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The main aim of this simulation work is to assess the financial possibility analysis of 10 MWP grid-associated solar photovoltaic (PV) power plants in seven cities i.e. Lucknow, Agra, Meerut, Gorakhpur, Kanpur, Allahabad, and Varanasi of Uttar Pradesh (UP) state of India with the RETScreen Software. The presented research work demonstrates the method of selection of profitable locations for solar PV power plants according to financial viability indicators. It is found that Allahabad city is the most profitable site with values of 16,686 MWh of electricity exported to the grid (EEG), US$20,896.30/year of electricity export revenue (EER), 9.4 years of simple payback period (SPP), 7.7 years of equity payback period (EPP), 19545.9 tCO2/year of GHG emission reduction, US$3492.82/year of the annual life cycle savings (ALCS), 1.5 benefit-cost (B-C) ratio, US$27394.59 of net present value (NPV), 16.5% internal rate of return on equity (IRR-equity), 12.3% modified internal rate of return on equity (MIRR-equity), 5.4% internal rate of return on assets (IRR-assets), and 7% modified internal rate of return on assets (MIRR-assets). The second most profitable site is found in Gorakhpur city and Varanasi city is found the least profitable site. The other two cities, Agra and Kanpur are not found suitable because of the negative values of NPV and ALCS.

Background In India, the usage of modern contraception methods among women is relatively lower in comparison to other developed economies. Even within India, there is a state-wise variation in family planning use that leads to unintended pregnancies. Significantly less evidence is available regarding the determinants of modern contraception use and the level of inequalities associated with this. Therefore, the present study has examined the level of inequalities in modern contraception use among currently married women in India. Methods This study used the fourth round of National Family Health Survey (NFHS-4) conducted in 2015-16. Our analysis has divided the uses of contraception into three modern methods of family planning such as Short-Acting Reversible Contraception (SARC), Long-Acting Reversible Contraception (LARC) and permanent contraception methods. SARC includes pills, injectable, and condoms, while LARC includes intrauterine devices, implants, and permanent contraception methods (i.e., male and female sterilization). We have employed a concentration index to examine the level of socioeconomic inequalities in utilizing modern contraception methods. Results Our results show that utilization of permanent methods of contraception is more among the currently married women in the higher age group (40–49) as compared to the lower age group (25–29). Women aged 25–29 years are 3.41 times (OR: 3.41; 95% CI: 3.30–3.54) more likely to use SARC methods in India. Similarly, women with 15 + years of education and rich are more likely to use the LARC methods. At the regional level, we have found that southern region states are three times more likely to use permanent methods of contraception. Our decomposition results show that women age group (40–49), women having 2–3 children and richer wealth quintiles are more contributed for the inequality in modern contraceptive use among women. Conclusions The use of SARC and LARC methods by women who are marginalized and of lower socioeconomic status is remarkably low. Universal free access to family planning methods among marginalized women and awareness campaigns in the rural areas could be a potential policy prescription to reduce the inequalities of contraceptive use among currently married women in India.

The paper develops the resistivity correlations with standard penetration test (SPT)-N and shear wave velocity (Vs) for the soil in Patna region in India. As part of the investigation, 16 numbers of each SPTs and electrical resistivity tests (ERTs) were conducted in the study area of 500 acres. The field tests were conducted up to a depth of 20 m, uniformly spanning across the study area. During the SPT, soil samples were collected at selected depths for the laboratory investigation. ERTs were performed using the Schlumberger array. Field test results were used to develop the correlation between resistivity and SPT-N. Previously available shear wave velocity data of the area were used for the developing the correlation between resistivity and shear wave velocity. The results revealed the existence of a strong linear correlation between resistivity and SPT-N. A relatively weak linear correlation was observed between resistivity and shear wave velocity. Further, the resistivity correlations were extended to corrected SPT-N and moisture content for the given soil. In overall, the developed correlations are useful for the quick determination of the soil design parameters solely performing electrical resistivity tests, saving the time and effort required by conventional tests.

Using reanalysis data and observations, interannual variations and long-term trends in the Somali Jet (hereafter, the Jet) and Indian Summer Monsoon Rainfall (ISMR) are characterized for drought vs flood, El Nino vs La Nina, and positive vs negative Indian Ocean Dipole (IOD) summer monsoon seasons. In flood years, the Jet is stronger over the upstream sector (i.e., Arabian Sea) and weaker over the downstream (i.e., Bay of Bengal), resulting in additional convergence and enhanced moisture transport over India, whereas the reverse occurs during drought years. The Jet and ISMR characteristics for El Nino (La Nina) years are similar to drought (flood) years, despite only around half of dry (wet) years, being associated with El Nino (La Nina). In +IOD years, the Jet shifts northward and intensifies over central and northern India, bringing more moisture and rainfall to those regions, while the −IOD has an opposite but relatively weak impact on ISMR. Over the last century, the Jet has become weaker over peninsular India, with reductions in rainfall across east India. Future projections under the SSP585 scenario from the CMIP6 multi-model mean suggest that the Jet will progressively shift northward and strengthen over the Arabian Sea, with associated rainfall increases over entire Indian region. The long-term changes in the Jet over the twentieth century are of comparable magnitude to interannual variations; however, the absolute magnitude of projected future changes is smaller than interannual variations observed in the past.

