Computational intelligence methods for predicting fetal outcomes from heart rate patterns

In this thesis, methods for evaluating the fetal state are compared to make predictions based on Cardiotocography (CTG) data. The first part of this research is the development of an algorithm to extract features from the CTG data. A feature extraction algorithm is presented that is capable of extracting most of the features in the SISPORTO software package as well as late and variable decelerations. The resulting features are used for classification based on both U.S. National Institutes of Health (NIH) categories and umbilical cord pH data. The first experiment uses the features to classify the results into three different categories suggested by the NIH and commonly being used in practice in hospitals across the United States. In addition, the algorithms developed here were used to predict cord pH levels, the actual condition that the three NIH categories are used to attempt to measure. This thesis demonstrates the importance of machine learning in Maternal and Fetal Medicine. It provides assistance for the obstetricians in assessing the state of the fetus better than the category methods, as only about 30% of the patients in the Pathological category suffer from acidosis, while the majority of acidotic babies were in the suspect category, which is considered lower risk. By predicting the direct indicator of acidosis, umbilical cord pH, this work demonstrates a methodology to achieve a more accurate prediction of fetal outcomes using Fetal Heartrate and Uterine Activity with accuracies of greater than 99.5% for predicting categories and greater than 70% for fetal acidosis based on pH values --Abstract, page iii

Target identification and drug design for human pathogen chlamydophila pneumoniae -in silico analysis

Whole genome sequence of the human pathogen Chlamydophila pneumoniae and four other strains of same species were analyzed to identify drug targets. Total number 4388 protein coding genes were studied from four strains; in which 3948 genes were having more than 100 amino acids in their coding sequence were selected; we found 147 genes were identified as non-human homologs and conserved proteins among four strains. These non-human homologs genes and their encoding protein were categorized on the basis of the pathways involved in the basic survival mechanisms of the bacterium. Further, MSA of these genes showed eight different types of proteins as a novel drug target to design a drug. The modeled Holliday junction DNA helicase RuvB protein has more appropriate active sites among all other target proteins. Though all chosen drugs bind to Holliday junction DNA helicase RuvB protein, the binding site on the target protein with the minimum binding energy was selected. By using the active site prediction tools, under the optimized conditions we designed a set of antibiotics. Docking was done with the Autodock 4.0 with the different conformations of each ligand. This is the better drug that binds to the active site of target protein and inhibits their activities, which will effects one of the most essential pathways involved in DNA replication, recombination, modification and repair. Therefore, this in silico analysis provides rapid and potential approach for identification of drug target and designing of dru

Effect of surgical trauma on serum magnesium levels in the early postoperative period

Background: For proper functioning of energy system in the body, magnesium is essential. Deficiency of magnesium leads to hyperactivity of central nervous system and neuromuscular system. During surgery or before surgery or after surgery there can be alterations in the volume of fluid and composition of electrolytes. Objective was to study the effect of surgical trauma on serum magnesium levels in the early postoperative period.Methods: The present hospital based cross sectional study was carried out for a period of one year among 35 cases of surgical stress and 10 normal as control. Institutional ethics committee permission was taken prior to the start of the study. Individual informed consent was noted from each individual patient from both cases and controls. Data was recorded in the pre-designed pre-tested semi structured questionnaire for the present study. Serum magnesium level was assessed in both the groups and compared.Results: It was found that the preoperative magnesium levels were more as compared to postoperative levels among both the types of stress groups but the difference was not found to be statistically significant (p > 0.05). Among the mild to moderate stress groups, it was found that the preoperative magnesium levels were more as compared to postoperative levels among all the age groups but the difference was not found to be statistically significant (p > 0.05). Among the severe stress groups, it was found that the preoperative magnesium levels were more as compared to postoperative levels among all the age groups but the difference was not found to be statistically significant (p > 0.05).Conclusions: Occurrence of postoperative hypomagnesaemia plays a minor role in normal surgical convalescence

Non-destructive Techniques to Identify the Presence of Silane on Concrete

The Oklahoma Department of Transportation (ODOT) wants to develop a non-destructive technique to identify the presence of silane on bridge decks. Two of the methods (Germann Water Permeability Test and Wenner probe resistivity method) were examined to understand the consistency of the technique and their accuracy. A simple field technique was developed to identify the presence of concrete sealer on concrete.School of Civil & Environmental Engineerin

Modeling rain-fed maize vulnerability to droughts using the standardized precipitation index from satellite estimated rainfall-Southern Malawi case study

