RÉSUMÉ
Rice crop yield data and weather data were considered in this study, covering the past twenty-nine years (1991-2019) in Prayagraj District, Uttar Pradesh. The data was sourced from DACNET and the College of Forestry, SHUATS Prayagraj. The analysis comprised a calibration period of 26 years (90% of the dataset) and a validation period using the remaining data (10%). In this study, 75.9% of the data were utilized for training the Artificial Neural Network (ANN) model, while the remaining 24.1% were allocated for testing and validation, ensuring comprehensive model assessment. The primary evaluation metric employed for model efficiency was the Normalized Root Mean Squared Error (nRMSE), with a focus on achieving the lowest values. Both a Stepwise Linear Regression technique and a Neural Network were employed for rice yield prediction. Notably, the regression-based model exhibited superior performance compared to the ANN model, as indicated by the nRMSE values. This conclusion was drawn from the observation that the regression-based model yielded the best-fitting results. The study's findings highlight the significance of Bright Sunshine Hours in relation to nRMSE and the coefficient of determination, which were recorded at 0.00025 and 0.94, respectively. This underlines the importance of this meteorological factor in accurately predicting rice crop yield.
RÉSUMÉ
The Bundelkhand region, one of the most vulnerable locations in central India, is prone to severe drought and crop failure attributed to annual rainfall fluctuation. In this study, basic statistics were utilized to determine the variances in rainfall across different districts in the Bundelkhand zone for 30 years (1987-2016) The average annual rainfall was found to be maximum for Damoh district (1169.24 mm) followed by Sagar district (1163.04 mm), Panna district (1118.79 mm), whereas it was minimum for Jalaun district (774.91 mm) followed by Datia district (841.61 mm), Hamirpur district (849.30 mm). In this study period in the year 2010 received low annual rainfall. The average seasonal rainfall was found to be maximum for Sagar district (1075.52 mm) followed by Damoh district (1073.40 mm), Panna district (1008.74 mm) whereas was minimum for Jalaun district (701.11 mm) followed by Datia district (769.1 mm). In this 30 year 1990 real received low seasonal rainfall. This research demonstrates the rainfall pattern over the study region and indicates susceptible locations that are more likely to face water stress as a result of rainfall variability.
RÉSUMÉ
Background: Aim of the study was to evaluate the role of endoscopy and ultrasonography in pediatric patients suffering from portal hypertension .subjects: children under 12 years of age hospitalized with any symptom or sign suggestive of portal hypertension.Methods: The study was conducted in 30 children with portal hypertension. They were divided into two groups on the basis of site of lesion: extrahepatic (extra hepatic portal vein obstruction) and intrahepatic (chronic liver diseases).Results: Mean age of children with EHPVO (extra hepatic portal vein obstruction) was 4 years and 4 months while that of children with CLD (chronic liver diseases) mean age was 8 years and 4 months. Endoscopic findings in patients with EHPVO have severe grade of varices as compared to those with CLD. In patients with EHPVO, the most common USG finding was nonvisualisation of the main portal vein or either branch (75-85%). Portal vein cavernoma was seen in 75% of these patients. Portosystemic collaterals were visualized in 23 patients' in which the left gastric collateral (60%) was the most common followed by short gastric collaterals in 11 children (55%).Conclusions: Endoscopy and ultrasonography are new and better modalities to assess the diagnosis and severity of portal hypertension. Extra hepatic portal vein obstruction is the commonest cause followed by intrahepatic obstruction (Chronic liver diseases).