Biological route is one of the viable options to mitigate CO2 from its point sources. The major purpose of the review article is to discuss the possible utilization of microbial cultures for the mitigation of CO2. The article also highlights the scaling-up approach for biological processes especially when microbial cultures are utilized for the same. Few recent studies reported the chemoautotrophic fixation of CO2(g) by catalyzing thermodynamically favored but kinetically inhibited oxidation-reduction or electron donor-acceptor scheme of dissolved inorganic compounds. The previous studies have confirmed the utilization of different bacterial strains for the mitigation of 5%, 10%, and 15% CO2(g) in the absence of light and its simultaneous conversion into valuable products in the lab scale bioreactor. The recent studies also revealed the possibility of prokaryotes to assimilate CO2(g) via carbon concentration mechanism (CCM). The article summarizes the biological route for the natural assimilation of CO2(g) into biomass at the expense of very less energy penalty, via photoautotrophy and chemolithotrophy. The chemolithotrophs utilizes different concentrations of CO2 and thiosulfate salts as an energy source for the non-photosynthetic process. The identification of products using Fourier transform infrared spectroscopy (FTIR) and gas chromatography-mass spectroscopy (GCMS) studies is also entailed. The concept of material balance approach is explained to established the mechanism of CO2(g) mitigation through bacterial route. The obtained results pave the way for further development of CO2 utilization technology at larger scales.

At the High Luminosity Large Hadron Collider (HL-LHC), traditional track reconstruction techniques that are critical for physics analysis will need to be upgraded to scale with track density. Quantum annealing has shown promise in its ability to solve combinatorial optimization problems amidst an ongoing effort to establish evidence of a quantum speedup. As a step towards exploiting such potential speedup, we investigate a track reconstruction approach by adapting the existing geometric Denby-Peterson (Hopfield) network method to the quantum annealing framework for HL-LHC conditions. We develop additional techniques to embed the problem onto existing and near-term quantum annealing hardware. Results using simulated annealing and quantum annealing with the D-Wave 2X system on the TrackML open dataset are presented, demonstrating the successful application of a quantum annealing algorithm to the track reconstruction challenge. We find that combinatorial optimization problems can effectively reconstruct tracks, suggesting possible applications for fast hardware-specific implementations at the HL-LHC while leaving open the possibility of a quantum speedup for tracking.

Flexible and lightweight films of Polyvinylidene fluoride (PVDF) loaded with nanosheets of reduced graphene oxide (RGO) have been prepared via solution casting method. The structure of RGO nanosheets have been examined through X-ray diffraction (XRD), Transmission electron microscopy (TEM) and Raman spectroscopy technique. FTIR studies revealed that the enhancement of β-phase from 53 to 70% has been observed by adding RGO nanosheets in PVDF matrix. The frequency dependent dielectric constant and dielectric loss have been studied. Ultraviolet–visible spectra show a decrease in optical band gap with increases RGO concentration in nanocomposite films. The ferroelectric behavior of RGO loaded PVDF nanocomposite films showed remarkable improvement in remnant polarization values as compared to bare PVDF. The piezo-response of RGO loaded nanocomposite films showed significant enhancement in output voltage from 0.886 to 1.915 V. On exposure to ultraviolet–visible light, RGO loaded nanocomposite PVDF films showed about 13.8% enhancement in piezo- voltage with action of same pressure.

Squamous cell carcinoma of the breast (SCCB) is a rare entity with limited data pertaining to the clinicopathological profile and treatment outcome. These tumors are characterized by rapid progression and have a poor outcome. The optimal therapy for SCCB has not yet been standardized. Most patients with SCCB are treated with the similar conventional chemotherapy regimens used in the ductal variant of breast cancer. This was an observational study of patients diagnosed with SCCB diagnosed from March 2013 to February 2015 at our institute. The medical records were reviewed and patients were contacted by telephone to study the clinicopathological profile and treatment outcome. We identified 5 (0.45%) patients of SCCB out of 1100 breast cancer patients treated in the department of medical oncology during this period. The median age at presentation was 48 years. All tumor specimens showed macroscopic findings of a cystic lesion and central necrosis. After a median follow-up of 32 months, 3 patients (60%) were alive, whereas 2 (40%) patients succumbed to disease progression after recurrence. SCCB is a rare subtype of breast cancer with no standard treatment approach. These are associated with poor prognosis and larger studies are needed to investigate different treatment options.

It is a practice that users or customers intend to share their comments or reviews about any product in different social networking sites. An analyst usually processes to reviews properly to obtain any meaningful information from it. Classification of sentiments associated with reviews is one of these processing steps. The reviews framed are often made in text format. While processing the text reviews, each word of the review is considered as a feature. Thus, selection of right kind of features needs to be carried out to select the best feature from the set of all features. In this paper, the machine learning algorithm, i.e., support vector machine, is used to select the best features from the training data. These features are then given input to artificial neural network method, to process further. Different performance evaluation parameters such as precision, recall, f-measure, accuracy have been considered to evaluate the performance of the proposed approach on two different datasets, i.e., IMDb dataset and polarity dataset.