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Purpose: To determine optimal pinhole size (OPS) and establish a relationship with visual acuity (VA) and RMS (root mean square) values in cases with higher-order aberrations (HOAs) undergoing pinhole pupilloplasty (PPP). Setting: Private practice, India. Design: Prospective, interventional study. Methods: RMS value for 6-mm--diameter optical zone was determined by Scheimpflug imaging (Pentacam). Patients with RMS value >0.3 mm were included. Preoperatively, a hand-held pinhole gauge with varied apertures determined the OPS, and single-pass four-throw technique was used to perform pupilloplasty with Purkinje-1 reflex as a marker for centration. VA with OPS, correlation of RMS values with OPS and pupil size, and Strehl ratio were the main outcome measures. Results: 29 eyes with HOAs were analyzed; all patients chose 1.0 or 1.5 mm as OPS. The mean preoperative and postoperative pupil size was 3.25 ± 0.81 mm and 1.8 ± 0.54 mm (P = .000), respectively. Postoperative mean pupil size when compared with OPS denoted that 14 eyes had a difference of <0.1 mm, 8 eyes ranged from 0.2 to 0.45 mm, and 7 eyes had ≥0.6 mm (range from 0.6 to 1.8 mm) difference from OPS. Eyes with higher RMS values needed smaller pupil gauge to achieve better VA. Preoperatively, vision with OPS correlated well with preoperative 6-mm RMS HOAs (r = 0.728; P = .00). Postoperative UDVA correlated well with VAmeasured with OPS (r = 0.847; P = .00). The preoperative and postoperative mean Strehl ratio was 0.109 ± 0.07 and 0.195 ± 0.11 (P = .001), respectively. Conclusions: Higher RMS values required a smaller pupil to achieve optimum VA. PPP can help achieve pinhole size in accordance with patient's optimum pinhole requirement. [ABSTRACT FROM AUTHOR]

The climate over North India during winter has been endorsed with a good amount of precipitation that occurs due to the interaction between the tropical–extratropical flows. We examined two land surface parameterizations namely Biosphere Atmosphere Transfer (BAT) scheme and the Community Land Model (CLM) with the Regional Climate Model (RegCM) on simulation of North Indian winter climate. RegCM model is configured for the Indian region and was integrated from 1 January 1982 to 31 December 2016 using the initial–boundary condition of ERA-interim reanalysis. Our results reveal that the CLM features of rainfall, temperature, and circulation at 700 hPa provided an added value with respect to BAT. The analysis of extreme rainfall seasons revealed the relative resemblance of CLM with CRU by means of sensible heat flux and soil moisture analyses. Various verification methods such as Taylor metrics, Improvement parameter, and root mean square deviation also reveal the consistency of CLM in its better performance over BAT simulations. These findings suggest that the implementation of CLM scheme with RegCM results in the added value of winter climate simulations than BAT over north India and thus the usage of the same are encouraged over the region. [ABSTRACT FROM AUTHOR]

Objectives. The combined role of whole-body vibration (WBV) exposure and awkward posture on musculoskeletal disorders (MSDs) experienced by dumper operators in two metalliferous mines in India was evaluated through a cross-sectional study. Methods. Frequency-weighted root mean square (rms) acceleration was used for WBV exposure assessment. Anthropometry and rapid upper limb assessment (RULA) were used for static and dynamic posture assessment, respectively. Prevalence of MSDs was assessed using the Nordic musculoskeletal questionnaire (NMQ). Logistic regression was used to assess the factors contributing to MSD problems. Results. The rms values revealed that the operators exceeded the lower limit of Standard No. ISO 2631-1:1997. The dynamic posture study revealed that the majority of dumper operators were taking awkward postures and 58–74% of them were subjected to high and medium levels of MSD risk. The adjusted odds ratio (7.96, 95% confidence interval [1.24, 41.35]) for the most awkward postures revealed WBV exposure as the significant risk factor for MSD problems among the operators. Conclusion. WBV exposure and posture of operators should be regularly monitored and corrective actions implemented to reduce their MSD problems. Ergonomic seat design based on the anthropometry of the operators should be assessed at the time of procuring new equipment. [ABSTRACT FROM AUTHOR]

