Background: Breast conserving surgery (BCS) followed by radiotherapy has gained great popularity in the treatment of breast cancer over the past years. However, radiation therapy can lead to many unfavourable aesthetic outcomes including significant volume/skin deficiency, nipple areola complex distortion and skin contraction. We present our experience in using pedicled perforator flaps to tackle the resultant partial breast defects or deformities. Methods: A retrospective data analysis study on Thirty patients with post breast conserving surgery (BCS) partial breast defects who were managed with pedicled per-forator flaps including muscle sparing latissimus dorsi muscle flap (MSLD), thoraco-dorsal artery perforator flap (TDAP) and intercostal artery perforator flap (ICAP) in the period between December 2008 and December 2018.Results: Defects were in all quadrants apart from the upper inner quadrant. The reconstructive techniques included TDAP flap 6/30 (20%), MSLD flap 20/30 (66.7%), AICAP flap 4/30 (13.3%). Age ranges 22-35 (mean 29). All flaps showed complete survival, one nipple areola complex superficial epidermolysis was experienced, and one patient presented with fat necrosis. No resultant donor site morbidity apart from scar revision for excess skin at the axillary fold in one patient. The overall satisfaction reached 94% with only 8 patients who required lipofilling to maximize the cosmetic outcome. Conclusions:The availability of a range of reliable techniques including thoracodorsal/intercostal artery perforator flap (TAP/ICAP) and muscle sparing lattissimus dorsi flap (MSLD) allow optimum results to be achieved in the treatment of partial breast defects following breast conserving surgery.

In this work, we address the problem of spelling correction in the Arabic language utilizing the new corpus provided by QALB (Qatar Arabic Language Bank) project which is an annotated corpus of sentences with errors and their corrections. The corpus contains edit, add before, split, merge, add after, move and other error types. We are concerned with the first four error types as they contribute more than 90% of the spelling errors in the corpus. The proposed system has many models to address each error type on its own and then integrating all the models to provide an efficient and robust system that achieves an overall recall of 0.59, precision of 0.58 and F1 score of 0.58 including all the error types on the development set. Our system participated in the QALB 2014 shared task "Automatic Arabic Error Correction" and achieved an F1 score of 0.6, earning the sixth place out of nine participants.

No abstract

Cascaded machine translation systems are essential for Deaf people. Speech recognizers and sign language translators when combined together constitute helpful automatic machine translators. This paper introduces an automatic translator from Arabic spoken language into Arabic sign language. This system aims to integrate Deaf students into classrooms of hearing ones. The proposed system consists of three cascaded modules: a modified Arabic speech recognizer that works using adaptation, an Arabic machine translator, and a developed signing avatar animator. The system is evaluated on real case studies and shows good performance.

No abstract