Evaluation of post partum intrauterine contraceptive device versus interval intrauterine contraceptive device insertion

Background: Family planning is important not only for population stabilization, but it has been increasingly recognized as central tool to improve maternal and neonatal health. Aim of current study was to compare interval and post partum intrauterine contraceptive device (IUCD) insertion in terms of effectiveness and safety.Methods: This was a prospective observational cohort study, done in the department of Obstetrics and Gynecology, GMERS Medical College, Sola, Ahmedabad, from August 2015 to April 2017 was taken for evaluation. 80 women in each group who were inserted IUCD after delivery and in the interval period were studied. Outcome was measured by expulsion rate, continuation rate, and incidence of dysfunctional uterine bleeding (DUB), Pelvic inflammatory disease (PID), failure rate and effect on puerperium.Results: Expulsion rate in PPIUCD group was 8.75% while in interval IUCD group it was 1.25%. Continuation rate following Postpartum intrauterine contraceptive device (PPIUCD) and interval IUCD insertion was 86.25% and 95% respectively. Incidence of bleeding per vaginum (menorrhagia) was 7.5% in PPIUCD group while 8.75% in interval IUCD group. There was one case 1.25% of PID in interval IUCD group while no case in PPIUCD was noted. Failure rate was nil in both the group. There was no effect on puerperium following PPIUCD insertion group during present study.Conclusions: PPIUCD is an effective and safe spacing method of contraception as compared to interval IUCD insertion. There is no statistically significant change in incidence of expulsion rate, continuation rate and other complications in both the group

Study the accuracy of salivary ferning test as a predictor of ovulation

Background: Women probably spent much of their adult life avoiding getting pregnant but when they are actively trying for a baby, it may be taking a little longer time than they hoped. So it is important for the women to know when they are ovulating. Recently, a small hand held microscope (KNOWHEN ovulation microscope) has been developed for the purpose of self-observing ferning patterns in saliva during female fertile period. The purpose of our study is to evaluate the accuracy of salivary ferning test by KNOWHEN ovulation microscope to predict the ovulation and to detect sensitivity and specificity of salivary ferning test and to correlate the salivary ferning with cervical mucus and Trans vaginal sonographic findings (TVS).Methods: This was a prospective observational type of study conducted on all healthy married women volunteers age between 21–40 years attending gynec OPD in sola civil hospital, Ahmedabad, with regular menstrual cycle From April 2016 to September 2016.Results: Salivary ferning test by KNOWHEN ovulation microscope is accurate method of detecting ovulation. Its accuracy was 86.5%.Conclusions: Salivary ferning test is a reliable test to detect fertile period of menstrual cycle. Hence can be use for monitoring ovulation instead of ultrasonography where facility of ultrasonography will not available. Detection of salivary ferning by KNOWHEN microscope has same accuracy as laboratory microscope. KNOWHEN microscope can be use by patient herself to detect fertile period

Rate Forecaster based Energy Aware Band Assignment in Multiband Networks

The high frequency communication bands (mmWave and sub-THz) promise tremendous data rates, however, they also have very high power consumption which is particularly significant for battery-power-limited user-equipment (UE). In this context, we design an energy aware band assignment system which reduces the power consumption while also achieving a target sum rate of M in T time-slots. We do this by using 1) Rate forecaster(s); 2) Channel forecaster(s) which forecasts T direct multistep ahead using a stacked (long short term memory) LSTM architecture. We propose an iterative rate updating algorithm which updates the target rate based on current rate and future predicted rates in a frame. The proposed approach is validated on the publicly available `DeepMIMO' dataset. Research findings shows that the rate forecaster based approach performs better than the channel forecaster. Furthermore, LSTM based predictions outperforms well celebrated Transformer predictions in terms of NRMSE and NMAE. Research findings reveals that the power consumption with this approach is ~ 300 mW lower compared to a greedy band assignment at a 1.5Gb/s target rate

Comparative evaluation of antihypertensive drugs in the management of pregnancy-induced hypertension

Background: Pregnancy-induced hypertension is associated with various adverse fetal and maternal outcomes. The use of anti-hypertensive drugs in pregnancy is controversial. We conducted a prospective study to evaluate the comparative effectiveness and safety of nifedipine, methyldopa and labetalol monotherapy in patients with pregnancy-induced hypertension.Methods: A total of 60 pregnant women with blood pressure of 140/90 mm Hg or more with ≥1+ proteinuria between 20 and 38 weeks of gestation were randomly allocated to receive nifedipine (n=20), methyldopa (n=20) or labetalol (n=20). Blood pressure was measured at 0, 6, 24, 48 and 72 h of initiation of antihypertensive drugs. Patients were also followed up for development of adverse drug effects during this period.Results: Antihypertensive treatment with methyldopa was associated with reduction in systolic blood pressure (SBP) by 50 mmHg and diastolic blood pressure (DBP) by 30 mmHg at 72 h. For the same period treatment with nifedipine was associated with reduction in SBP by 54 mmHg and DBP by 30 mmHg. Treatment with labetalol was associated with reduction in SBP by 70 mmHg and DBP by 36 mmHg at 72 h.Conclusions: Labetalol was more effective than methyldopa and nifedipine in controlling blood pressure in patients with pregnancy-induced hypertension while methyldopa and nifedipine are equally effective in controlling blood pressure

Spectrum Sensing Based on Censored Observations in Time-Varying Channels using AR-1 Model

Non-parametric sensing algorithms are preferred in cognitive radio. In this paper, spectrum sensing method based on censored observations is proposed. We evaluate the performance of Censored Anderson-Darling (CAD) sensing method in time-varying and flat-fading channel using Monte Carlo simulations. We have shown the performance of the CAD sensing in terms of receiver operating characteristic (ROC). The considered channel is modeled by Gaussian variables and characterized by a first ordered autoregressive process ($AR1$). It is shown that the proposed method outperforms prevailing techniques such as the Energy detection (ED) sensing and  Order-statistic (OS) based sensing in time-varying channel at lower signal to noise ratio