Damage to sperm DNA was proposed to play an important role in embryonic development. Previous studies focused on outcomes after fresh embryo transfer, whereas this study investigated the influence of sperm DNA fragmentation index (DFI) on laboratory and clinical outcomes after frozen embryo transfer (FET). This retrospective study examined 381 couples using cleavage-stage FET. Sperm used for intracytoplasmic sperm injection (ICSI) or in vitro fertilization (IVF) underwent density gradient centrifugation and swim up processing. Sperm DFI had a negative correlation with sperm motility ( r = −0.640, P < 0.01), sperm concentration ( r = −0.289, P < 0.01), and fertilization rate of IVF cycles ( r = −0.247, P < 0.01). Sperm DFI examined before and after density gradient centrifugation/swim up processing was markedly decreased after processing (17.1% vs 2.4%, P < 0.01; 65 randomly picked couples). Sperm progressive motility was significantly reduced in high DFI group compared with low DFI group for both IVF and ICSI (IVF: 46.9% ± 12.4% vs 38.5% ± 12.6%, respectively; ICSI: 37.6% ± 14.1% vs 22.3% ± 17.8%, respectively; both P < 0.01). The fertilization rate was significantly lower in high (≥25%) DFI group compared with low (<25%) DFI group using IVF (73.3% ± 23.9% vs 53.2% ± 33.6%, respectively; P < 0.01) but was equivalent in high and low DFI groups using ICSI. Embryonic development and clinical outcomes after FET were equivalent for low and high DFI groups using ICSI or IVF. In this study, sperm DFI did not provide sufficient information regarding embryo development or clinical outcomes for infertile couples using FET.

An Objective-Flexible Clustering Algorithm (OFCA), which is applicable to multiple design objectives and targets high performance and low energy task mapping and scheduling on homogenous cluster-based NoC, is presented. OFCA employs a lineal clustering to group tasks into clusters, and utilizes an efficient heuristic task mapping process to allocate ready clusters onto the platform. Then a low latency pipeline-based static task scheduling stage is proposed to arrange task sequence in IP cores. Finally a best hardware resource demand for the application could be predicted for reference. OFCA can fully exploit the parallel characteristics within task graphs to minimize inter-cluster communication and limit copying tasks when clustering to reduce extra execution energy. It also controls the use of task-duplicationtechnique (TDT) by setting different parameters for flexible goals to make a compromise between energy and latency. Experiments show that objectives can be adjusted via different parameter ratios performing OFCA and 57% energy savings on average can be achieved compared to CM Algorithm when employed to streaming applications of 18, 36, and 40 tasks.

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