Modeling of Rainfall- Runoff relationship using Artificial Neural Networks

Abstract— Relationship between rainfall and runoff plays a significant role in generation of stramflows. The objective of the study is to model the rainfall – runoff using daily, weekly and monthly data for a catchment in the coastal Karnataka region using Artificial Neural Networks. The study uses data from two rainguage stations and a riverguage station located within the catchment. Fifteen models were developed using different input combinations which included 11 daily, 2 weekly and 2 monthly models. The efficiency of the models were compared using the statistical parameters - Coefficient of Correlation (r), Index of Agreement (d), Nash-Sutcliffe Efficiency (NSE) and Root Mean Square Error (RMSE). The results indicate that the daily model with daily past one day rainfall, past 2 day rainfall, past one day maximum temperature and past one day runoff as inputs was the best. The results can be used for any future studies of the catchment

Study of correlation between maternal body mass index with maternal and perinatal outcome

Background: To study the correlation between maternal body mass index (BMI) with maternal and perinatal outcome in women admitted to labour ward in Department of OBG, VIMS, Ballari.Methods: This observation study was conducted in Department of OBG, VIMS, Ballari for a period of one year between 1st October 2014 to 30th September 2015. All women admitted to labour ward with full term singleton pregnancy were included in the study. The cases were classified into four groups as under-weight (BMI 30kg/m2). The maternal and perinatal outcome noted and studied in the above groups.Results: A total of 500 cases were included during the study period of one year, out of which 15% were under-weight, 68% were normal BMI, 12% were over-weight and 5% cases were obese(BMI >30kg/m2). The patients with low BMI had higher incidence of low birth weight (40%) and perinatal deaths. Increased BMI category was associated with higher incidence of PIH (25-28%), operative deliveries (50-68%), PPH (12%), microsomal babies (32%), low APGAR (24%) and perinatal deaths (12%).Conclusions: Adverse maternal and perinatal outcomes are significantly related to extremes of BMI categories and least complications were seen in normal BMI group

Analysis of Stock Portfolio with Global Economic Factors using Dynamic Data Modelling

This article analyzes stock portfolios and worldwide economic challenges. This study uses APIs to retrieve data and analyze correlations. To determine and measure how economic indicators affect stock performance. This work introduces an autoencoder-based model to better comprehend the complex relationship between economic conditions and stock portfolio dynamics. The analysis begins with an API retrieval of a wide range of macroeconomic information. These indicators include global economic metrics like GDP, unemployment, CPI, federal funds rates, and treasury bill rates. After collection, data is carefully curated and prepared for analysis. This study uses correlation analysis to understand economic variables and stock portfolio performance. This study explores how economic conditions affect stock prices and portfolio returns. This study seeks to discover trends, dependencies, and future issues that may affect investment decisions. This study also introduces an autoencoder-based neural network model to capture complex nonlinear relationships between economic variables and stock portfolio behavior. Deep learning improves interpretability and prediction, allowing a better understanding of the complex financial ecosystem dynamics. The inquiry provides valuable insights for investors, financial experts, and regulators. This study advances data-driven investment and risk management solutions. The autoencoder-based approach also reveals latent structures and hidden factors that affect stock portfolios. This novel approach opens new study options. In conclusion, this study provides a thorough stock portfolio analysis approach for global economic challenges. API data retrieval, correlation analysis, and a novel autoencoder model are used in this work to better understand the complicated relationships between economic indicators and financial markets. These insights can improve investment and policy decisions in a more integrated and dynamic global economy

Evaluation of serum lipids in preeclampsia: a comparative study

Background: Preeclampsia occurs in 7 to 10% of pregnancies worldwide. At present most, popular theory is an oxidative stress. Abnormal lipid profiles and species may have a role in promotion of oxidative stress and vascular dysfunction seen in pre-eclampsia. Objectives of this study was carried out to evaluate lipid profile in subjects with preeclampsia and to compare lipid profile in subjects of preeclampsia as compared to normal pregnant women.Methods: A comparative longitudinal study was conducted under the tertiary care hospital setting over a period of one year where 440 study subjects were enrolled out of which 220 subjects were pre-eclamptic and 220 subjects were normotensive with gestation of 28 weeks to till term. Lipid profiling was done in all the subjects.Results: The mean serum levels of total cholesterol (198.5±18.91), HDL (50.63±9.35), LDL (84.5±16.16), VLDL (42.75±4.72) and TGA (74.92±11.95) were higher in pre-eclampsia group compared to normotensive group and this difference in the levels of lipid parameters was found to be statistically significant.Conclusions: Dyslipidemia is significantly evident in preeclampsia and plays an important role in its pathogenesis

A study of prevalence and determinants of gestational diabetes mellitus

Background: It is estimated that one out of every 200 pregnancies is complicated by diabetes mellitus and additionally that five in every 200 pregnant women will develop gestational diabetes. Risk factors of gestational diabetes mellitus may act directly or indirectly to facilitate the onset of diabetes, it is of utmost important to detect.Methods: A hospital based cross-sectional study was conducted in the setting of department of Obstetrics and Gynaecology, JSS Medical College and Hospital, Mysore, Karnataka, India during the year 2006-2007. All antenatal pregnant women with 24-28 weeks of pregnancy attending the OBG department (both outpatients and inpatients) were included in the study. Women with history of pregestational diabetes (overt diabetes) were excluded from the study. Screening test of glucose challenge test (GCT) was done and those positive for GCT were subjected to oral glucose tolerance test (OGTT) to diagnose the gestational diabetes mellitus.Results: Out of 800 antenatal pregnant women, two thirds of them were in the age group of 21-25 years (67.5%), 60% of the women were multigravida. The prevalence of GDM in this study was 5.25% (95% CI; 3.8%-6.9%). GDM was significantly associated with past history of macrosomia (OR: 28), GDM (OR: 8.2), abortions (OR: 8.2), family history of diabetes mellitus (OR: 8.0), obesity (OR: 4.7) and maternal age >25 years (OR: 3.5)Conclusions: Overall prevalence of GDM was 5.5%. Increasing maternal age, family history of DM, past history of GDM, macrosomia, abortions and increasing maternal BMI were the important determinants of GDM

