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With the advancement in modulation formats, optical transmission systems are becoming more adaptable and dynamic. Predicting bit errors of higher-order modulation formats is a challenging problem for the optimum design of communication systems. The existing simulation methods have persisted by employing iterative procedures that frequently incur high computing expenses and time consumption. On the other hand, deep learning (DL) algorithms have demonstrated remarkable efficacy as practical computing tools, presenting a viable approach to accelerate modulation simulations. In this paper, an artificial neural network (ANN) based bit error rate (BER) estimation scheme is proposed for the popular modulation forms including 56 Gbps 16-quadrature amplitude modulation (16QAM), 100 Gbps 32QAM, and 120 Gbps 64QAM optical system. Based on constellation diagrams (CDs) acquired with different launch power, laser linewidth, transmission distance, and OSNR, amplitude histograms (AHs) are generated via a manual preprocessing method. The properly trained ANN architecture exhibits a computational speed that surpasses traditional simulation methods by a factor exceeding 347. Moreover, the design considerations including the number of layers, nodes, activation functions, learning rate, optimizers, and evolution epochs are also investigated in detail. This research paves the way for optical transmission systems to use fast DL-based optimization strategies. [ABSTRACT FROM AUTHOR]

We retrospectively evaluated the clinico-laboratory features of 11 children and adolescents with Systemic Lupus Erythematosus between the period of 2001 and 2006. All of them (100.0%) had renal involvement at the first visit in the hospital. Female to male ratio was 10:1. Skin and or mucosal involvement (90.9%), periorbital puffiness and or pedal edema (81.8%), fever (72.7%), hypertension (72.7%), and reticuloendothelial involvement (72.7%), were the commonest presentations. All patients had anemia (8.6 +/- 1.5 gm/dl), raised ESR (46.7 +/- 9.4 mm in first hour), proteinuria, and in disease activity as evident by raised ESR and positive anti-dsDNA antibody at the first visit. The mean duration of disease was 7.6 months and the average duration of disease activity was 63.18 days. Renal biopsy was performed in 8 patients: class IV lupus nephritis in 4 patients (50.0%), class II in 2 patients (25.0%), class III and V in patient (12.5%) each. Nephrotic range proteinuria and hypertension was observed in all patients of class IV and V of lupus nephritis. Class II and III lupus nephritis patients' were normotensive and had non-nephrotic range proteinuria. Three out of 11 patients (27.2%) expired. The commonest primary determinant of mortality was uncontrolled disease activity in 2 patients (66.6%). The third one had infection and developed disseminated intravascular coagulation. The mean duration of disease activity in patients who died (mean 30 days) was statistically lower than the survival group (75.6 days) (p < 0.01). Renal involvement during first visit and mortality could be attributed by late referrals and diagnosis at hospital.