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This paper is aimed at the problem of designing optimized interleavers for parallel concatenated convolutional codes (PCCC) that satisfy several requirements simultaneously: 1) designing interleavers tailored to the constituent codes of the PCCC; 2) improving the distance spectra of the resulting turbo codes which dominate their asymptotic performance; 3) constructing optimized interleavers recursively so that they are implicitly prunable; and 4) completely avoiding short permutation cycles in order to reduce the risk of having strong correlations between the extrinsic information during iterative decoding. To this end, we present two theorems that lead to a modification of a previously developed iterative interleaver growth algorithm (IGA) that can be used to design optimized variable-length interleavers, whereby at every length the optimized permutation implemented by the interleaver is a single-cycle permutation. Two more modifications of the IGA are presented to improve the performance of the optimized interleavers at a reduced complexity. The optimization is achieved via constrained minimization of a cost function closely related to the asymptotic bit-error rate or frame-error rate of the code.