During 1990s, disaster risk reduction emerged as a novel, proactive approach to managing risks from natural hazards. The World Bank, USAlD, and other international donor agencies began making efforts to mainstream disaster risk reduction in countries whose population and economies were heavily dependent on rain-fed agriculture. This approach has more significance in light of the increasing climatic hazard patterns and the climate scenarios projected for different hazard prone countries in the world. The Famine Early Warning System Network (FEWS NET) has been monitoring the food security issues in the sub-Saharan Africa, Asia and in Haiti. FEWS NET monitors the rainfall and moisture availability conditions with the help of NOAA RFE2 data for deriving food security status in Africa. This paper highlights the efforts in using satellite estimated rainfall inputs to develop drought vulnerability models in the drought prone areas in Malawi. The satellite RFE2 based SPI corresponding to the critical tasseling and silking phases (in the months of January, February, and March) were statistically regressed with drought-induced yield losses at the district level. The analysis has shown that the drought conditions in February and early March lead to most damage to maize yields in this region. The district-wise vulnerabilities to drought were up scaled to obtain a regional maize vulnerability model for southern Malawi. The results would help in establishing an early monitoring mechanism for drought impact assessment, give the decision makers additional time to assess seasonal outcomes, and identify potential food-related hazards in Malawi

Current status of fuel cell based combined heat and power systems forresidential sector

Combined Heat and Power (CHP) is the sequential or simultaneous generation of multiple forms of usefulenergy, usually electrical and thermal, in a single and integrated system. Implementing CHP systems inthe current energy sector may solve energy shortages, climate change and energy conservation issues.This review paper is divided into six sections: thefirst part defines and classifies the types of fuel cellused in CHP systems; the second part discusses the current status of fuel cell CHP (FC-CHP) around theworld and highlights the benefits and drawbacks of CHP systems; the third part focuses on techniques formodelling CHP systems. The fourth section gives a thorough comparison and discussion of the two mainfuel cell technologies used in FC-CHP (PEMFC and SOFC), characterising their technical performance andrecent developments from the major manufacturers. Thefifth section describes all the main componentsof FC-CHP systems and explains the issues connected with their practical application. The last partsummarises the above, and reflects on micro FC-CHP system technology and its future prospects

Remdesivir use in pregnant women with severe COVID-19

Numerous therapeutic strategies are proposed and tested for SARS CO-V2 infection. Remdesivir is researched and proposed by various societies. Studies about efficacy and safety in pregnancy are limited. A case series of 22 pregnant women effected with severe COVID disease and who received remdesivir, over a period of 1 year from May 2020 to May 2021 is presented. The 12 antenatal and 10 post-partum women were included. Demographic factors, baseline, day 3 and day 7 blood values of haemoglobin, total leukocyte count, platelets, liver enzymes, serum creatinine and D-dimers were collected. Adverse events were reported. Pregnancy complications and foetal and neonatal complications were studied. Pre-eclampsia was the most common comorbidity. The 99% of pregnant women and 100% of postpartum women recovered from COVID disease after remdesivir use. Lab investigations did not change considerably during the week of remdesivir use, suggesting its safety. Incidence of adverse events reported is 36.3%, of these 9% are serious adverse events. There are no antenatal or post-natal complications. No incidence of teratogenicity, foetal or neonatal complications. Incidence of feto-maternal transmission was 9%. Remdesivir is effective in treating severe SARS-CoV2 infection and has safety profile in pregnancy with regard to maternal and foetal effects

Application of a Household-Based Molecular Xenomonitoring Strategy to Evaluate the Lymphatic Filariasis Elimination Program in Tamil Nadu, India

Lymphatic filariasis (LF) is one of the world’s foremost debilitating infectious diseases with nearly 800 million people at risk of infection. Given that LF is a mosquito-borne disease, the use of molecular xenomonitoring (MX) to detect parasite DNA/RNA in mosquitoes can serve as a valuable tool for LF monitoring and evaluation, particularly in Culexvector areas. We investigated using MX in a low-level prevalence district of Tamil Nadu, India by applying a household-based sampling strategy to determine trap location sites. Two independent mosquito samples were collected in each of a higher human infection hotspot area (sites with community microfilaria prevalence �1%) and across a larger evaluation area that also encompassed the hotspots. Pooled results showed mostly reproducible outcomes in both settings and a significant higher pool positivity in the hotspot area. A follow-up survey conducted two years later reconfirmed these findings while also showing a reduction in pool positivity and estimated prevalence of infection in mosquitoes in both settings. The utilization of a household-based sampling strategy for MX proved effective and should be further validated in wider epidemiological settings