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भारत की उपास्थिमीन मात्स्यकी

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Homeopathic Flora of Bilaspur District of Himachal Pradesh, India: A Preliminary Survey

The present study was made in nine villages of Bilaspur district of Himachal Pradesh, a north Indian state known for its vast herbal flora. About 23 plant species belonging to 18 families used in the homeopathic system of medicine are highlighted in the present study along with their taxonomic description including botanical name, medicine name, plant part used and ailment against which the medicines are used. The collected plant specimens were identified, taxonomically defined and submitted to the herbarium for future records

Significance of handcrafted features in human activity recognition with attention-based RNN models

Sensors incorporated in devices are a source of temporal data that can be interpreted to learn the context of a user. The smartphone accelerometer sensor generates data streams that form distinct patterns in response to user activities. The human context can be predicted using deep learning models built from raw sensor data or features retrieved from raw data. This study analyzes data streams from the UCI-HAR public dataset for activity recognition to determine 31 handcrafted features in the temporal and frequency domain. Various stacked and combination RNN models, trained with attention mechanisms, are designed to work with computed features. Attention gave the models a good fit. When trained with all features, the two-stacked GRU model performed best with 99% accuracy. Selecting the most promising features helps reduce training time without compromising accuracy. The ranking supplied by the permutation feature importance measure and Shapley values are utilized to identify the best features from the highly correlated features. Models trained using optimal features, as determined by the importance measures, had a 96% accuracy rate. Misclassification in attention-based classifiers occurs in the prediction of dynamic activities, such as walking upstairs and walking downstairs, and in sedentary activities, such as sitting and standing, due to the similar range of each activity’s axis values. Our research emphasizes the design of streamlined neural network architectures, characterized by fewer layers and a reduced number of neurons when compared to existing models in the field, to design lightweight models to be implemented in resource-constraint gadgets

Efficacy of Mefipristone for induction of labour in late term pregnancy

Background: Late-term pregnancy defined as one that has reached between 41 0/7 weeks and 41 6/7 weeks of gestation is associated with an increased maternal morbidity as well as an increased risk of fetal and neonatal mortality and morbidity. Mifepristone, an anti-glucocorticoid and antiprogesterone, though not an oxytocic increases uterine activity and causes cervical effacement and dilatation and improves the Bishop score without over/hyper stimulation of uterus. Increased maternal and fetal mortality from late term pregnancy could be prevented by induction of labour. The objective of this study was to know the efficacy of single dose of oral mifepristone in induction of labour in late term pregnancy and to assess the induction delivery interval in the study population.Methods: This was a prospective interventional study conducted in Department of Obstetrics and Gynaecology at BGS Global Institute of Medical Sciences, Bengaluru. 100 Women with late term pregnancy who fulfilled the inclusion and exclusion criteria were considered for the study after an informed written consent.Results: 73.5% (n=36) of multigravida and 80.4% (n=41) of prim gravida showed improvement in the Bishop score post induction with mifepristone and majority (89.79 % primigravida and 84.31% multigravida) of the study population had vaginal delivery. Multigravida (73.5%) had less induction delivery interval (less than 48hours) compared to primigravida (19.6%).Conclusions: Mifepristone, a progesterone antagonist causes a significant improvement in the Bishop’s score and is associated with an increased rate of vaginal deliveries

Art outcome in combined group of women with premature ovarian failure and menopausal women

Background: It is to present an overview of the study of the ART cycles in combined group of women with premature ovarian failure (POF) and menopausal women in 1 year period. Purpose of the study was to know the pregnancy outcome in this combined group. Since majority of the patients who entered our tertiary hospital had already received various treatment methods such as gonadotropins, long protocols and ultra-short protocols in previous hospitals with no positive result, we had to take them directly to the ovum donation (OD) or embryo donation (ED).Methods: A simple study was performed from 1st January, 2015 to 31st December, 2015. Women with POF and menopause were enrolled and complete follow up of them was done from their first visit till stable pregnancy of 14 weeks was achieved. While doing this, we considered various parameters which can affect the ART outcome, for e.g. endometrial evaluation, hysteroscopy findings, proliferative phase preparation, leuteal support, semen analysis etc. The study outcome results included pregnancy rate and miscarriage rate.Results: In spite of good efforts, ultimately, stable pregnancy rate (beyond 14 weeks gestation) of these women was only 35% that was almost one third of the total study population that too with the help of OD and ED. Pregnancy rate was actually 42%, out of which 7% had miscarriage. With all the cost, efforts and time involved, 65% (2/3rd) of women could not achieve successful pregnancy.Conclusions: Since the possibility of pregnancy gradually declines after the age of 30 and a steep fall in fertility after the age of 35, women should be advised not to postpone marriages and should be encouraged to have children earlier

Modified digital space vector pulse width modulation realization on low-cost FPGA platform with optimization for 3-phase voltage source inverter

The realization of power electronic applications on hardware is a challenging task. The digital control circuit strategies are used to overcome the analog control strategies by providing great flexibility with simple equipment and higher switching frequencies. In this manuscript, an area optimized, modified digital space vector (DSV) pulse width modulation is designed and realized on low-cost FPGA. The modified digital space vector pulse width modulation (DSVPWM) uses a phase-locked loop (PLL) to generate clocks using the digital clock manager (DCM). These DCM clocks are used in the DSVPWM module to synchronize the other sub-modules. The voltage generation unit generates the three-phase (3-Ф) voltages and is used in the alpha-beta generation and sector determination unit. The reference active vectors are made by the reference generation unit and used in switching time calculation. The PWM pulses are generated using switching time generation, and lastly, the dead time occurrence unit generates the final SVPWM gate pulses. The modified DSVPWM is synthesized and implemented on Spartan-3E FPGA. The modified DSVPWM utilizes 17% slices, works at 102.45 MHz, and consumes 0.070 W total power. The simulation results and the resource utilization of modified DSVPWM are represented in detail. The modified DSVPWM is compared with existing PWM approaches on different Spartan-series FPGAs with better chip area improvemen

An introspection of quality of novel drug approvals by United States Food and Drug Administration

Background: United States Food and Drug Administration (FDA) is the fastest drug review agency in the world. FDA is responsible for protection of the public health by assuring that foods are safe, wholesome, sanitary and properly labelled. Approved Novel drugs are often innovative products that serve unmet medical needs or otherwise help to advance patient care.Methods: FDA novel drug approvals were analysed from calendar year (CY) 2012 to 2016 on the basis of three criteria i.e., impact, access and predictability. Impact measured on the basis of: percentage of novel drug approvals (a) first in class (b) for rare diseases. Access measured on the basis of: percentage of novel drug approvals (a) first cycle approval (b) approval in the U.S. before other countries and (c) percentage of priority reviews. Predictability measured by: the percentage of novel drug approvals that met the PDUFA goal dates for the application review.Results: Total number of novel drugs approved from CY 2012 to 2016 was 176 (average 35 novel drugs/ year). Impact of novel drug approvals: 40% were first in class and 39% were for rare diseases. Access of novel drug approvals: 84% were first cycle approval, 60% were approval in US before other countries, 51% priority reviews among novel drug approvals. Predictability of novel drug approvals: 97% approvals able to meet PDUFA goal dates for application review.Conclusions: Novel drug approvals during CY 2012-2016 had a high quality which is very much evident by their high impact, good access and high predictability