aman aggarwal

Aim To evaluate pregnancy outcome in women with systemic lupus erythematosus (SLE). Methods A total of 71 pregnancies in 35 women with SLE were evaluated for maternal and perinatal outcomes in a tertiary centre of Northern India. Thirty-five pregnancies were evaluated prospectively while details of previous 36 pregnancies in the same women were studied retrospectively. Results The Mean age of pregnant women with SLE was 26.89 ± 2.7 years and 14.57% were nulliparous. The presenting event was arthritis in 60% of the patients; others presented with febrile illness, renal manifestation and cutaneous manifestation. One woman was lupus anticoagulant positive. All women conceived while on disease quiescence period and were continued on the same pre-pregnancy dose of pharmacological agents. Hypertensive disorders of pregnancy were seen in 28.5% while chronic hypertension was seen in 5.6%. The incidence of abortion, preterm deliveries and perinatal loss was 33.8, 29.57 and 12.67%, respectively. Vaginal delivery rate was 47.88 and 18.3% underwent caesarean section. There was no case of neonatal lupus and none had disease flare-up in the postpartum period. Conclusion A better pregnancy outcome can be expected if clinical remission is achieved and disease activity is adequately controlled prior to pregnancy.

This paper presents a methodology to evaluate the performance of carbide compacting die using graph theoretic approach (GTA). Factors affecting the die performance and their interactions are analysed by developing a mathematical model using digraph and matrix method. Permanent function or die performance index is obtained from the matrix model developed from the digraphs. This permanent function/index value compares and ranks the factors affecting the die performance. It helps in selection of optimum process parameters during die manufacturing. Hence, process output errors such as dimensional inaccuracy, large surface craters, deep recast layers, etc. will be minimised during die manufacturing which helps to achieve better die performance. In present illustration, factors affecting the performance of carbide compacting die are grouped into five main factors namely work material, machine tool, tool electrode, geometry of die and machining operation. GTA methodology reveals that the machine tool has highest index value. Therefore, it is the most influencing factor affecting the die performance. In case of die material low cobalt concentration and small grain size yields good surface finish, while in machine tool low discharge energy (i.e. low values of peak current, pulse-on time, servo voltage and high value of pulse-off time) and high dielectric flow rate yields good surface finish and, hence, favours the good die performance. In case of die geometry, large work piece thickness and small taper angles results in lesser geometrical deviations and hence helps to achieve better die performance.

Machinability aspect is of considerable importance for efficient process planning in manufacturing. Machinability of an engineering material may be evaluated in terms of the process output variables like material removal rate, processed surface finish, cutting forces, tool life, specific power consumption, etc. In this paper, graph theoretic approach (GTA) is proposed to evaluate the machinability of tungsten carbide composite. Material removal rate is considered as a machinability attribute of tungsten carbide to evaluate the effect of several factors and their subfactors. Factors affecting the machinability and their interactions are analyzed by developing a mathematical model using digraph and matrix method. Permanent function or machinability index is obtained from the matrix model developed from the digraphs. This index value helps in quantifying the influence of considered factors on machinability. In the present illustration, factors affecting machinability of tungsten carbide are grouped into five broad factors namely work material, machine tool, tool electrode, cutting conditions, and geometry to be machined. GTA methodology reveals that the machine tool has highest index value. Therefore, it is the most influencing factor affecting machinability.