In this paper, a combined approach of Principal Component Analysis (PCA)-based Extreme Learning Machine (ELM) for boiler output forecasting in a thermal power plant is presented. The input used for this prediction model is taken from the boiler unit of the Yermarus Thermal Power Station (YTPS), India. Calculation of the accurate electrical output of a boiler in an operating system requires the knowledge of hundreds of operating parameters. The dimensionality of the input dataset is reduced by applying principal component analysis using IBM@SPSS Software. In the process of principal component analysis, a dataset of 232 parameters is standardized into 16 principal components. The total dataset collected is divided into training and testing datasets. The extreme learning machine is designed for various activation functions and the number of neurons. Sigmoid and hyperbolic tangent activation functions are studied here. Its generalization performance is examined in terms of the Mean Square Error (MSE), Mean Absolute Error (MAE), Root Mean Square (RMSE), and Mean Absolute Percentage Error (MAPE). ELM and PCA–ELM are compared. In both the ELM and PCA–ELM models, when the extreme learning machine was designed with a sigmoid activation function with 100 nodes in the hidden layer, RMSE was 5.026 and 4.730, respectively. Therefore, the developed combined approach of PCA–ELM proved as a promising technique in forecasting with reduced errors and reduced time. [ABSTRACT FROM AUTHOR]

The use of the groundwater flow model is prevalent in the field of hydrogeology. The models have been used to address a variety of hydrogeological conditions including flow and transport of contaminants for risk evaluation. In the present study, a transient groundwater flow model for part of the Bemetara district of Chhattisgarh was developed to determine in detail the groundwater flow in the shallow and deep aquifer. The model simulates groundwater flow over an area of about 588 sq. km with a uniform grid size of 500 m by 500 m and contains two layers, 53 rows, and 68 columns. The visual MODFLOW software was used in this study to simulate groundwater flow. The conceptual model was built by analyzing the hydrogeological data. Based on the available data observed from 2015 to 2018, which provide insights to understand the dynamic behavior of groundwater systems and to predict spatial-temporal distributions of groundwater levels in responding to changes in the aquifer environment. 10 observatory wells within the study area were used for observation as well as calibration purposes. With the help of hydraulic conductivities and storage coefficients, the model has been calibrated with a normalized root mean squared of 7.477 % for steady-state & transient state NRMS is 9.242 %. The model has been forecasted for 2190 days up to the year 2024, suggests the depletion of the water table with an average annual fall of about 50cm, which indicates the overall projected depletion of the water table by 2024 will be 2.5–4 meters in different place of the study area. To mitigate this hazardous condition 15% reduction in the pumping of groundwater and the establishment of a total of four recharge wells has been suggested. [ABSTRACT FROM AUTHOR]

Black fungus is the foremost life-threatening disease during the SARS-CoV-2 affected patients and spreading quickly in the region of the subcontinent of India although there was no prescribed proper medication. As the Dglucofuranose and its derivatives are reported to show strong antifungal activity, this study has been designed with them for their computational investigation. Firstly, the overallprediction of activity spectra for substances (PASS) value illustrates a goodprobability to be active(Pa) and probability to be inactive (Pi) value. Next, pharmacokinetics parameters including drug-likeness and Lipinski's rules, absorption, distribution, metabolism, excretion, and toxicity (ADMET) parameters, and overall quantum calculation of computational approaches by Density Functional Theory (DFT) have graduallybeen performed to analyze quantum calculations. After the analysis of docking score, it is found at -9.4 kcal/mol, -7.5 kcal/mol, -7.8 kcal/mol, -8.5 kcal/mol against the strain of black fungus protein strains Mycolicibacterium smegmatis, Mucor lusitanicus, Rhizomucor mieh, and white fungus protein Candida Auris, Aspergillus luchuensis and Candida albicans. Next, the molecular dynamics of docked complexes have been performed to check their stability in biological systems with water ranging 100 ns calculating the Root Mean Square Deviation (RMSD) and Root Mean Square Fluctuation (RMSF)where the minimum RMSD and RMSF value indicated the higher stable configuration of docked complexes. These compounds have perfectly matched all the pharmacokinetics criteria to be a good drug candidate against both black and white fungus, and they are non-carcinogenic, low solubility, low toxic for both aquatic and non-aquatic. In addition, the quantum calculation using DFT conveys the strongest support and information about their chemical stability and biological significance. Finally, it could be concluded that the carboxylic group and methyl group inthe benzene ring causes higher binding affinity against black and white fungus protein strain through the formation of hydrogen and hydrophobic bonds. [ABSTRACT FROM AUTHOR]