Preserving neural function under extreme scaling

Important brain functions need to be conserved throughout organisms of extremely varying sizes. Here we study the scaling properties of an essential component of computation in the brain: the single neuron. We compare morphology and signal propagation of a uniquely identifiable interneuron, the HS cell, in the blowfly (Calliphora) with its exact counterpart in the fruit fly (Drosophila) which is about four times smaller in each dimension. Anatomical features of the HS cell scale isometrically and minimise wiring costs but, by themselves, do not scale to preserve the electrotonic behaviour. However, the membrane properties are set to conserve dendritic as well as axonal delays and attenuation as well as dendritic integration of visual information. In conclusion, the electrotonic structure of a neuron, the HS cell in this case, is surprisingly stable over a wide range of morphological scales

A study of prevalence and association of fundus changes in pregnancy induced hypertension

Background: The pathological changes of pregnancy induced hypertension appear to be related to vascular endothelial dysfunction and its consequences. The retinal vascular changes generally, but not always, correlate with the severity of systemic hypertension. To find out the prevalence and association of retinal changes in pregnancy induced hypertension.Methods: A hospital based cross-sectional study was conducted where all antenatal pregnant women who fulfilled the diagnostic criteria of PIH were included in this study. Patients who had pre-existing diabetes or hypertension or renal disease or hazy media which did not permit fundus visualization were excluded from the study.Socio-demogrpahic and obstetric data was collected and all the patients were subjected to detailed clinical examination followed by fundoscopic examination.Results: Out of the total 423 patients of PIH examined, the retinal changes (hypertensive retinopathy changes) were noted in 181 (42.7%) patients. The prevalence of retinopathy changes was more among patients with imminent Eclampsia (76.5%) and eclampsia patients (50%). As the severity of the PIH increased the Odds of women developing retinopathy also increased substantially from OR: 17.6; 95% CI: 3.1-136.3 in severe PIH to OR: 253; 95% CI: 47.2-1935 in Imminent eclampsia and this association between the severity of PIH and the development of retinopathy changes was found to be statistically significant.Conclusions: Fundus examination in cases of PIH is of paramount importance in monitoring and managing cases as it co-relates with the severity of PIH

Analysis of caesarean section rate in tertiary care hospital according to Robson`s 10 groups classification

Background: The caesarean section (CS) delivery rate is steadily increasing worldwide, including India. Identifying the proportion of women in various categories as per Robson's ten group classification system and CS rate among them is important to bring down the increasing CS rate.Methods: This case series study was conducted at Vijayanagar Institute of Medical Sciences (VIMS), a tertiary care teaching hospital in Ballari, Karnataka, India. All pregnant women who have been admitted for delivery were enrolled and the data was collected for the women delivered by CS during January 2016 to December 2016 and proportions in various groups as per Robson’s ten-group classification system were calculated.Results: Among a total of 6980 women delivered during study period, 2992 (42.8%) delivered by CS. The CS rates among various groups varied from 100% among women with abnormal lies and group 6-95% (all nulliparous breeches) group 5-94% (Previous CS, single cephalic, >37 weeks) to 10 to 15% among multiparous women with spontaneous labour having single cephalic pregnancy (group 3). Among women with previous section, CS rate was very high (89.6%). Women with previous CS (group 5) contributed maximum (40.24%) to the total number of CS.Conclusions: In the present study, all women with breech presentation and abnormal lies delivered by CS and repeat CS was the highest contributor to all CS deliveries

DISCOVERY INJURE BASED ON SOCIAL CONNECTIONS IN NETWORK

We recommend suggesting the attack on the site if a particular user has visited the particular URL on YouTube. Our attacks are openly close to the combination of information available: click on Shortcuts Twitter Analysis and Services. For 2 seconds, we create monitoring accounts that monitor the messages of the targeted users to compile all the small URLs that can be clicked to address the users. After that, we analyze the URL of those people who are pushing the analysis and are using the user's metadata. Former researchers have considered technological attacks on the social privacy system, for example, private attributes and inappropriate users. The diagnostic results show that our attacks indicate that with precision in health and context. Let's see the novelization strategy that will be a special user, click on some specific URLs in a YouTube tab

Multiphysics Integrated Coupling Environment (MICE) User Manual

The complex, multi-part nature of waste glass melters used in nuclear waste vitrification poses significant modeling challenges. The focus of this project has been to couple a 1D MATLAB model of the cold cap region within a melter with a 3D STAR-CCM+ model of the melter itself. The Multiphysics Integrated Coupling Environment (MICE) has been developed to create a cohesive simulation of a waste glass melter that accurately represents the cold cap. The one-dimensional mathematical model of the cold cap uses material properties, axial heat, and mass fluxes to obtain a temperature profile for the cold cap, the region where feed-to-glass conversion occurs. The results from Matlab are used to update simulation data in the three-dimensional STAR-CCM+ model so that the cold cap is appropriately incorporated into the 3D simulation. The two processes are linked through ModelCenter integration software using time steps that are specified for each process. Data is to be exchanged circularly between the two models, as the inputs and outputs of each model depend on the other