The combination of low-dose spironolactone with metformin seems superior to either drug alone in terms of clinical benefits and compliance in women with PCOS.

The state of Jammu and Kashmir in North India experienced one of the worst floods in the past 60 years, during the first week of September 2014. In the present study, multi-temporal synthetic aperture radar (SAR) satellite images acquired from Indian Remote Sensing (IRS) satellite RISAT-1 and Canadian satellite Radarsat-2 during the peak flood period (08thÀ23rd September 2014) are used for extraction of flood disaster footprints, mapping spatial and temporal dynamics of flood inundation and assessing the disaster impact. With the aid of pre-and post-flood satellite images, coupled with hydro-meteorological data, the unprecedented flood situation is analyzed. It is estimated that about 557 km 2 of the Kashmir Valley's geographical area was inundated. Bandipora, Pulwama, Srinagar, Baramulla and Budgam were the worst flood affected districts, having more than 50 km 2 of their area affected by flood waters. Of the total inundated area, about 80% of the area under agricultural activity was submerged, followed by built-up areas constituting about 12% of geographical area. About 22 lakh people in 287 villages were affected by floods. The flood waters persisted in the northern and central part of the valley for more than two weeks.

-In present work, we have implemented the pseudo-code (PN-code) generator using quantum-dot cellular (QCA) technology. Simulation results are obtained from QCA designer software. The PN-code generation is of paramount importance for any secure communication system. The complex code generated is used to scramble incoming plain text. At the receiving end, the same code is generated and successfully used to decrypt the transmitted data. The algorithm for generating noise signal is quite simple. The simplicity of the circuit along with the complexity of the code generated makes the circuit attractive for secure message communication.

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Globally, the COVID-19 pandemic has become a threat to humans and to the socioeconomic systems they have developed since the industrial revolution. Hence, governments and stakeholders call for strategies to help restore normalcy while dealing with this pandemic effectively. Since till now, the disease is yet to have a cure; therefore, only risk-based decision making can help governments achieve a sustainable solution in the long term. To help the decisionmakers explore viable actions, we propose a risk-based assessment framework for analyzing COVID-19 risk to areas, using integrated hazard and vulnerability components associated with this pandemic for effective risk mitigation. The study is carried on a region administrated by Jaipur municipal corporation (JMC), India. Based on the current understanding of this disease, we hypothesized different COVID-19 risk indices (C19Ri) of the wards of JMC such as proximity to hotspots, total population, population density, availability of clean water, and associated land use/land cover, are related with COVID-19 contagion and calculated them in a GIS-based multicriteria risk reduction method. The results showed disparateness in COVID-19 risk areas with a higher risk in north-eastern and south-eastern zone wards within the boundary of JMC. We proposed prioritizing wards under higher risk zones for intelligent decision making regarding COVID-19 risk reduction through appropriate management of resources-related policy consequences. This study aims to serve as a baseline study to be replicated in other parts of the country or world to eradicate the threat of COVID-19 effectively.

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We investigated intraspecific variation of the Snowtrout, Schizothorax richardsonii on the basis of morphometric characters. Altogether, 217 specimens were collected from four rivers in the Western and Central Indian Himalaya. A truss network was constructed by interconnecting 14 landmarks to yield 31 distance variables that were extracted from digital images of specimens using tpsDig2 and PAST software. Transformed truss measurements were subjected to univariate analysis of variance, factor analysis and discriminant analysis. All variables exhibited significant differences between the populations. Altogether 86.6% of the specimens were classified into their original populations (82.9 % under a ‘leave-one-out’ procedure). With factor analysis measurements of the head region, the middle portion and the caudal region had high loadings on the on first and second axis. The results indicated that S. richardsonii has significant phenotypic heterogeneity between the Western and Central Indian Himalayas. We hypothesize that the marked interspecific variation in S. richardsonii is the result of local ecological conditions.