The efficacy of the standard performance metrics [mean bias (Bias), root mean square deviation (RMSD), and correlation coefficient (CC)] compared to a new symmetric index of agreement (λ) for the evaluation of numerical weather prediction models is investigated in this study. It evaluates the weather research and forecasting (WRF) model with the global precipitation measurement's (GPM) Integrated Multi-satellitE Retrievals for GPM (IMERG) and station rainfall, as the reference datasets. This study uses three IMERG products, namely: GPM infrared-microwave merged gauge corrected (GMS), GPM microwave-calibrated infrared (GIR), and GPM inter-calibrated microwave (GMW) rainfall. The analysis showed that WRF rainfall when compared to different reference datasets is producing similar RMSD values but significantly different Bias values. This behavior is because of the inverse relationship between Bias and standard deviation of residual ( σ R ). It is so because RMSD is a function of both. However, λ is able to appropriately represent the distinct performances of WRF. The regions with contradictory behavior of RMSD and CC are also appropriately represented in λ. The evaluation using λ showed that WRF is comparable to GMS and GIR, except for GMW. The performance of WRF was not found to be very promising when compared to station rainfall, which is attributed to WRFs representation efficiency and the effect of topography. However, a comparison of IMERG products with station rainfall showed that GMS was the most agreeable followed by GIR and GMW. The study also showed that the efficacy of λ is related to its non-linear relationship with Bias and CC. [ABSTRACT FROM AUTHOR]

Background: There are several methods of bone age (BA) assessment, which include Gruelich-Pyle (GP), Gilsanz-Ratib (GR), and Tanner Whitehouse-3 (TW-3) methods. Although GP atlas is the most widely used, there are concerns about its accuracy in children of different ethnicities, making the use of the TW-3 method an attractive option in Indian children. Objectives: 1) To assess the relationship of BA with chronological age (CA) as assessed by different methods (GP, GR, and TW-3) in healthy Indian children 2) To assess which of the three methods of BA assessment is more suitable in Indian children. Methodology: X-rays of 851 children (438 boys and 413 girls, aged 2–16.5 years) were analyzed by four independent observers using three different methods of BA estimation (GP, GR, and TW-3). Mean BAs were converted to Z-scores. For purpose of deciding which method of BA was most suitable in our cohort, a test of proportions and root mean square (RMS) deviations were computed. Results: Using the test of proportions, the TW-3 method was most suitable overall (P < 0.05). TW-3 method was again most applicable in prepubertal boys (P < 0.05), in prepubertal girls (although not significant, P > 0.1), and pubertal girls (P < 0.05). However, in pubertal boys, the GR atlas method was most suitable (P < 0.05). The same results were obtained when root mean square (RMS) deviations were computed. Interestingly, BA was underestimated in Indian boys irrespective of the method used. In Indian girls, however, the BA was underestimated till the pubertal growth spurt, after which there was rapid advancement of BA. Conclusions: Among the three methods (GP, GR, and TW-3), the BAs estimated by the TW-3 method were closest to CAs. Hence, it seems reasonable to recommend the use of the TW-3 method for BA estimation in the Indian population till an Indian standard bone age atlas is developed. [ABSTRACT FROM AUTHOR]

The area of North-East India and Nepal Himalaya undergoes seasonal deformations due to the variation of surface mass loads induced mainly by annual monsoon precipitation. The present study focuses on comparing seasonal horizontal deformations of the Earth's surface obtained over the area of North-East India and Nepal Himalaya using Global Positioning System (GPS) and the corresponding ones obtained from Gravity Recovery and Climate Experiment (GRACE) satellite mission data. Seasonal deformations of the Earth's surface in horizontal components were determined using daily observations from 36 GPS stations located in North-East India and Nepal Himalaya and Release-05 GRACE-based Global Geopotential Models (GGMs). The consistency between these seasonal horizontal deformations was investigated using three statistical metrics, namely: the correlation, Weighted Root Mean Square (WRMS) reduction and Nash–Sutcliffe model Efficiency (NSE). The results obtained indicate that at nearly 89% of GPS stations investigated, positive correlation can be determined between seasonal deformations of the Earth's surface in the north component obtained from GPS and the corresponding ones from GRACE data. The percentage of WRMS reductions computed from seasonal horizontal deformations of the Earth's surface obtained using GPS and GRACE data reach ~ 18% and 0.71% in north and east components, respectively. Moreover, we obtain the median value of NSE almost 0.28 for north and − 0.01 for east components. The study finds that seasonal horizontal deformations in the area investigated are controlled by local tectonics, and realizes the need of a realistic Earth model comprising local crustal inhomogeneities and tectonic features for better constraining the surface deformations in this region. [ABSTRACT FROM AUTHOR]

