No abstract

No abstract

The present study describes the clinical characteristics of patients with systemic lupus erythematosus (SLE), from the rheumatology service of the two main teaching hospitals in Kuwait. It was a retrospective-cum-prospective clinical study of 108 SLE patients. There were 98 females and 10 males, with a median age of 31.5y. Kuwaitis constituted 69%, while 31% were expatriates. The mean disease duration was 62 months. The main clinical features were: musculoskeletal involvement (87%), photosensitivity (48%), malar rash (43%), discoid lesions (10%), oral ulcers (33%), vasculitic skin lesions (10%), haematological features (53%), constitutional symptoms (51.4%), neuropsychiatric manifestations (23%), renal involvement (37%), serositis (29%), clinical manifestations of antiphospholipid syndrome (21%), cardiac involvement (10%) and pulmonary manifestations (19%). In conclusion, the clinical features of SLE in Kuwait were similar to most major studies from developed countries. Main differences included prominent haematological and mucocutaneous manifestations and possibly a low prevalence of anti-Sm antibodies. Whether these differences are due to the environment or genetic factors, remains to be studied.

No abstract

Brayton heat engine model is developed in MATLAB simulink environment and thermodynamic optimization based on finite time thermodynamic analysis along with multiple criteria is implemented. The proposed work investigates optimal values of various decision variables that simultaneously optimize power output, thermal efficiency and ecological function using evolutionary algorithm based on NSGA-II. Pareto optimal frontier between triple and dual objectives is obtained and best optimal value is selected using Fuzzy, TOPSIS, LINMAP and Shannon's entropy decision making methods. Triple objective evolutionary approach applied to the proposed model gives power output, thermal efficiency, ecological function as (53.89 kW, 0.1611, À142 kW) which are 29.78%, 25.86% and 21.13% lower in comparison with reversible system. Furthermore, the present study reflects the effect of various heat capacitance rates and component efficiencies on triple objectives in graphical custom. Finally, with the aim of error investigation, average and maximum errors of obtained results are computed. Ó 2015 Faculty of Engineering, Ain Shams University. Production and hosting by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

No abstract

The present research investigates the application of artificial intelligence tool for modelling and multi-objective optimization of friction stir welding parameters of dissimilar AA5083-O-AA6063-T6 aluminium alloys. The experiments have been conducted according to a well-designed L 27 orthogonal array. The experimental results obtained from L 27 experiments were used for developing artificial neural network-based mathematical models for tensile strength, microhardness and grain size. A hybrid approach consisting of artificial neural network and genetic algorithm has been used for multiobjective optimization. The developed artificial neural network-based models for tensile strength, microhardness and grain size have been found adequate and reliable with average percentage prediction errors of 0.053714, 0.182092 and 0.006283%, respectively. The confirmation results at optimum parameters showed considerable improvement in the performance of each response.

No abstract