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Background: This study aimed to determine the utility of RMI 2 in distinguishing benign and malignant adnexal masses in low-income countries. Methods: For the purpose of this retrospective observational study, relevant data from patients who attended a tertiary care institution in central Gujarat between June 2020 and June 2022 were obtained from the Medical Records Department (MRD). Ultrasound and biochemical parameters along with epidemiological factors were identified and an RMI 2 score was calculated followed by statistical analysis. Results: Twenty-five (37.87%) of the sixty-six instances that were investigated were benign, two (3.03%) were borderline, and thirty-nine (59.09%), were malignant. Using RMI 2 at the traditional cut-off value of 250, results showed a sensitivity of 85.2% (95?%; CI=68.9-95.05), a specificity of 66.6% (95?%; CI=47.1-82.7 %), a positive predictive value of 74.36%, and a negative predictive value of 80.0 %. The ROC showed an AUC of 0.68 (CI=0.5-0.7) with a standard error of 0.07 (p=0.009). Conclusions: With a cut-off point of 250, RMI 2 was able to identify malignant masses with an 85.2% sensitivity and 66.6% specificity to enable timely referral to more advanced institutions for improved management in resource-constrained settings where its affordability and user-friendliness are favourable.
RESUMO
The soil and water conservation structures are constructed to overcome water scarcity as a result of interannual rainfall variability and paucity of the perennial source of water. The present study was aimed to estimate the design runoff for the efficient hydrologic design of various soils and water conservation structures using machine techniques for enabling efficient harvesting of available rainfall with economical design which can support in developing climate resilience for the Saurashtra region of Gujarat, India. The design rainfall at various return periods was predicted by Annual One Day Maximum Rainfall (ADMR) using three technics i.e. Probability Distribution Fitting, Artificial Neural Network (ANN) and Gaussian Process Regression (GPR) for 11 stations. Various goodness of fit tests revealed that ADMR was efficiently predicted by log-logistic (3P) distribution for six stations, generalized extreme value distribution for two stations and lognormal (3P), gamma (3P) and lognormal distribution for one station each. Among ANN and GPR, the performance indicators revealed that GPR has shown a higher capability to predict ADMR as compared to ANN with correlation coefficient ranging from 0.97 to 0.99, mean absolute error from 15 mm to 411 mm and root mean squared error from 40 mm to 494 mm for various stations. The design runoff estimation was demonstrated based on predicted ADMR for return periods suitable for various soil and water conservation structures like field bunding, terrace outlets and vegetative outlets, field diversion, permanent masonry gully control structures, earthen dam, etc. using SCS-Curve Number method for curve number 70 and 85. The study is useful for researchers, planners and engineers to implement the economical, efficient and safe design of various soil and water conservation structures.
RESUMO
Aim: Many crop modelling and climate simulation studies have reported variability in pest and pathogen distribution as well as their interaction with host. These prediction encourages to revisit the pest and pathogen epidemological and distribution studies in light of changing climate. In line with above assumption, the present field study was carried out to study the population dynamics of cowpea aphid (Aphis craccivora) and its influence on BCMV disease incidence. Methodology: In this field experiment, A. craccivora population and BCMV disease incidence data were collected in different standard meteorological weeks of 2013-2014 and 2014-2015. Impact of weather parameters on A. craccivora and BCMV disease incidence was statistically analyzed. Results: The significant change in A. craccivora population and BCMV disease incidence was documented during the study. The maximum aphid population was observed during rabi season and less was observed in kharif and summer season. Whereas, incidence of BCMV was recorded maximum in rabi season. Correlation analysis affirmed, minimum temperature (Tmin) and rainfall had negative impact on A. craccivora whereas weather parameters had non-significant impact on BCMV disease incidence. The regression models developed from the present study explained 41.4 % to 78.8 % and 18.5 % to 46.1% variability (R2) of aphid population and BCMV incidence, respectively. Interpretation: The weather parameters had more impact on A. craccivora population than BCMV disease incidence and merely presence of maximum number of A. craccivora was not a deciding factor for outbreak of virus disease incidence.
RESUMO
Background: The diagnosis of collagen vascular disease is based on clinical, serological and histological findings. The classical ANA indirect immunofluorescence assay is the most efficient screening test for LE. Aim and objectives: To study ANA profile in various collagen vascular diseases. Materials and methods: A study was conducted in 170 clinically confirmed cases of collagen vascular diseases during 2010-2012. A thorough clinical examination was carried out and baseline investigations were done. All the patients were subjected to complete ANA profile. Patients were followed up regularly in department of dermatology. Results: Majority of the patients (55%) in our study were those of lupus erythematosus and systemic sclerosis (30%). The study revealed that 92% patients of SLE, 90% of MCTD, 85% of systemic sclerosis and 50% each of dermatomyositis and overlap syndromes showed ANA positivity. 77.14% and 42.85% patients of SLE showed anti Ds DNA and anti Ro 52 positivity respectively. Anti scl 70 positivity was seen in 75% patients of systemic sclerosis. All patients of MCTD tested positive anti u1 RNP. Conclusion: ANA profile correlated very well with clinical manifestations in majority of patients in this study.
RESUMO
The adsorption of fluoride on corn cobs powder was investigated in the present study. Neat powdered corn cobs did not show remarkable adsorption but aluminium treated corn cobs had good adsorption capacity. The parameters studied include the contact time, concentration, temperature and pH. Near neutral pH was identified as the optimum condition of the medium, and 90 to 120 minutes was the best contact time for maximum fluoride adsorption. The adsorption process was found to follow Freundlich isotherm. The adsorption process was found to be exothermic as adsorption decreased with increasing temperature.