endotheliosis, and mesangial expansion. They also had an increased incidence of miscarriage and premature delivery. Embryonic weight at 18.5 dpc was significantly lower than that in sham mice. The closer to the ligation site the embryos were, the higher the resorption rate and the lower the embryonic weight. The phenotype was more severe in the order of ligation at the ovarian vessels < uterine vessels < both. Unlike the RUPP models described in the literature, this model did not constrict the abdominal aorta, which allowed BP to be measured with a tail cuff. This novel RUPP model in mice should be useful for investigating the pathogenesis of PE in genetically engineered mice and for evaluating new therapies for PE.

In contrast to the ultrasonic measurement of fetal heart motion, the fetal electrocardiogram (ECG) provides clinically significant information concerning the electrophysiological state of a fetus. In this paper, a novel method for extracting the fetal ECG from abdominal composite signals is proposed. This method consists of the cancellation of the mother's ECG and blind source separation with the reference signal (BSSR). The cancellation of the mother's ECG component was performed by subtracting the linear combination of mutually orthogonal projections of the heart vector. The BSSR is a fixed-point algorithm, the Lagrange function of which includes the higher order cross-correlation between the extracted signal and the reference signal as the cost term rather than a constraint. This realizes the convexity of the Lagrange function in a simple form, which guarantees the convergence of the algorithm. By practical application, the proposed method has been shown to be able to extract the P and T waves in addition to the R wave. The reliability and accuracy of the proposed method was confirmed by comparing the extracted signals with the directly recorded ECG at the second stage of labor. The gestational age-dependency of the physiological parameters of the extracted fetal ECG also coincided well with that of the magnetocardiogram, which proves the clinical applicability of the proposed method.

Abstract. Consider a puzzle consisting of n tokens on an n-vertex graph, where each token has a distinct starting vertex and a distinct target vertex it wants to reach, and the only allowed transformation is to swap the tokens on adjacent vertices. We prove that every such puzzle is solvable in O(n 2 ) token swaps, and thus focus on the problem of minimizing the number of token swaps to reach the target token placement. We give a polynomial-time 2-approximation algorithm for trees, and using this, obtain a polynomial-time 2α-approximation algorithm for graphs whose tree α-spanners can be computed in polynomial time. Finally, we show that the problem can be solved exactly in polynomial time on complete bipartite graphs.