Determining nearshore bathymetry by traditional surveying methods is a challenging task as it involves huge costs and efforts. Most of the coastal shallowwater zones worldwide either remain unmapped or not updated. Bathymetry estimations from optical satellite imageries have been increasingly implemented as an alternative tool for traditional bathymetry surveys. In this study, we examine the usefulness of freely available, five-day revisit and relatively highresolution Multi Spectral Instruments (MSI) on-board Sentinel-2A and 2B twin satellites. A process workflow has been developed which automatically incorporates a robust atmospheric correction through ACOLITE software and multi-scene compositing of several scenes to improve the reliability and no data gaps. Two study sites in India are explored owing to their variability in submarine morphology. High-resolution bathymetry maps are generated through a log-ratio transform model calibrated with minimal in situ data from the jet ski soundings. The satellite-derived bathymetry obtained has an overall bias of -0.01 and 0.02 m, and root mean square error of 1.09 and 0.93 m respectively, at two study sites up to 15 m depth. The consistency in bathymetry retrieval indicates a potential for automated application for the benefit of operational and scientific studies. These high-resolution maps capture small-scale nearshore features like sandbars and rip channels, which are of prime importance for coastal and beach managers. [ABSTRACT FROM AUTHOR]

In recent decades, various conventional techniques have been formulated around the world to evaluate the overall water quality (WQ) at particular locations. In the present study, back propagation neural network (BPNN) and adaptive neuro-fuzzy inference system (ANFIS), support vector regression (SVR), and one multilinear regression (MLR) are considered for the prediction of water quality index (WQI) at three stations, namely Nizamuddin, Palla, and Udi (Chambal), across the Yamuna River, India. The nonlinear ensemble technique was proposed using the neural network ensemble (NNE) approach to improve the performance accuracy of the single models. The observed WQ parameters were provided by the Central Pollution Control Board (CPCB) including dissolved oxygen (DO), pH, biological oxygen demand (BOD), ammonia (NH3), temperature (T), and WQI. The performance of the models was evaluated by various statistical indices. The obtained results indicated the feasibility of the developed data intelligence models for predicting the WQI at the three stations with the superior modelling results of the NNE. The results also showed that the minimum values for root mean square (RMS) varied between 0.1213 and 0.4107, 0.003 and 0.0367, and 0.002 and 0.0272 for Nizamuddin, Palla, and Udi (Chambal), respectively. ANFIS-M3, BPNN-M4, and BPNN-M3 improved the performance with regard to an absolute error by 41%, 4%, and 3%, over other models for Nizamuddin, Palla, and Udi (Chambal) stations, respectively. The predictive comparison demonstrated that NNE proved to be effective and can therefore serve as a reliable prediction approach. The inferences of this paper would be of interest to policymakers in terms of WQ for establishing sustainable management strategies of water resources. [ABSTRACT FROM AUTHOR]

Abstract: A detailed study of monthly average daily diffuse solar radiation for selected Indian locations have been performed using five years (2001–2005) measured data. The data of four prominent locations (Jodhpur, Calcutta, Bombay and Pune), representing varying weather conditions of the entire country, have been taken for the present study. The correlations between the diffuse fraction (H d/H) and the sunshine fraction (S/S 0) have been developed using regression analysis method for each selected location as well as for all Indian locations, we call it All India Correlation (AIC). The results obtained from present AIC are well compared with the measured data along with the estimates of Liu and Jordan, Gopinathan and Iqbal for different locations. The comparisons between various data conclude that AIC can be used to estimate diffuse fraction for any location in India. For further validation and to show the accuracy of present correlations, statistical tests of root mean square error (RMSE), mean bias error (MBE) and mean percentage error (MPE) are also performed. [Copyright &y& Elsevier]