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Breast cancer-related lymphedema (BCRL) is a major long-term complication for post-surgery breast cancer survivors. Although several risk factors have been identified, lifestyle characteristics have been neglected in previous studies. The aim of this study was to develop and validate a nomogram for estimating this population’s risk of developing lymphedema, taking into consideration their demographic, clinical, and personal lifestyle behaviors. In a cross-sectional study, we collected data from 775 post-operative breast cancer survivors who had attended a follow-up session in the recent 10 years (primary cohort). Lymphedema was assessed using the Norman telephone questionnaire, self-reported by patients. Multiple logistic regression was used to identify risk factors for lymphedema, including demographic, clinical, and lifestyle-related factors. A nomogram was constructed based on those factors and was validated using a separate group of 314 breast cancer patients (validation cohort). The factors independently associated with lymphedema were higher body mass index (BMI), modified radical mastectomy (MRM), postsurgical infection, chemotherapy, radiotherapy, exercise of the affected arm, and the active participation in physical activity (P

Efficient reconciliation is a crucial step in continuous variable quantum key distribution. The progressive-edge-growth (PEG) algorithm is an efficient method to construct relatively short block length low-density parity-check (LDPC) codes. The qua-sicyclic construction method can extend short block length codes and further eliminate the shortest cycle. In this paper, by combining the PEG algorithm and qua-si-cyclic construction method, we design long block length irregular LDPC codes with high error-correcting capacity. Based on these LDPC codes, we achieve high-efficiency Gaussian key reconciliation with slice recon-ciliation based on multilevel coding/multistage decoding with an efficiency of 93.7%.