Essays on Maternal and Child Healthcare

India accounts for two-thirds of global maternal deaths and the highest number of infant deaths annually. Given the poor performance of maternal and infant healthcare service indicators, India launched two maternal health programs- a conditional cash transfer program called Janani Suraksha Yojna (JSY) in 2005 and a free services program called Janani Shishu Suraksha Karyakaram (JSSK) in 2011. The programs aim to reduce maternal and infant mortality through the promotion of public institutional delivery. Both provide financial incentives to pregnant women through a reduced price effect on delivery care. Using the Indian District Household Surveys, I exploit the differences in individual eligibility rules across states to estimate the impact of the programs on healthcare utilization and infant mortality measures. The results suggest that JSY and JSSK reduced home births and increased the use of public institutional care. While JSY also shifted women away from private to public facilities, JSSK increased the use of private care. I also find evidence that JSY reduces fetal and perinatal mortality but does not impact higher days mortality rates. Further, the spread of information about healthier pregnancies by health facilitators under the programs increases the use of antenatal services. On the one hand, JSY reduces the probability of women going back for a postpartum checkup. On the other hand, free maternal care services with zero postpartum care costs under JSSK increase their likelihood of returning for a checkup. Also, I find heterogeneity in programs\u27 impact with more educated and poorer women benefiting the most from them

Tuberculosis Prediction by Machine Learning Techniques

Tuberculosis is one of the top reasons of death all over the planet. Mycobacterium tuberculosis, bacteria that infects the lungs, is what causes it. For professionals working in the medical field, accurately identifying and timely predicting tuberculosis are major challenges. The course of treatment also varies from patient to patient since occasionally a patient develops drug resistance. Doctors will be given algorithmic support while using machine learning to help them diagnose, treat patients appropriately, and make quicker and better judgments. This paper discusses the many tuberculosis causes and symptoms as well as how accurate and fast prediction and diagnostic investigations have been carried out in recent years with the aid of machine learning (ML) technique

Adaptation of the Mahabharata, the Myth and Metaphor, into Animation for Children

Animation provides a unique window for children through which they could absorb the culturally superior Hindu epic in existence, the Mahabharata, the greatest myth and metaphor of life, and seek wisdom while entertaining themselves simultaneously. Concocting elements of fiction into the great myth in the form of animation gives a completely different perspective to children and show them a world of their own. The main motivation is to introduce them with the great heritage of India, the Mahabharata, in a lighter way through animation

Analysis of nucleosome positioning landscapes enables gene discovery in the human malaria parasite Plasmodium falciparum.

BackgroundPlasmodium falciparum, the deadliest malaria-causing parasite, has an extremely AT-rich (80.7 %) genome. Because of high AT-content, sequence-based annotation of genes and functional elements remains challenging. In order to better understand the regulatory network controlling gene expression in the parasite, a more complete genome annotation as well as analysis tools adapted for AT-rich genomes are needed. Recent studies on genome-wide nucleosome positioning in eukaryotes have shown that nucleosome landscapes exhibit regular characteristic patterns at the 5'- and 3'-end of protein and non-protein coding genes. In addition, nucleosome depleted regions can be found near transcription start sites. These unique nucleosome landscape patterns may be exploited for the identification of novel genes. In this paper, we propose a computational approach to discover novel putative genes based exclusively on nucleosome positioning data in the AT-rich genome of P. falciparum.ResultsUsing binary classifiers trained on nucleosome landscapes at the gene boundaries from two independent nucleosome positioning data sets, we were able to detect a total of 231 regions containing putative genes in the genome of Plasmodium falciparum, of which 67 highly confident genes were found in both data sets. Eighty-eight of these 231 newly predicted genes exhibited transcription signal in RNA-Seq data, indicative of active transcription. In addition, 20 out of 21 selected gene candidates were further validated by RT-PCR, and 28 out of the 231 genes showed significant matches using BLASTN against an expressed sequence tag (EST) database. Furthermore, 108 (47%) out of the 231 putative novel genes overlapped with previously identified but unannotated long non-coding RNAs. Collectively, these results provide experimental validation for 163 predicted genes (70.6%). Finally, 73 out of 231 genes were found to be potentially translated based on their signal in polysome-associated RNA-Seq representing transcripts that are actively being translated.ConclusionOur results clearly indicate that nucleosome positioning data contains sufficient information for novel gene discovery. As distinct nucleosome landscapes around genes are found in many other eukaryotic organisms, this methodology could be used to characterize the transcriptome of any organism, especially when coupled with other DNA-based gene finding and experimental methods (e.g., RNA-Seq)

Nanostructured Thick Electrode Strategies toward Enhanced Electrode-Electrolyte Interfaces

This article addresses the issue of bulk electrode design and the factors limiting the performance of thick electrodes. Indeed, one of the challenges for achieving improved performance in electrochemical energy storage devices (batteries or supercapacitors) is the maximization of the ratio between active and non-active components while maintaining ionic and electronic conductivity of the assembly. In this study, we developed and compared supercapacitor thick electrodes using commercially available carbons and utilising conventional, easily scalable methods such as spray coating and freeze-casting. We also compared different binders and conductive carbons to develop thick electrodes and analysed factors that determine the performance of such thick electrodes, such as porosity and tortuosity. The spray-coated electrodes showed high areal capacitances of 1428 mF cm at 0.3 mm thickness and 2459 F cm at 0.6 mm thickness